Advanced Trend Momentum [Alpha Extract]The Advanced Trend Momentum indicator provides traders with deep insights into market dynamics by combining exponential moving average analysis with RSI momentum assessment and dynamic support/resistance detection. This sophisticated multi-dimensional tool helps identify trend changes, momentum divergences, and key structural levels, offering actionable buy and sell signals based on trend strength and momentum convergence.
🔶 CALCULATION
The indicator processes market data through multiple analytical methods:
Dual EMA Analysis: Calculates fast and slow exponential moving averages with dynamic trend direction assessment and ATR-normalized strength measurement.
RSI Momentum Engine: Implements RSI-based momentum analysis with enhanced overbought/oversold detection and momentum velocity calculations.
Pivot-Based Structure: Identifies and tracks dynamic support and resistance levels using pivot point analysis with configurable level management.
Signal Integration: Combines trend direction, momentum characteristics, and structural proximity to generate high-probability trading signals.
Formula:
Fast EMA = EMA(Close, Fast Length)
Slow EMA = EMA(Close, Slow Length)
Trend Direction = Fast EMA > Slow EMA ? 1 : -1
Trend Strength = |Fast EMA - Slow EMA| / ATR(Period) × 100
RSI Momentum = RSI(Close, RSI Length)
Momentum Value = Change(Close, 5) / ATR(10) × 100
Pivot Support/Resistance = Dynamic pivot arrays with configurable lookback periods
Bullish Signal = Trend Change + Momentum Confirmation + Strength > 1%
Bearish Signal = Trend Change + Momentum Confirmation + Strength > 1%
🔶 DETAILS
Visual Features:
Trend EMAs: Fast and slow exponential moving averages with dynamic color coding (bullish/bearish)
Enhanced RSI: RSI oscillator with color-coded zones, gradient fills, and reference bands at overbought/oversold levels
Trend Fill: Dynamic gradient between EMAs indicating trend strength and direction
Support/Resistance Lines: Horizontal levels extending from pivot-based calculations with configurable maximum levels
Momentum Candles: Color-coded candlestick overlay reflecting combined trend and momentum conditions
Divergence Markers: Diamond-shaped signals highlighting bullish and bearish momentum divergences
Analysis Table: Real-time summary of trend direction, strength percentage, RSI value, and momentum reading
Interpretation:
Trend Direction: Bullish when Fast EMA crosses above Slow EMA with strength confirmation
Trend Strength > 1%: Strong trending conditions with institutional participation
RSI > 70: Overbought conditions, potential selling opportunity
RSI < 30: Oversold conditions, potential buying opportunity
Momentum Divergence: Price and momentum moving opposite directions signal potential reversals
Support/Resistance Proximity: Dynamic levels provide optimal entry/exit zones
Combined Signals: Trend changes with momentum confirmation generate high-probability opportunities
🔶 EXAMPLES
Trend Confirmation: Fast EMA crossing above Slow EMA with trend strength exceeding 1% and positive momentum confirms strong bullish conditions.
Example: During institutional accumulation phases, EMA crossovers with momentum confirmation have historically preceded significant upward moves, providing optimal long entry points.
15min
4H
Momentum Divergence Detection: RSI reaching overbought levels while momentum decreases despite rising prices signals potential trend exhaustion.
Example: Bearish divergence signals appearing at resistance levels have marked major market tops, allowing traders to secure profits before corrections.
Support/Resistance Integration: Dynamic pivot-based levels combined with trend and momentum signals create high-probability trading zones.
Example: Bullish trend changes occurring near established support levels offer optimal risk-reward entries with clearly defined stop-loss levels.
Multi-Dimensional Confirmation: The indicator's combination of trend, momentum, and structural analysis provides comprehensive market validation.
Example: When trend direction aligns with momentum characteristics near key structural levels, the confluence creates institutional-grade trading opportunities with enhanced probability of success.
🔶 SETTINGS
Customization Options:
Trend Analysis: Fast EMA Length (default: 12), Slow EMA Length (default: 26), Trend Strength Period (default: 14)
Support & Resistance: Pivot Length for level detection (default: 10), Maximum S/R Levels displayed (default: 3), Toggle S/R visibility
Momentum Settings: RSI Length (default: 14), Oversold Level (default: 30), Overbought Level (default: 70)
Visual Configuration: Color schemes for bullish/bearish/neutral conditions, transparency settings for fills, momentum candle overlay toggle
Display Options: Analysis table visibility, divergence marker size, alert system configuration
The Advanced Trend Momentum indicator provides traders with comprehensive insights into market dynamics through its sophisticated integration of trend analysis, momentum assessment, and structural level detection. By combining multiple analytical dimensions into a unified framework, this tool helps identify high-probability opportunities while filtering out market noise through its multi-confirmation approach, enabling traders to make informed decisions across various market cycles and timeframes.
Поиск скриптов по запросу "support resistance"
Supertrend - Support & ResistanceSupertrend – Multi-Timeframe Support & Resistance
This script overlays multiple Supertrend bands from higher timeframes on a single chart and treats them as dynamic support and resistance. The goal is simple: see the bigger picture without leaving your current timeframe.
What it does
• Calculates Supertrend using the same ATR Length and Factor across 5m, 15m, 30m, 1h, 4h, 8h, 12h, and 1D.
• Pulls each timeframe via request.security(..., lookahead_off) so values only update on candle close. No look-ahead, no “teleporting” lines.
• Plots each timeframe’s Supertrend as an on-chart band with increasing transparency the higher you go, so you can visually separate short-term vs higher-timeframe structure.
• Colors indicate direction:
• Green = bearish band above price (acting as resistance)
• Red = bullish band below price (acting as support)
• Drops compact labels (5m, 15m, 30m, etc.) every 20 bars right on the corresponding Supertrend level, so you can quickly identify which line belongs to which timeframe.
Why this helps
Supertrend is great for trend definition and trailing stops. But one timeframe alone can whipsaw you. By stacking multiple timeframes:
• Confluence stands out. When several higher-TF bands cluster, price often reacts.
• You see where intraday pullbacks are likely to pause (lower TF bands) and where trend reversals are more meaningful (higher TF bands).
• It’s easier to align entries with the dominant trend while still timing them on your working timeframe.
How it works (quick refresher)
Supertrend uses ATR to offset a median price with a multiplier (Factor). When price crosses the band, direction flips and the trailing line switches sides. This script exposes:
• ATR Length (default 10): sensitivity of the ATR. Smaller = tighter band, more flips. Larger = smoother, fewer flips.
• Factor (default 3.0): multiplier applied to ATR. Larger = wider band, more conservative.
The same settings are used for all timeframes for clean, apples-to-apples comparisons.
How to use it
• Trend alignment: Prefer longs when most higher-TF lines are below price (red support). Prefer shorts when most are above price (green resistance).
• Pullback entries: In an uptrend, look for pullbacks into a lower-TF red band that lines up near a higher-TF red band. That overlap is your “zone.”
• Breakout confirmation: A strong break and close beyond a higher-TF band carries more weight than a lower-TF poke.
• Stops and targets: Use the nearest opposing band as a logic point. For example, in a long, if price loses the lower-TF red band and the next higher-TF band is close overhead, trim or tighten.
Signals you can read at a glance
• Stacking: Multiple red bands beneath price = strong bullish structure. Multiple green bands above price = strong bearish structure.
• Compression: Bands from different TFs squeezing together often precede expansion.
• Flip zones: When a higher-TF band flips side, treat that level as newly minted support/resistance.
Design choices in the code
• lookahead_off on all request.security calls avoids repainting from future data.
• Increasing transparency as the timeframe rises makes lower-TF context visible without drowning the chart.
• Labels every 20 bars keep the chart readable while still giving you frequent anchors.
Good to know (limits and tips)
• This is an overlay of closed-bar Supertrend values from higher TFs. Intrabar moves can still exceed a band before close; final signal prints at candle close of that timeframe.
• Using the same ATR/factor across TFs makes confluence easier to judge. If you need independent tuning per TF, you can clone the security calls and add separate inputs.
• On very low timeframes with many symbols, multiple request.security calls can be heavy. If performance drops, hide one or two higher TFs or increase the label spacing.
Risk note
This is a context tool, not an auto-trader. Combine it with structure (HH/HL vs LH/LL), volume, and your execution rules. Always test on your market and timeframe before committing real capital.
SHA Multi Pivot Points -v1.0.0🔎Using Pivot Points in Trading
Traders use PPs to help determine predefined support and resistance levels to guide their trading strategies. In addition, traders identify potential price reversals, trend direction, and breakout opportunities:
Trend identification: PPs act as a reference level to gauge market sentiment. If the price opens above the PP and remains above it, traders interpret this as an uptrend. Conversely, if the price opens below the pivot point and stays below, it suggests a downtrend.
Support and resistance determination: Pivot levels are natural barriers where price reactions frequently occur. Traders may enter long positions near support levels, expecting a price bounce, or if the price approaches resistance levels, traders may consider shorting the asset.
Breakout trading: When the price breaks above resistance or support, it may indicate strong momentum for further movement.
Reversal identification: Traders also look for failed breakouts or price rejections at pivot levels to anticipate reversals.
Trading strategy combinations: Traders can improve accuracy by combining PPs with other technical analysis indicators.
1. Camarilla Pivot Points
📌 Overview:
Developed by Nick Scott in 1989, Camarilla Pivot Points are designed for short-term, intraday trading. Unlike traditional pivots, Camarilla levels are tighter and more responsive, making them useful in volatile markets.
📐 Key Levels:
It generates eight levels:
- Resistance: Initial Level (R1), Mid-range Level (R2), Sell Reversal Level (R3), Breakout Level (R4)
- Support: Initial Level (S1), Mid-range Level (S2), Buy Reversal Level (S3), Breakout Level (S4)
✅ How to Use:
- S1/R1 + RSI or volume divergence to confirm weak momentum and early reversals.
- S2/R2 with price action patterns to enter early on major moves before L3/H3 get tested.
- S3/R3: Mean-reversion zones → price often reverses.
- Break of S4/R4: Strong breakout → trend-following signal.
- Combine with volume or candlestick confirmation for entries.
🔹 2. Floor (Standard) Pivot Points
📌 Overview:
This is the most traditional pivot method, widely used by floor traders. It’s symmetrical and provides a clear central pivot point with equally spaced support and resistance levels.
📐 Key Levels:
- Povit Points : Average price (PPs)
- Resistance : First price ceiling (R1), Stronger ceiling (R2), Extreme resistance (R3)
- Support : First price floor (S1), Stronger floor (S2), Extreme support (S3)
✅ How to Use:
- Above PPs = bullish bias; Below PPs = bearish bias.
- S1/R1 are most used for intraday targets.
- S2–S3/R2–R3 indicate potential extreme moves.
- Often used in combination with momentum indicators.
🔹 3. Woodie Pivot Points
📌 Overview:
Woodie’s pivot formula gives double weight to the closing price, emphasizing the most recent session's sentiment.
📐 Key Levels:
- Povit Points : Weighted average (PPs)
- Resistance : First price ceiling (R1), Stronger resistance (R2)
- Support : First price floor (S1), Stronger support (S2)
✅ How to Use:
- Works best in fast-moving markets.
- PPs acts as a momentum-based balance level.
- Good for scalpers and momentum traders.
🔹 4. Fusion Pivot Points
📌 Overview:
This method differs significantly — it calculates only one support and one resistance level, adjusting based on the relationship between the open and close.
📐 Key Levels:
- Povit Points : Single directional (PPs)
- Resistance : Potential ceiling (R)
- Support : Potential floor (S)
✅ How to Use:
- Not symmetrical → more responsive to price behavior.
- Best for breakout or reversal strategies.
- Use when you're expecting directional momentum.
🔹 5. Classic Pivot Points (Traditional)
📌 Overview:
Also known as Standard or Traditional Pivot Points, this is the default method used by most charting platforms. It offers a balanced and simple framework.
📐 Key Levels:
- Povit Points : Central price level (PPs)
- Resistance : First ceiling (R1), Stronger resistance (R2), Extreme resistance (R3)
- Support : First floor (S1), Stronger floor (S2), Extreme support (S3)
✅ How to Use:
- PPs is the market’s equilibrium point.
- Helps define market structure, bias, and trade zones.
- Combine with order blocks, RSI, or MACD for confirmation.
📊 Summary Comparison :
1. Camarilla Pivot Points
- Focus : Mean Reversion & Breakouts
- Best Use : Scalping, Day Trading
2. Floor Pivot Points
- Focus : General Support/Resistance
- Best Use : Intraday, Swing
3. Woodie Pivot Points
- Focus : Recent Close Emphasis
- Best Use : Momentum Trading
4. Fusion Pivot Points
- Focus : Trend/Breakout
- Best Use : Directional Breakouts
5. Classic Povit Points
- Focus : Market Structure
- Best Use : General Use
⚠️ Disclaimer
The information and tools provided in this script are for educational and informational purposes only. They do not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instrument.
Trading in the financial markets involves risk of loss and is not suitable for every investor. You are solely responsible for your trading decisions. Always do your own research, use proper risk management, and consult a licensed financial advisor before making any financial decisions.
RSI + MA + Divergence + SnR + Price levelOverview
This indicator combines several technical analysis tools to give traders a comprehensive view based on the RSI indicator. Its main features include:
RSI & Moving Averages on RSI:
RSI: Calculates the RSI based on the closing price (or a user-selected source) with a configurable period (default is 14).
EMA and WMA: Computes and plots an Exponential Moving Average (EMA with a period of 9) and a Weighted Moving Average (WMA with a period of 45) on the RSI, helping to smooth out signals and better identify trends.
Price Ladder Based on RSI:
Draws horizontal lines at specified target RSI levels (from targetRSI1 to targetRSI7, default levels ranging from 20 to 80).
Calculates a target price based on the price change relative to the averaged gains and losses, providing an estimated price level when the RSI reaches those critical levels.
Divergence Detection:
Identifies divergence between price and RSI:
Bullish Divergence: Detected when the price forms a lower low but RSI fails to confirm with a corresponding lower low, with the RSI falling under a configurable threshold (d_below).
Bearish Divergence: Detected when the price forms a higher high while the RSI does not, with the RSI exceeding a configurable upper threshold (d_upper).
Optionally displays labels on the chart to alert the trader when divergence signals are detected.
Auto Support & Resistance on RSI:
Automatically calculates and plots support and resistance lines based on the RSI over different lookback periods (e.g., 34, 89, 200 bars).
Helps traders identify key RSI levels where price reversals or breakouts might occur.
Benefits for the Trader
This indicator is designed to assist traders in their decision-making process by integrating multiple technical analysis elements:
Identifying Market Trends:
By combining the RSI with its moving averages (EMA, WMA), traders can better assess market trends and the strength of these trends, thereby improving trade entry accuracy.
Early Reversal Signals via Divergence:
Divergence signals (both bullish and bearish) can help forecast potential reversals in the market, allowing traders to adjust their strategies timely.
Determining RSI-Based Support/Resistance Levels:
Automatic identification of support and resistance levels on the RSI provides key areas where a price reversal or breakout may occur, assisting traders in setting stop-loss and take-profit levels strategically.
Price Target Forecasting with the Price Ladder:
The target price labels calculated at important RSI levels provide insights into potential price objectives, aiding in risk management and profit planning.
Flexible Configuration:
Traders can customize key parameters such as the RSI period, lengths for EMA and WMA, target RSI levels, divergence conditions, and support/resistance settings. This flexibility allows the indicator to adapt to different trading styles and strategies.
How to read data
Some use-cases
Used to estimate price according to the RSI level.
When you trade using RSI, you want to set your stop-loss or take-profit levels based on RSI. By looking at the price ladder, you know the corresponding price level to enter a trade.
Used to determine the entry zone.
RSI often reacts to its own previously established support/resistance levels. Use the Auto SnR feature to identify those zones.
Used to determine the trend.
RSI and its moving averages help identify the price trend:
Uptrend: 3 lines separate and point upward.
Downtrend: 3 lines separate and point downward.
Use WMA45 to determine the trend:
Uptrend: WMA45 is moving upward or trading above the 50 level.
Downtrend: WMA45 is moving downward or trading below the 50 level.
Sideways: WMA45 is trading around the 50 level.
Use EMA9 to confirm the trend: A crossover of EMA9 through WMA45 confirms the formation of a new trend.
Configuration
The script allows users to configure a number of important parameters to suit their analytical preferences:
RSI Settings:
RSI Length (rsiLengthInput): The number of periods used to compute the RSI (default is 14, adjustable as needed).
RSI Source (rsiSourceInput): Select the price source (default is the closing price).
RSI Color (rsiClr): The color used to display the RSI line.
Moving Averages on RSI:
EMA Length (emaLength): The period for calculating the EMA on RSI (default is 9).
WMA Length (wmaLength): The period for calculating the WMA on RSI (default is 45).
EMA Color (emaClr) and WMA Color (wmaClr): Customize the colors of the EMA and WMA lines.
Price Ladder Settings:
Toggle Price Ladder (showPrice): Enable or disable the display of the price ladder.
Target RSI Levels: targetRSI1 through targetRSI7: RSI values at which target prices are calculated (default values range from 20, 30, 40, 50, 60, 70 to 80).
Price Label Color (priceColor): The text color for displaying the target price labels.
Divergence Settings:
Divergence Toggle (calculateDivergence): Option to enable or disable divergence calculation and display.
Divergence Conditions:
d_below: RSI level below which bullish divergence is considered.
d_upper: RSI level above which bearish divergence is considered.
Display Divergence Labels (showDivergenceLabel): Option to display labels on the chart when divergence is detected.
Auto Support & Resistance on RSI:
Toggle Auto S&R (enableAutoSnR): Enable or disable automatic plotting of support and resistance levels.
Lookback Periods for Support/Resistance:
L1_lookback: Lookback period for level 1 (e.g., 34 bars).
L2_lookback: Lookback period for level 2 (e.g., 89 bars).
L3_lookback: Lookback period for level 3 (e.g., 200 bars).
Support and Resistance Colors:
rsiSupportClr: Color for the support line.
rsiResistanceClr: Color for the resistance line.
Alerts:
Divergence Alerts: Alert conditions are set up to notify the trader when bullish or bearish divergence is detected, aiding in timely decision-making.
Ehlers Adaptive Trend Indicator [Alpha Extract]Ehlers Adaptive Trend Indicator
The Ehlers Adaptive Trend Indicator combines Ehlers' advanced digital signal processing techniques with dynamic volatility bands to identify robust trend conditions and potential reversals. This powerful tool helps traders visualize trend strength, adaptive support/resistance levels, and momentum shifts across various market conditions.
🔶 CALCULATION
The indicator employs a sophisticated adaptive algorithm that responds to changing market conditions:
• Ehlers Filter : Calculates a weighted average based on momentum differences to create an adaptive trend baseline.
• Dynamic Bands : Volatility-adjusted bands that expand and contract based on recent price action.
• Trend Level : A dynamic support/resistance level that adapts to the current trend direction.
• Smoothed Volatility : Market volatility measured and smoothed to provide reliable band width.
Formula:
• Ehlers Basis = Weighted average of price, with weights determined by momentum differences
• Volatility = Standard deviation of price over Ehlers Length period
• Smoothed Volatility = EMA of volatility over Smoothing Length
• Upper Band = Ehlers Basis + Smoothed Volatility × Sensitivity
• Lower Band = Ehlers Basis - Smoothed Volatility × Sensitivity
• Trend Level = Adaptive support in uptrends, resistance in downtrends
🔶 DETAILS
Visual Features :
• Ehlers Basis Line (Yellow): The core adaptive trend reference that serves as the primary trend indicator.
• Trend Level Line (Dynamic Color): Changes between green (bullish) and red (bearish) based on the current trend state.
• Fill Areas : Transparent green fill during bullish trends and transparent red fill during bearish trends for clear visual identification.
• Bar Coloring : Optional price bar coloring that reflects the current trend direction for enhanced visualization.
Interpretation :
• **Bullish Signal**: Price crosses above the upper band, triggering a trend change with the Trend Level becoming dynamic support.
• **Bearish Signal**: Price drops below the lower band, confirming a trend change with the Trend Level becoming dynamic resistance.
• **Trend Continuation**: Trend Level rises in bullish markets and falls in bearish markets, providing adaptive trailing support/resistance.
🔶 EXAMPLES
The chart demonstrates:
• Bullish Trend Identification : When price breaks above the upper band, the indicator shifts to bullish mode with green trend level and fill.
• Bearish Trend Identification : When price falls below the lower band, the indicator shifts to bearish mode with red trend level and fill.
• Trend Persistence : Trend Level adapts to market movement, rising during uptrends to provide dynamic support and falling during downtrends to act as resistance.
Example Snapshots :
• During a strong uptrend, the Trend Level continuously adjusts upward, keeping traders in the trend while filtering out minor retracements.
• During trend reversals, clear color changes and Trend Level shifts provide early warning of potential direction changes.
🔶 SETTINGS
Customization Options :
• Ehlers Length (p1) (Default: 30): Controls the primary adaptive calculation period, balancing responsiveness with stability.
• Momentum Length (p2) (Default: 25): Determines the lag for momentum calculations used in the adaptive weighting.
• Smoothing Length (Default: 10): Adjusts the volatility smoothing period—higher values provide more stable bands.
• Sensitivity (Default: 1.0): Multiplier for band width—higher values increase distance between bands, lower values tighten them.
• Visual Settings : Customizable colors for bullish and bearish trends, basis line, and optional bar coloring.
The Ehlers Adaptive Trend Indicator combines John Ehlers' digital signal processing expertise with modern volatility analysis to create a robust trend-following system that adapts to changing market conditions, helping traders stay on the right side of the market.
DTFX Algo Zones [SamuraiJack Mod]CME_MINI:NQ1!
Credits
This indicator is a modified version of an open-source tool originally developed by Lux Algo. I literally modded their indicator to create the DTFX Algo Zones version, incorporating additional features and refinements. Special thanks to Lux Algo for their original work and for providing the open-source code that made this development possible.
Introduction
DTFX Algo Zones is a technical analysis indicator designed to automatically identify key supply and demand zones on your chart using market structure and Fibonacci retracements. It helps traders spot high-probability reversal areas and important support/resistance levels at a glance. By detecting shifts in market structure (such as Break of Structure and Change of Character) and highlighting bullish or bearish zones dynamically, this tool provides an intuitive framework for planning trades. The goal is to save traders time and improve decision-making by focusing attention on the most critical price zones where market bias may confirm or reverse.
Logic & Features
• Market Structure Shift Detection (BOS & CHoCH): The indicator continuously monitors price swings and marks significant structure shifts. A Break of Structure (BOS) occurs when price breaks above a previous swing high or below a swing low, indicating a continuation of the current trend. A Change of Character (ChoCH) is detected when price breaks in the opposite direction of the prior trend, often signaling an early trend reversal. These moments are visually marked on the chart, serving as anchor points for new zones. By identifying BOS and ChoCH in real-time, the DTFX Algo Zones indicator ensures you’re aware of key trend changes as they happen.
• Auto-Drawn Fibonacci Supply/Demand Zones: Upon a valid structure shift, the indicator plots a Fibonacci-based zone between the breakout point and the preceding swing high/low (the source of the move). This creates a shaded area or band of Fibonacci retracement levels (for example 38.2%, 50%, 61.8%, etc.) representing a potential support zone in an uptrend or resistance zone in a downtrend. These supply/demand zones are derived from the natural retracement of the breakout move, highlighting where price is likely to pull back. Each zone is essentially an auto-generated Fibonacci retracement region tied to a market structure event, which traders can use to anticipate where the next pullback or bounce might occur.
• Dynamic Bullish and Bearish Zones: The DTFX Algo Zones indicator distinguishes bullish vs. bearish zones and updates them dynamically as new price action unfolds. Bullish zones (formed after bullish BOS/ChoCH) are typically highlighted in one color (e.g. green or blue) to indicate areas of demand/support where price may bounce upward. Bearish zones (formed after bearish BOS/ChoCH) are shown in another color (e.g. red/orange) to mark supply/resistance where price may stall or reverse downward. This color-coding and real-time updating allow traders to instantly recognize the market bias: for instance, a series of bullish zones implies an uptrend with multiple support levels on pullbacks, while consecutive bearish zones indicate a downtrend with resistance overhead. As old zones get invalidated or new ones appear, the chart remains current with the latest key levels, eliminating clutter from outdated levels.
• Flexible Customization: The indicator comes with several options to tailor the zones to your trading style. You can filter which zones to display – for example, show only the most recent N zones or limit to only bullish or only bearish zones – helping declutter the chart and focus on recent, relevant levels. There are settings to control zone extension (how far into the future the zones are drawn) and to automatically invalidate zones once they’re no longer relevant (for instance, if price fully breaks through a zone or a new structure shift occurs that supersedes it). Additionally, the Fibonacci retracement levels within each zone are customizable: you can choose which retracement percentages to plot, adjust their colors or line styles, and decide whether to fill the zone area for visibility. This flexibility ensures the DTFX Algo Zones can be tuned for different markets and strategies, whether you want a clean minimalist look or detailed zones with multiple internal levels.
Best Use Cases
DTFX Algo Zones is a versatile indicator that can enhance various trading strategies. Some of its best use cases include:
• Identifying High-Probability Reversal Zones: Each zone marks an area where price has a higher likelihood of stalling or reversing because it reflects a significant prior swing and Fibonacci retracement. Traders can watch these zones for entry opportunities when the market approaches them, as they often coincide with order block or strong supply/demand areas. This is especially useful for catching trend reversals or pullbacks at points where risk is lower and potential reward is higher.
• Spotting Key Support and Resistance: The automatically drawn zones act as dynamic support (below price) and resistance (above price) levels. Instead of manually drawing Fibonacci retracements or support/resistance lines, you get an instant map of the key levels derived from recent price action. This helps in quickly identifying where the next bounce (support) or rejection (resistance) might occur. Swing traders and intraday traders alike can use these zones to set alerts or anticipate reaction areas as the market moves.
• Trend-Following Entries: In a trending market, the indicator’s zones provide ideal areas to join the trend on pullbacks. For example, in an uptrend, when a new bullish zone is drawn after a BOS, it indicates a fresh demand zone – buying near the lower end of that zone on a pullback can offer a low-risk entry to ride the next leg up. Similarly, in a downtrend, selling rallies into the highlighted supply zones can position you in the direction of the prevailing trend. The zones effectively serve as a roadmap of the trend’s structure, allowing trend traders to buy dips and sell rallies with greater confidence.
• Mean-Reversion and Range Trading: Even in choppy or range-bound markets, DTFX Algo Zones can help find mean-reversion trades. If price is oscillating sideways, the zones at extremes of the range might mark where momentum is shifting (ChoCH) and price could swing back toward the mean. A trader might fade an extended move when it reaches a strong zone, anticipating a reversion. Additionally, if multiple zones cluster in an area across time (creating a zone overlap), it often signifies a particularly robust support/resistance level ideal for range trading strategies.
In all these use cases, the indicator’s ability to filter out noise and highlight structurally important levels means traders can focus on higher-probability setups and make more informed trading decisions.
Strategy – Pullback Trading with DTFX Algo Zones
One of the most effective ways to use the DTFX Algo Zones indicator is trading pullbacks in the direction of the trend. Below is a step-by-step strategy to capitalize on pullbacks using the zones, combining the indicator’s signals with sound price action analysis and risk management:
1. Identify a Market Structure Shift and Trend Bias: First, observe the chart for a recent BOS or ChoCH signal from the indicator. This will tell you the current trend bias. For instance, a bullish BOS/ChoCH means the market momentum has shifted upward (bullish bias), and a new demand zone will be drawn. A bearish structure break indicates downward momentum and creates a supply zone. Make sure the broader context supports the bias (e.g., if multiple higher timeframe zones are bullish, focus on long trades).
2. Wait for the Pullback into the Zone: Once a new zone appears, don’t chase the price immediately. Instead, wait for price to retrace back into that highlighted zone. Patience is key – let the market come to you. For a bullish setup, allow price to dip into the Fibonacci retracement zone (demand area); for a bearish setup, watch for a rally into the supply zone. Often, the middle of the zone (around the 50% retracement level) can be an optimal area where price might slow down and pivot, but it’s wise to observe price behavior across the entire zone.
3. Confirm the Entry with Price Action & Confluence: As price tests the zone, look for confirmation signals before entering the trade. This can include bullish reversal candlestick patterns (for longs) or bearish patterns (for shorts) such as engulfing candles, hammers/shooting stars, or doji indicating indecision turning to reversal. Additionally, incorporate confluence factors to strengthen the setup: for example, check if the zone overlaps with a key moving average, a round number price level, or an old support/resistance line from a higher timeframe. You might also use an oscillator (like RSI or Stochastic) to see if the pullback has reached oversold conditions in a bullish zone (or overbought in a bearish zone), suggesting a bounce is likely. The more factors aligning at the zone, the more confidence you can have in the trade. Only proceed with an entry once you see clear evidence of buyers defending a demand zone or sellers defending a supply zone.
4. Enter the Trade and Manage Risk: When you’re satisfied with the confirmation (e.g., price starts to react positively off a demand zone or shows rejection wicks in a supply zone), execute your entry in the direction of the original trend. Immediately set a stop-loss order to control risk: for a long trade, a common placement is just below the demand zone (a few ticks/pips under the swing low that formed the zone); for a short trade, place the stop just above the supply zone’s high. This way, if the zone fails and price continues beyond it, your loss is limited. Position size the trade so that this stop-loss distance corresponds to a risk you are comfortable with (for example, 1-2% of your trading capital).
5. Take Profit Strategically: Plan your take-profit targets in advance. A conservative approach is to target the origin of the move – for instance, in a long trade, you might take profit as price moves back up to the swing high (the 0% Fibonacci level of the zone) or the next significant zone or resistance level above. This often yields at least a 1:1 reward-to-risk ratio if you entered around mid-zone. More aggressive trend-following traders may leave a portion of the position running beyond the initial target, aiming for a larger move in line with the trend (for example, new higher highs in an uptrend). You can also trail your stop-loss upward behind new higher lows (for longs) or lower highs (for shorts) as the trend progresses, locking in profit while allowing for further gains.
6. Monitor Zone Invalidation: Even after entering, keep an eye on the behavior around the zone and any new zones that may form. If price fails to bounce and instead breaks decisively through the entire zone, respect that as an invalidation – the market may be signaling a deeper reversal or that the signal was false. In such a case, it’s better to exit early or stick to your stop-loss than to hold onto a losing position. The indicator will often mark or no longer highlight zones that have been invalidated by price, guiding you to shift focus to the next opportunity.
Risk Management Tips:
• Always use a stop-loss and don’t move it farther out in hope. Placing the stop just beyond the zone’s far end (the swing point) helps protect you if the pullback turns into a larger reversal.
• Aim for a favorable risk-to-reward ratio. With pullback entries near the middle or far end of a zone, you can often achieve a reward that equals or exceeds your risk. For example, risking 20 pips to make 20+ pips (1:1 or better) is a prudent starting point. Adjust targets based on market structure – if the next resistance is 50 pips away, consider that upside against your risk.
• Use confluence and context: Don’t take every zone signal in isolation. The highest probability trades come when the DTFX Algo Zone aligns with other analysis (trend direction, chart patterns, higher timeframe support/resistance, etc.). This filtered approach will reduce trades taken in weak zones or counter-trend traps.
• Embrace patience and selectivity: Not all zones are equal. It can be wise to skip very narrow or insignificant zones and wait for those that form after a strong BOS/ChoCH (indicating a powerful move). Larger zones or zones formed during high-volume times tend to produce more reliable pullback opportunities.
• Review and adapt: After each trade, note how price behaved around the zone. If you notice certain Fib levels (like 50% or 61.8%) within the zone consistently provide the best entries, you can refine your approach to focus on those. Similarly, adjust the indicator’s settings if needed – for example, if too many minor zones are cluttering your screen, limit to the last few or increase the structure length parameter to capture only more significant swings.
⸻
By combining the DTFX Algo Zones indicator with disciplined confirmation and risk management, traders can improve their timing on pullback entries and avoid chasing moves. This indicator shines in helping you trade what you see, not what you feel – the clearly marked zones and structure shifts keep you grounded in price action reality. Whether you’re a trend trader looking to buy the dip/sell the rally, or a reversal trader hunting for exhaustion points, DTFX Algo Zones provides a robust visual aid to elevate your trading decisions. Use it as a complementary tool in your analysis to stay on the right side of the market’s structure and enhance your trading performance.
dynamic support and resistance v3**Automatic Multi-Timeframe & Dynamic Support/Resistance Indicator**
This indicator automatically identifies and plots key Support and Resistance levels across multiple timeframes (1H, 4H, Daily) and dynamically adapts to the chart's current timeframe. It provides a comprehensive view of potential price reversal zones, helping traders make more informed decisions.
**Key Features:**
* **Multi-Timeframe Analysis:** Automatically calculates and displays Support and Resistance levels derived from the 1-hour, 4-hour, and Daily timeframes. This allows you to see the bigger picture and anticipate potential price reactions at significant levels. Levels from higher timeframes are often stronger.
* **Dynamic Support & Resistance:** Beyond the fixed timeframe levels, the indicator also dynamically calculates and plots Support and Resistance based on the *currently visible* timeframe of your chart. This ensures you always have relevant levels, regardless of whether you're zoomed in on a 1-minute chart or looking at a weekly view. This dynamic calculation adapts to changing market conditions.
* **Combined View:** All identified Support and Resistance levels (from all timeframes) are plotted on the same chart. This gives you a clear and concise overview of potential areas of interest, simplifying your analysis. Different colors or styles can be used to distinguish between timeframes (e.g., Daily levels could be thicker lines, 4H thinner, and 1H dashed).
* **Customizable:** (Optional - Mention if you offer customization) The indicator may include customizable settings, such as:
* Lookback period for dynamic S/R calculation.
* Strength/sensitivity adjustments for identifying levels.
* Color and style customization for different timeframes.
* Option to toggle visibility of specific timeframe levels.
**Benefits:**
* **Saves Time:** No more manually drawing Support and Resistance lines. The indicator does the work for you.
* **Improved Accuracy:** The automated calculations can help identify key levels that might be missed by manual analysis.
* **Enhanced Visualization:** Seeing all relevant S/R levels on one chart provides a clearer picture of potential price action.
* **Adaptable to Any Timeframe:** Whether you're a scalper or a long-term investor, the dynamic S/R adapts to your trading style.
**How to Use:**
Simply add the indicator to your TradingView chart. The Support and Resistance levels will be automatically calculated and displayed. Use these levels to identify potential entry and exit points, stop-loss placements, and areas where price might encounter resistance or find support.
**Disclaimer:**
This indicator is for informational and educational purposes only. It should not be considered financial advice. Trading involves risk, and you should always do your own research before making any investment decisions. Past performance is not indicative of future results.
Enhanced SMA Strategy with Trend Lines & S&R by DaxThe Enhanced SMA Strategy with Trend Lines & Support/Resistance (S&R) by Dax indicator is a technical analysis tool designed to improve trading decisions by combining the simplicity of the Simple Moving Average (SMA) with the insight provided by trend lines and support/resistance levels. This hybrid approach aims to create a more robust and reliable trading strategy.
Key Components:
Simple Moving Average (SMA):
SMA is a basic trend-following indicator that calculates the average of a set of price data over a specified period. It helps identify the direction of the market, such as whether an asset is in an uptrend or downtrend.
The Enhanced SMA Strategy may use multiple SMAs, such as short-term (e.g., 20-period) and long-term (e.g., 50-period), to detect crossovers that signal buy or sell opportunities. For example, a bullish crossover occurs when a short-term SMA crosses above a long-term SMA, indicating a potential buying signal, while a bearish crossover signals a potential sell.
Trend Lines:
Trend lines are drawn on the price chart to visually identify the direction of the market, acting as dynamic support and resistance levels. A trend line is drawn by connecting two or more price points that demonstrate the overall price movement.
Trend lines can help traders see potential breakout or breakdown points. A price breaking above a downtrend line or below an uptrend line often signals a trend reversal.
Support and Resistance (S&R):
Support levels are price levels where an asset tends to find buying interest and stop falling, while Resistance levels are points where selling pressure emerges and prevent the price from rising further.
These levels are critical in determining where price reversals or consolidations are likely to occur. Enhanced S&R indicators can automatically identify these levels and draw horizontal lines at these critical points on the chart.
Combining S&R with SMA can help traders decide whether a breakout or bounce is likely at these levels, increasing the odds of a successful trade.
How It Works:
Trend Identification: The SMA is used to determine the trend direction. A rising SMA indicates an uptrend, while a falling SMA suggests a downtrend.
Signal Generation: The strategy often uses a combination of SMA crossovers (bullish or bearish) along with the confirmation of price action near trend lines and support/resistance levels. For example:
If a price breaks above resistance and the short-term SMA crosses above the long-term SMA, a buy signal is confirmed.
Conversely, if the price breaks below support and the short-term SMA crosses below the long-term SMA, a sell signal is given.
Dynamic Support/Resistance: Trend lines are drawn automatically or manually to spot areas where price might reverse. The Enhanced SMA Strategy checks if the price is close to these levels, providing a more precise entry/exit point based on the broader market context.
Advantages of the Enhanced SMA Strategy with Trend Lines & S&R:
Improved Accuracy: By combining trend-following (SMA) with key levels like trend lines and S&R, the strategy filters out false signals, leading to more reliable trade setups.
Trend Confirmation: The use of trend lines and S&R confirms the broader market context, reducing the risk of trading against the trend or entering at weak price points.
Flexible: This strategy can be applied to various timeframes, from short-term day trading to longer-term swing trading.
Visual Clarity: The combination of trend lines, S&R, and moving averages provides a clear and visually intuitive strategy for identifying key price levels and trend shifts.
How to Use It:
Draw Trend Lines: Identify the most recent price peaks and troughs to draw trend lines, marking the potential resistance and support levels.
Use SMAs: Apply two different-period SMAs to detect the trend (e.g., 20-period and 50-period). Pay attention to crossovers for buy/sell signals.
Watch for Breakouts or Reversals: Monitor how the price behaves at support or resistance levels and the trend lines. A price move beyond these levels, accompanied by a confirming SMA crossover, can signal a strong trade opportunity.
Conclusion:
The Enhanced SMA Strategy with Trend Lines & S&R by Dax is a powerful, multi-layered approach to technical analysis. It enhances the basic SMA strategy by incorporating additional tools like trend lines and support/resistance levels, which help traders make more informed decisions with higher accuracy. This method is suitable for both novice and experienced traders, offering clear trade signals while reducing the risk of false entries.
MERCURY by DrAbhiramSivprasad"MERCURY by DrAbhiramSivprasad"
Developed from over 10 years of personal trading experience, the Mercury Indicator is a strategic tool designed to enhance accuracy in trading decisions. Think of it as a guiding light—a supportive tool that helps traders refine and build more robust strategies by integrating multiple powerful elements into a single indicator. I’ll be sharing some examples to illustrate how I use this indicator in my own trading journey, highlighting its potential to improve strategy accuracy.
Reason behind the combination of emas , cpr and vwap is it provides very good support and resistance in my trading carrier so now i brought them together in one plate
How It Works:
Mercury combines three essential elements—EMA, VWAP, and CPR—each of which plays a vital role in detecting support and resistance:
Exponential Moving Averages (EMAs): Known for their strength in providing dynamic support and resistance levels, EMAs help in identifying trends and shifts in momentum. This indicator includes a dashboard with up to nine customizable EMAs, showing whether each is acting as support or resistance based on real-time price movement.
Volume Weighted Average Price (VWAP): VWAP also provides valuable support and resistance, often regarded as a fair price level by institutional traders. Paired with EMAs, it forms a dual-layered support/resistance system, adding an additional level of confirmation.
Central Pivot Range (CPR): By combining CPR with EMAs and VWAP, Mercury highlights “traffic blocks” in your target journey. This means it identifies zones where price is likely to stall or reverse, providing additional guidance for navigating entries and exits.
Why This Combination Matters:
Using these three tools together gives you a more complete view of the market. VWAP and EMAs offer dynamic trend direction and support/resistance, while CPR pinpoints critical price zones. This combination helps you find high-probability trades, adding clarity to complex market situations and enabling stronger confirmation on trend or reversal decisions.
How to Use:
Trend Confirmation: Check if all EMAs are aligned (green for uptrend, red for downtrend), which is visible in the EMA dashboard. An alignment across VWAP, CPR, and EMAs signifies high confidence in trend direction.
Breakouts & Breakdowns: Mercury has an alert system to signal when a price breakout or breakdown occurs across VWAP, EMA1, and EMA2. This can help in spotting strong directional moves.
Example Application: In my trading, I use Mercury to identify support/resistance zones, confirming trends with EMA/VWAP alignment and using CPR as a checkpoint. I find this especially useful for day trading and swing setups.
Recommended Timeframes:
Day Trading: 5 to 15-minute charts for swift, actionable insights.
Swing Trading: 1-hour or 4-hour charts for broader trend analysis.
Note:
The Mercury Indicator should be used as a supportive tool rather than a standalone strategy, guiding you toward informed decisions in line with your trading style and goals.
EXAMPLE OF TRADE
you can see the cart of XAUUSD on 11th nov 2024
1.SHORT POSITION - TIME FRAME 15 MIN
So here for a short position you need to wait for a breakdown candle which will print in orange post the candle you need to check ema dashboard is completly red that indicates no traffic blocks in your journey to destiny target from ema's and you can take the target from nearest cpr support line
TAKEN IN XAUUSD you can see in chart of XAUUSD on 7th nov
2.LONG POSITION - TIME FRAME 15 MIN -
So here for long position you need to wait for a breakout candle from indicator thats here is blue and check all ema boxes are green and candle body should close above all the 3 lines here it is the both ema 1 and 2 and the vwap line then you can take and entry and your target will be the nearest resistance from the daily cpr
3. STOP LOSS CRITERIA
After the entry any candle close below any of the last line from entry for example we have 3 lines vwap and ema 1 and 2 lines and u have made an entry and the last line before the entry is vwap then if any candle closes below vwap can be considered as stoploss like wise in any lines
The MERCURY indicator is a comprehensive trading tool designed to enhance traders' ability to identify trends, breakouts, and reversals effectively. Created by Dr. Abhiram Sivprasad, this indicator integrates several technical elements, including Central Pivot Range (CPR), EMA crossovers, VWAP levels, and a table-based EMA dashboard, to offer a holistic trading view.
Core Components and Functionality:
Central Pivot Range (CPR):
The CPR in MERCURY provides a central pivot level along with Below Central (BC) and Top Central (TC) pivots. These levels act as potential support and resistance, useful for identifying reversal points and zones where price may consolidate.
Exponential Moving Averages (EMAs):
MERCURY includes up to nine EMAs, with a customizable EMA crossover alert system. This feature enables traders to see shifts in trend direction, especially when shorter EMAs cross longer ones.
VWAP (Volume-Weighted Average Price):
VWAP is incorporated as a dynamic support/resistance level and, combined with EMA crossovers, helps refine entry and exit points for higher probability trades.
Breakout and Breakdown Alerts:
MERCURY monitors conditions for upside and downside breakouts. For an upside breakout, all EMAs turn green and a candle closes above VWAP, EMA1, and EMA2. Similarly, all EMAs turning red, combined with a close below VWAP and EMA1/EMA2, signals a downside breakdown. Continuous alerts are available until the trend shifts.
Real-Time EMA Dashboard:
A table displays each EMA’s relative position (Above or Below), helping traders quickly gauge trend direction. Colors in the table adjust to long/short conditions based on EMA alignment.
Usage Recommendations:
Trend Confirmation:
Use the CPR, EMA alignments, and VWAP to confirm uptrends and downtrends. The table highlights trends, making it easy to spot long or short setups at a glance.
Breakout and Breakdown Alerts:
The alert system is customizable for continuous notifications on critical price levels. When all EMAs align in one direction (green for long, red for short) and the close is above or below VWAP and key EMAs, the indicator confirms a breakout/breakdown.
Adaptable for Different Styles:
Day Trading: Traders can set shorter EMAs for quick insights.
Swing Trading: Longer EMAs combined with CPR offer insights into sustained trends.
Recommended Settings:
Timeframes: MERCURY is suitable for timeframes as low as 5 minutes for intraday traders, up to daily charts for trend analysis.
Symbols: Works across forex, stocks, and crypto. Adjust EMA lengths for asset volatility.
Example Strategy:
Long Entry: When the price crosses above CPR and closes above both EMA1 and EMA2.
Short Entry: When the price falls below CPR with a close below both EMA1 and EMA2.
Periodic Linear Regressions [LuxAlgo]The Periodic Linear Regressions (PLR) indicator calculates linear regressions periodically (similar to the VWAP indicator) based on a user-set period (anchor).
This allows for estimating underlying trends in the price, as well as providing potential supports/resistances.
🔶 USAGE
The Periodic Linear Regressions indicator calculates a linear regression over a user-selected interval determined from the selected "Anchor Period".
The PLR can be visualized as a regular linear regression (Static), with a fit readjusting for new data points until the end of the selected period, or as a moving average (Rolling), with new values obtained from the last point of a linear regression fitted over the calculation interval. While the static method line is prone to repainting, it has value since it can further emphasize the linearity of an underlying trend, as well as suggest future trend directions by extrapolating the fit.
Extremities are included in the indicator, these are obtained from the root mean squared error (RMSE) between the price and calculated linear regression. The Multiple setting allows the users to control how far each extremity is from the other.
Periodic Linear Regressions can be helpful in finding support/resistance areas or even opportunities when ranging in a channel.
The anchor - where a new period starts - can be shown (in this case in the top right corner).
The shown bands can be visualized by enabling Show Extremities in settings ( Rolling or Static method).
The script includes a background gradient color option for the bands, which only applies when using the Rolling method.
The indicator colors can be suggestive of the detected trend and are determined as follows:
Method Rolling: a gradient color between red and green indicates the trend; more green if the output is rising, suggesting an uptrend, and more red if it is decreasing, suggesting a downtrend.
Method Static: green if the slope of the line is positive, suggesting an uptrend, red if negative, suggesting a downtrend.
🔶 DETAILS
🔹 Anchor Type
When the Anchor Type is set to Periodic , the indicator will be reset when the "Anchor Period" changes, after which calculations will start again.
An anchored rolling line set at First Bar won't reset at a new session; it will continue calculating the linear regression from the first bar to the last; in other words, every bar is included in the calculation. This can be useful to detect potential long-term tops/bottoms.
Note that a linear regression needs at least two values for its calculation, which explains why you won't see a static line at the first bar of the session. The rolling linear regression will only show from the 3rd bar of the session since it also needs a previous value.
🔹 Rolling/Static
When Anchor Type is set at Periodic , a linear regression is calculated between the first bar of the chosen session and the current bar, aiming to find the line that best fits the dataset.
The example above shows the lines drawn during the session. The offered script, though, shows the last calculated point connected to the previous point when the Rolling method is chosen, while the Static method shows the latest line.
Note that linear regression needs at least two values, which explains why you won't see a static line at the first bar of the session. The rolling line will only show from the 3rd bar of the session since it also needs a previous value.
🔶 SETTINGS
Method: Indicator method used, with options: "Static" (straight line) / "Rolling" (rolling linear regression).
Anchor Type: "Periodic / First Bar" (the latter works only when "Method" is set to "Rolling").
Anchor Period: Only applicable when "Anchor Type" is set at "Periodic".
Source: open, high, low, close, ...
Multiple: Alters the width of the bands when "Show Extremities" is enabled.
Show Extremities: Display one upper and one lower extremity.
🔹 Color Settings
Mono Color: color when "Bicolor" is disabled
Bicolor: Toggle on/off + Colors
Gradient: Background color when "Show extremities" is enabled + level of gradient
🔹 Dashboard
Show Dashboard
Location of dashboard
Text size
Market Structure CHoCH/BOS (Fractal) [LuxAlgo]The Market Structure CHoCH/BOS (Fractal) indicator is an experimental take on classical market structure, whereas fractal patterns are used for their construction instead of swing points.
Compared to utilizing swing points for highlighting market structure like our Smart Money Concepts indicator , fractal-based market structure can appear as more adaptive, however, it can also be more restrictive when it comes to returning swing points which can cause the indicator to miss reversals in some cases.
If enabled from within the settings, users can see support and resistance levels returned from the detected market structure with breakouts highlighted on the chart. Alongside this feature, an additional dashboard showing the structure to fractal structure percentage is also provided.
🔶 SETTINGS
Length: Length of the fractal patterns to detect.
🔹 Style
Bullish Structures: Show bullish structures.
Bearish Structures: Show bullish structures.
Support: Show support levels.
Resistance: Show resistance levels.
🔹 Dashboard
Show Dashboard: Show structure to fractal percentage dashboard on the chart.
Location: Location of the dashboard on the chart.
Size: Dashboard size.
🔶 USAGE
Market structure is commonly used to determine trend direction by using price positions relative to prior swing points. Using fractal patterns to determine market structure can allow users to obtain shorter, more frequent structure labels.
Market structure is commonly classified as follows:
Change of Character (CHoCH), also referred to as Market Structure Shift (MSS)
Break of Structure (BOS), also referred to as Market Structure Break (MSB)
Change of Characters indicate a shift in the market trend, confirming trend reversals. Break of Structures on the other hand occur once a trend is already determined, confirming new higher highs/lower lows.
Using higher length values allow users to detect longer-term fractals, thus highlighting longer-term market structures. The image above detects fractal patterns made of 7 candles, even if the increment is only of 2 bars this significantly reduces the amount of detected market structure labels.
The result obtained by utilizing fractals and higher settings can be a more dynamic view of market structure, however, as seen in the image above this can introduce very significant delay compared to utilizing pure swing points.
🔹 Support/Resistance
The indicator also returns support/resistance levels constructed from the market structure, these levels are obtained similarly to order blocks, finding the minimum on the interval of a bullish market structure and the maximum of a bearish market structure.
Price reaching a support/resistance level can be expected to bounce from it. Once a level is broken, the support/resistance level will no longer extend, and a circle will be displayed highlighting the break.
While utilizing this script for fractal-based market structure, these levels can be useful to ensure all swing points are still considered by the user with the possibility of the indicator missing reversals due to its calculation not being based on swing points themselves.
🔹 Dashboard
The dashboard reports the structure to fractal percentage, that is the amount of bullish/bearish market structures relative to the total amount of detected bullish/bearish fractal patterns.
This allows us to see how often a detected fractal pattern is used to display a market structure.
🔶 DETAILS
🔹 Fractals
In the context of technical analysis, Fractals refer to specific patterns that exhibit self-similarity at different scales or timeframes.
The most commonly known fractal pattern consists of a consecutive sequence of candles (more commonly 5), with the central candle being the lowest (in case of a bullish fractal) or highest (in case of a bearish fractal).
A bullish fractal has candles on the right side of the central candle with increasing lows, while candles on the left side have decreasing lows.
A bearish fractal has candles on the right side of the central candle with decreasing highs, while candles on the left side have increasing highs.
🔶 RELATED SCRIPTS
🔹 Smart Money Concepts
🔹 Market Structure Trailing Stop
🔹 ICT Concepts
Trading ChannelTrading Channel aims to be a canvas on which to develop any strategy that the user feels comfortable with.
The greatest utility of the script lies in the fact that it plots a channel over the price action, as a support and resistance pivot, within which the price action develops.
It is a script of maximum simplicity in concept and development, but at the same time presents robust support to the price action and a quick visual aid complementary to any indicators that the user works with, feels comfortable with, and uses as a basis for their strategies.
The script includes the following features (most of them disabled by default, available for potential use without the need to add additional indicators):
Fast SMA
Medium SMA
Slow SMA (disabled)
Fast EMA (disabled)
Medium EMA (disabled)
Slow EMA (disabled)
Pivot
Pivot SMA
P Multiplier
Set of resistance and support pivots according to the studies of John L. Person (R3, R2, R1, S1, S2, S3 and midpoints) (disabled by default)
Channel for the current time period in use
Channels for extended time periods (disabled by default)
Various trend, momentum, and overbought/oversold indicating labels (note that the calculations for their representation are based on SMA's even though EMA's are visualized).
SMA's/EMA's
Both are available as both are used as basic indicators for different types of strategies. The default selection of SMA's in this case is based on the fact that the script development is largely based on the studies shared by John L. Person in the area of pivots and by Bill Williams in the area of fractals. Note also that for that same reason the various trend, momentum, and overbought/oversold indicating labels are calculated based on them.
Set of resistance and support pivots
They are included as a consultation tool especially for the higher time periods. They can be used to mark the most interesting supports/resistances and not lose sight of them while operating in lower time periods. Marking monthly, weekly, and daily pivots can be very useful. Additionally, marking S1 and R2 for bullish trends, S1 and R1 for ranges, and S2 and R1 for bearish trends can provide an even more precise framework to work on.
P Multiplier
It is set by default at 4, and is the basis for being able to consider during the use of a specific time frame, the price action with respect to higher time frames. It is the multiplier used for the generation of channels for extended time periods.
Channel for the current time period in use
It is a channel formed by the maximum and minimum closing of the last 21 periods. This value is modifiable and its adjustment depends on the asset under study. 24/7 markets show good results with this adjustment (in the case of BTC really good).
This channel represents a pivot in the form of a yellow middle line, with its support and resistance extremes on the upper green and lower red lines. The same green and red lines, referenced this time to the maximum, are added and serve as possible stop-loss marks.
Channels for extended time periods
Enabling the maximum and minimum channels for extended periods can provide a better idea of the price situation (it is recommended to disable the channel in use and enable the upper one for consultation, it provides a better vision).
Identifying labels:
Following a summary explanation for possible long entries, the same but opposite should be considered for possible short entries:
Small green arrow under candle: indicates possible upward trend (pivot above pivot SMA)
Large green arrow under candle: indicates upward trend (pivot above pivot SMA and above fast SMA)
Green triangle over candle: indicates channel breakout, possible upward momentum (represented as a fractal as its concept is the same)
Green/red arrows at the bottom of the chart: intended to confirm the validity of a signal (should doubt green indications with red lower arrow and vice versa)
Green/red dots at the bottom of the chart: red represents areas of strong resistance and green signals of strong support (with red dots, proceed with caution despite green signals, and vice versa)
Comments
It is emphasized that the basic and most useful functionality of this script is to provide a reliable base on which to develop any strategy, as a framework for working.
If the identifying labels are used, it should be taken into account that the earliest will always be the most reliable and valuable, but their confirmation will always depend on the user's strategy.
Its use in conjunction with the "Pivot Position for Trading Channel" indicator can serve as a base for the development of different strategies, by providing indication of the relative position of the price within the channel.
This script is just a consultation tool with didactic goals, it should not be used as an investment recommendation and the information provided should not be relied upon as such.
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Trading Channel pretende ser un lienzo sobre el que desarrollar cualquiera que sea la estrategia con la que el usuario se sienta más cómodo.
La mayor utilidad del script radica en que se traza sobre la acción del precio un canal, a modo de pivotes de soporte y resistencia, dentro del cual se desarrolla la acción del precio.
Se trata de un script de máxima sencillez en concepto y desarrollo, pero que a la vez presenta un soporte robusto a la acción del precio y una ayuda rápida visual complementaria a cualquieras que sean los indicadores con los que el usuario trabaje, se sienta más cómodo y utilice como base de sus estrategias.
El script incluye las siguientes funcionalidades (la mayoría desactivadas por defecto, disponibles para su potencial uso sin necesidad de añadir indicadores adicionales):
- SMA rápida
- SMA media
- SMA lenta (desactivada)
- EMA rápida (desactivada)
- EMA media (desactivada)
- EMA lenta (desactivada)
- Pivote
- SMA de pivote
- Multiplicador de P
- Conjunto de pivotes resistencia y soporte de acuerdo a los estudios de John L. Person (R3, R2, R1, S1, S2, S3 y puntos medios) (desactivados por defecto)
- Canal para el periodo temporal en uso
- Canales para periodos temporales extendidos (desactivados por defecto)
- Diversas etiquetas indicativas de cambios de tendencia, de impulso y de sobrecompra y sobreventa (nótese que los cálculos para su representación están basados en SMA's aunque se visualicen EMA's).
SMA's/EMA's
Ambas disponibles pues tanto unas como otras son utilizadas como indicadores básicos para diferentes tipos de estrategias. La selección de SMA's por defecto en este caso se basa en que las bases para desarrollo del script son en gran medida los estudios compartidos por John L. Person en el área de pivotes y de Bill Williams en el área de los fractales. Nótese también que por esa misma razón las diversas etiquetas indicativas de cambios de tendencia, impulso y sobrecompra/sobreventa se calculan en base a ellas.
Conjunto de pivotes resistencia y soporte
Se incluyen como herramienta de consulta sobre todo para los periodos temporales más altos. Pueden utilizarse para marcar los soportes/resistencias de más interés y no perderlos de vista mientras se opera en periodos de tiempo más bajos. De acuerdo a los estudios de John L. Person, marcarse los pivotes mensuales, semanales y diarios puede resultar de mucha utilidad. Adicionalmente, marcar S1 y R2 para tendencias alcistas, S1 y R1 para rangos, y S2 y R1 para tendencias bajistas puede proporcionar un marco aún más preciso sobre el que trabajar.
Multiplicador de p
Está fijado por defecto en 4, y es la base para poder considerar durante el uso de una franja temporal concreta, la acción del precio respecto a franjas temporales superiores. Es el multiplicador utilizado para la generación de los canales para periodos temporales extendidos.
Canal para el periodo temporal en uso
Se trata de un canal conformado por los cierres máximos y mínimos de los últimos 21 periodos. Este valor es modificable y su ajuste depende del activo en estudio. Mercados 24/7 muestran buenos resultados con este ajuste (en el caso de BTC realmente buenos).
Este canal representa en cierta manera un pivote en forma de línea intermedia amarilla, con sus extremos de soporte y resistencia en las líneas verdes superior y roja inferior. Se añaden las mismas líneas verdes y rojas, referenciadas esta vez a los máximos, que sirven como posibles marcas de stop-loss.
Canales para periodos temporales extendidos
Habilitar los máximos y mínimos de canales de periodos extendidos puede proporcionar una mejor idea de la situación del precio (se recomienda deshabilitar el canal en uso y habilitar el superior para consulta, proporciona una mejor visión).
Etiquetas identificativas:
A continuación explicación resumida para posibles entradas en largo, lo mismo pero de modo opuesto debería considerarse para posibles entradas en corto:
Flecha verde pequeña bajo vela: indica inicio de tendencia en alza (pivote por encima de SMA de pivote y ambos por encima de SMA rápida)
Flecha verde grande bajo vela: indica tendencia en alza (pivote por encima de SMA de pivote y ambos por encima de SMA rápida y media)
Triángulo verde sobre vela: indica rotura de canal, posible impulso al alza (representado a modo de fractal pues su concepto es el mismo)
Flechas verdes/rojas a pie de gráfico: pretenden confirmar la validez de una señal (debería dudarse de las indicaciones verdes con flecha inferior roja y viceversa)
Puntos verdes/rojos a pie de gráfico: los rojos representan áreas de fuerte resistencia y los verdes de fuerte soporte (con puntos rojos, proceder con cautela pese a señales verdes, y viceversa)
Comentarios
Se insiste en que la funcionalidad básica y de mayor utilidad de este script es proporcionar una base confiable sobre la que desarrollar cualquier estrategia, a modo de marco de trabajo.
Si se hace uso de las etiquetas identificativas, debe tenerse en cuenta que las más prematuras siempre serán las más confiables y valiosas, pero que su confirmación siempre dependerá de la estrategia por parte del usuario.
Su uso en conjunción al indicador "Pivot Position for Trading Channel" puede servir de base para el desarrollo de diferentes estrategias, al proporcionar indicación de la posición relativa del precio dentro del canal.
Este script es solo una herramienta de consulta con objetivos didácticos, no debe ser utilizado como recomendación de inversión y no se debe confiar en ella como tal.
PA Swings [TTA]Hello traders!
This script helps identify swing high levels of resistance and swing low levels of support via price action.
The indicator is designed to help identify support and resistance by measuring retracements. When the retracement has reached the threshold, the indicator identifies the high or low with a horizontal, solid line.
This line will continue until it is violated. Once it is violated it will adjust to a dashed line and continue until it is violated again (retested).
Therefore, a solid line resembles an unviolated swing level; a dashed line resembles a violated swing level that has yet to be retested.
Ideally, this script will filter some movements by identifying impulses in the market. Knowing that price is in a trending move rather than bouncing around in a range can help traders in their analysis. In range bound conditions the indicator will show small impulses, sometimes trapped by a support and/or resistance line. In trending markets there will be separation between the support and resistance lines.
Retests are also identified by the indicator.
Retests of swing highs and lows may induce precise, repeatable price moves - something a trader might find advantageous. A log is included to help identify potential price levels based on historical actions when an impulse or a retest occurs.
Consequently, this may help traders identify take-profit targets and avoid stop losses that are too close to the entry point.
The indicator has a color identity panel to help you get familiar with the colored lines, line types, and what they mean. The color panel is concealable. Additional customization options are available, such as toggling the chart labels. These labels distinguish impulses up and down, retests, and the distance price has traveled since breaking or creating a support or resistance level.
This can be toggled off. A High-Volume Swings only option is available for those that wish to filter out low volume movements (such as extended market hours).
You also have the option of hiding far away lines and can define what is “far away” for them % wise. It is defaulted to 15% which may need to be adjusted on lower timeframes.
Inactive lines can be shown or they can be removed in the settings as well. While this indicator can find some great levels of support or resistance it is important to remember that, should you find this script helpful, it is a tool in your toolbox!! (:
Hope you enjoy and thank you for checking this out!
Volume Adaptive Bollinger Bands (MZ VABB)This indicator is a functional enhancement to John Bollinger's Bollinger Bands. I've used Volume to adapt dynamic length which is used in basis (middle line) of Bollinger Bands and Simple Moving Average is replaced with Adaptive Ehlers Deviation Scaled Moving Average ( AEDSMA ).
BOLLINGER BANDS BASIC USAGE AND LIMITATIONS
Bollinger bands are popular among traders because of their simple way to detect volatility in market and redefine support and resistance accordingly. These are some basic usages of original Bollinger Bands:
Most commonly Bollinger Band works on 20 period Simple Moving Average as Basis / Middle Line and standard deviation of 2 for volatility detection.
Upper and lower bands can act as support and resistance which accordingly update with standard deviation of same period as of Simple Moving Average.
As upper and lower bands act as volatility measure which benefits in Squeeze detection and breakout trading.
Among all the usages there are some limitations as follows:
Original Bollinger Bands use 20 period Simple Moving Average as Basis which itself restricted to some number of data pints and if market moves in one direction or simply goes sideways for long time; candles can stay on either bands for long time. This gives benefit for staying in directional trade but will completely nullify the use of both bands as support and resistance.
Above point simply be explained as markets can stay overbought / oversold for long time and one way to make Bollinger Bands more useful is to simply use higher periods in SMA but as we know with higher periods SMA becomes more laggy and less adaptive.
Most traders use BBs alongside some other Volume Oscillator for example "On Balance Volume" but that does solve BBs limitations issue that it should be more adaptive to detect volatility in market.
VOLUME ADAPTIVE BOLLINGER BAND WORKING PRINCIPLE
Best way to make original Bollinger band more adaptive was to just use dynamic length instead on constant 20 period. This dynamic length had to be based on some other powerful parameter which can't be volatility as BB itself is a volatility indicator and adapting its length based volatility would have been superimposing volatility on Bollinger bands giving unrealistic results.
For adaptive length, I tried using Volume and for this purpose I used my Relative Volume Strength Index " RVSI " indicator. RVSI is the best way to detect if Volume is going for a breakout or not and based on that indication length of Bollinger Band Basis Moving Average changes.
RVSI breaking above provided value would indicate Volume breakout and hence dynamic length would accordingly make Bollinger band basis moving average more over fitted and similarly standard deviation of achieved dynamic length would give better bands for support and resistance. Similar case would happen if Volume goes down and dynamic length becomes more underfit.
According to my back testing studies I found that Simple Moving Average wasn't the best choice for dynamic length usage in Bollinger Band Basis. So, I used Adaptive Ehlers Deviation Scaled Moving Average ( AEDSMA ) which is more adaptive and already modified to adapt with RVSI.
SLOPE USAGE FOR TREND STRENGTH DETCTION
Volume Adaptive Bollinger Bands are more reactive to market trends so, I used slope for trend strength detection.
If slope of Volume Adaptive Bollinger Band Basis (i.e. AEDSMA ), Upper and Lower Bands is supporting a trend at same time then script will provide signal in that direction. That signal can also use Volume as confirmation if Bollinger Bands trend direction is supported by Volume or not.
DYNAMIC COLORS AND TREND CORRELATION
I’ve used dynamic coloring in Basis ( AEDSMA ) to identify trends with more detail which are as follows:
Lime Color: Slope supported Strong Uptrend also supported by Volume and Volatility or whatever you’ve chosen from both of them.
Fuchsia Color: Weak uptrend only supported by Slope or whatever you’ve selected.
Red Color: Slope supported Strong Downtrend also supported by Volume and Volatility or whatever you’ve chosen from both of them.
Grey Color: Weak Downtrend only supported by Slope or whatever you’ve selected.
Yellow Color: Possible reversal indication by Slope if enabled. Market is either sideways, consolidating or showing choppiness during that period.
SIGNALS
Green Circle: Market good for long with support of Volume and Volatility or whatever you’ve chosen from both of them.
Red Circle: Market good to short with support from Volume and Volatility or whatever you’ve chosen from both of them.
Flag: Market either touched upper or lower band and can act as good TP and warning for reversal.
FIBONACCI BANDS
I’ve included Fibonacci multiple bands which would act as good support/resistance zones. For example, 0.618 Fib level act as good local support and resistance in both upper and lower zones. Fibonacci values can be modified but should be lower than 1.
DEFAULT SETTINGS
I’ve set default Minimum length to 50 and Maximum length to 100 which I’ve found works best for almost all timeframes but you can change this delta to adapt your timeframe accordingly with more precision.
Dynamic length adoption is enabled based on Volume only but volatility can be selected which is already explained above.
Trend signals are enabled based on Slope and Volume but Volatility can be enabled for more precise confirmations.
In “ RVSI ” settings "Klinger Volume Oscillator" is set to default but others work good too especially Volume Zone Oscillator. For more details about Volume Breakout you can check “MZ RVSI Indicator".
ATR breakout is set to be positive if period 14 exceeds period 46 but can be changed if more adaption with volatility is required.
EDSMA super smoother filter length is set to 20 which can be increased to 50 or more for better smoothing but this will also change slope results accordingly.
EDSMA super smoother filter poles are set to 2 because found better results with 2 instead of 3.
FURTHER ENHANCEMENTS
So far, I've achieved better results with "Klinger Volume Oscillator" in RVSI but TFS Volume Oscillator and On Balance Volume can be used which would change dynamic length differently. It doesn't mean that results would be wrong with some oscillator and precise with others but every oscillator works in its specific way for and RVSI just detect strength of Volume based on provided oscillator.
FIBS S/R IndicatorHello,
I've decided to publish a new script. The previous version of this script was removed by admins for breaking community rules.
So I present to you the Fibonacci Support / Resistance.
1. How does it work
Ratio plots
I first take the input of pivot look back and search for pivots high and low.
And then it takes a second look back to search highest high and lowest low to establish the top bottom range.
Then using the top and bottom I plot ratios provided as input. Defaults to most relevant 5 ratios I've found (Fibonacci):
Ratio 0 = 0 - can't be changed
Ratio 1 = 0.5
Ratio 2 = 0.618
Ratio 3 = 1
Ratio 4 = 1.618
Ratio 5 = 2.618
Any changes done to these ratios should be in order, otherwise conditions could get messed up. So R1 needs to the lowest and R5 the highest.
Also the same ratios are used in reverse as negative ratios.
There is a option to plot all ratios but gets really confusing for me but maybe for you it works. By default there are certain conditions set so that as we go up new resistance ratio get displayed and as we go down we see new resistance plots.
Trendlines
I've also added some automatic trendline plots with breakout warning labels based on the pivots high and low. Start and end for trendlines can be changed via inputs.
Labels can be deactivated via input. On a older version the trendlines and labels where not removed from the chart but I felt like there was to much information.
Overcooked/Undercooked
I've also added some fills and background colors that indicate if the price action is over R5 or under Negative R5 ratios. This usually indicates some "overcooking" or "undecooking".
I've notices that after "crossunder"/"crossover" top bottom ratios it goes in consolidation or it dumps. So then I plot a bgcolor to signal that.
2. How to use it
Using plot lines we can determine where we have support and resistance. I found that the best way to use the default ratios values is on the 1H chart. Very good for trading on crypto because of current situation in the market where there is a lot of new people entering the space and volatility and sentiment make swings respect the Fibonacci ratios.
3. Examples
For instance lets look at BINANCE:BTCUSDT .
On the left we see that the price action between 20 and 21 February was "overcooked". So after we got the signal that we "crossunder" the R5 the signal was triggered and we got a small red candle followed by a small dip and after that we got a small bounce and a dump.
If we also look at MF-RSI we can also see we got multiple bear divs.
Lets entertain the idea that we went short at ~57.1k as soon as we get signaled and it starts dumping.
Where does it stop ?
We can see it went all the way down to Negative R5 ratio. Normally that should signal "undercooking" but this was not triggered as it did not close under it (signaled in green).
We can also see that previous support now becomes resistance (signaled in red).
If we take a look at BINANCE:ETHUSDT , we do see that the "undercooking" was triggered here.
I will be publishing a more detailed Idea with examples of using this on the BINANCE:BTCUSDT chart in combination with Volume and other technical analysis.
Use with caution, this is not 100% signal indicator as the markets do what they want. But by using this in combination with other indicators like MF-RSI, EMAs and regular patterns we can get some targets for Support/Resistance.
I'm trying to create a strategy based on this indicator but I'm not getting very good results. Best results were on the 15 min chart with gross profits around ~50%.
Please try to play around with the inputs and let me know if you find something interesting, maybe I can incorporate new features in the indicator.
You can find the MF-RSI indicator here
Price Action - Support & Resistance by DGTSᴜᴘᴘᴏʀᴛ ᴀɴᴅ Rᴇꜱɪꜱᴛᴀɴᴄᴇ , is undoubtedly one of the key concepts of technical analysis
█ Sᴜᴘᴘᴏʀᴛ ᴀɴᴅ Rᴇꜱɪꜱᴛᴀɴᴄᴇ Dᴇꜰɪɴɪᴛɪᴏɴ
Support and Resistance terms are used by traders to refer to price levels on charts that tend to act as barriers, preventing the price of an financial instrument from getting pushed in a certain direction.
A support level is a price level where buyers are more aggressive than sellers. This means that the price is more likely to "bounce" off this level rather than break through it. However, once the price has breached this level it is likely to continue falling until meeting another support level.
A resistance level is the opposite of a support level. It is where the price tends to find resistance as it rises. Again, this means that the price is more likely to "bounce" off this level rather than break through it. However, once the price has breached this level it is likely to continue rising until meeting another resistance level.
A previous support level will sometimes become a resistance level when the price attempts to move back up, and conversely, a resistance level will become a support level as the price temporarily falls back.
█ Iᴅᴇɴᴛɪꜰʏɪɴɢ Sᴜᴘᴘᴏʀᴛ ᴀɴᴅ Rᴇꜱɪꜱᴛᴀɴᴄᴇ
Support and resistance can come in various forms, and the concept is more difficult to master than it first appears. Identification of key support and resistance levels is an essential ingredient to successful technical analysis.
If the price stalls and reverses in the same price area on minimum of two different occasions, then a horizontal line is drawn to show that the market is struggling to move past that area. Those areas are static barriers, one of the most popular forms of support/resistance and are highlighted with horizontal lines.
Repeated test , the more often a support/resistance level is "tested" over an extended period of time (touched and bounced off by price), the more significance is given to that specific level
High volume , the more buying and selling that has occurred at a particular price level, the stronger the support or resistance level is likely to be
Market psychology , plays a major role as traders and investors remember the past and react to changing conditions to anticipate future market movement.
Psychological levels , is a price level that significantly affects the price of an underlying financial instrument. Typically, near round numbers often serve as support and resistance
The following support and resistance related topics are beyond the scope of this study, so they will be mentioned roughly only as a reference for support and resistance concept
Trendlines , Support and resistance levels in trends are dynamic. Throughout an uptrend, levels of support tend to look like a trendline, usually clustering around higher lows. As the price rises, the price where buyers consider the stock to be “too cheap” also changes, which creates new support levels on the way up. The same is also true for resistance levels. In an uptrend, a stock is continuously breaking through perceived resistance levels and making new highs
Moving Averages , is a constantly changing line that smooths out past price data while also allowing the trader to identify support and resistance. In the example Notice how the price of the asset finds support at the moving average when the trend is up, and how it acts as resistance when the trend is down
The Fibonacci Retracement/Extension tool , is a favorite among many short-term traders because it clearly identifies levels of potential support and resistance
Pivot Point Calculations , is another common technical analysis technique, where pivot point is calculated based on the high, low, and closing prices of previous trading session/day and support & resistance levels are projected based on the pivot point, different calculation techniques are available, as presented in this example of an pivot point indicator : PVTvX by DGT
█ Tʀᴀᴅɪɴɢ Bᴀꜱᴇᴅ ᴏɴ Sᴜᴘᴘᴏʀᴛ ᴀɴᴅ Rᴇꜱɪꜱᴛᴀɴᴄᴇ
Once an area or "zone" of support or resistance has been identified, those price levels can serve as potential entry or exit points because, as a price reaches a point of support or resistance, it will do one of two things—bounce back away from the support or resistance level (trading ranges), or violate the price level and continue in its direction (trading breakouts) —until it hits the next support or resistance level
The basic trading method for using support and resistance is to buy near support in uptrends or the parts of ranges or chart patterns where prices are moving up and to sell/sell short near resistance in downtrends or the parts of ranges and chart patterns where prices are moving down. Buying near support or selling near resistance can pay off, but there is no assurance that the support or resistance will hold. Therefore, consider waiting for some confirmation that the market is still respecting that area
Trading breakouts, a breakout is a potential trading opportunity that occurs when an asset's price moves above a resistance level or moves below a support level on increasing volume. The first step in trading breakouts is to identify current price trend patterns along with support and resistance levels in order to plan possible entry and exit points. Once the asset trades beyond the price barrier, volatility tends to increase and prices usually trend in the breakout's direction. Breakouts are such an important trading strategy since these setups are the starting point for future volatility increases, large price swings and, in many circumstances, major price trends. When trading breakouts, it is important to consider the underlying asset's support and resistance levels. The more times an asset price has touched these areas, the more valid these levels are and the more important they become. At the same time, the longer these support and resistance levels have been in play, the better the outcome when the asset price finally breaks out. Asset prices will often move slightly further than we expect them to. This doesn't happen all the time, but when it does it is called a false breakout. Therefore it is important to consider waiting for some confirmation while trading breakouts. It’s also popular for traders to sell 50% of their positions at the resistance level, and hold the rest in anticipation of a breakout above resistance
█ Pʀɪᴄᴇ Aᴄᴛɪᴏɴ - Sᴜᴘᴘᴏʀᴛ & Rᴇꜱɪꜱᴛᴀɴᴄᴇ ʙʏ DGT Sᴛᴜᴅʏ
This experimental study attempts to identify the support and resistance levels. Assumes a simple logic to discover moments where the price is rising or falling consecutively for minimum 3 bars with the condition volume increases on each bar and the last bar’s volume should be bigger than the long term volume moving average. A line will be drawn at the end of the move (highest or lowest, depending on the move direction), the line will be drawn at minimum on the 3rd bar and if condition holds for other consecutive bars the line will switch to 4th, 5th etc bar.
Lines will not be deleted so the historical ones will remain and will emphasis the levels significance when they overlap in feature. Strong levels are more likely to hold and cause the price to move in the other direction, whereas the minor levels may only cause the price to pause and keep moving in the same direction. Determining future levels of support and resistance can drastically improve the returns of a short-term investing strategy
Bar colors will be painted based on the volume of the specific bar to its long term volume moving average. This will help identifying the support and resistance levels significance and emphasis the sings of breakouts
Finally, Volume spikes will be marked on top of the price chart. A high volume usually indicates more interest in the security and the presence of institutional traders. However, a rapidly rising price in an uptrend accompanied by a huge volume may be a sign of exhaustion. Traders usually look for breaks of support and resistance to enter positions. When security break critical levels without volume , you should consider the breakout suspect and prime for a reversal off the highs/lows. Volume spikes are often the result of news-driven events. Volume spike will often lead to sharp reversals since the moves are unsustainable due to the imbalance of supply and demand
A good example with many support and resistance concepts observed on a stock chart and detected by the study
Settings:
Length of volume moving average, where volume moving average is used to detect support and resistance levels, is used as reference to compare with threshold values for volume spikes and colors of the bars
Hint, to get more historical lines scrolling chart to left will enable visualization of them. Please note they may appear to much all 500 line limit is used 😉
Special thanks to @HEMANT Telegram user, for his observations and suggestions
Disclaimer:
Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
The script is for informational and educational purposes only. Use of the script does not constitute professional and/or financial advice. You alone have the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Ruckard TradingLatinoThis strategy tries to mimic TradingLatino strategy.
The current implementation is beta.
Si hablas castellano o espanyol por favor consulta MENSAJE EN CASTELLANO más abajo.
It's aimed at BTCUSDT pair and 4h timeframe.
STRATEGY DEFAULT SETTINGS EXPLANATION
max_bars_back=5000 : This is a random number of bars so that the strategy test lasts for one or two years
calc_on_order_fills=false : To wait for the 4h closing is too much. Try to check if it's worth entering a position after closing one. I finally decided not to recheck if it's worth entering after an order is closed. So it is false.
calc_on_every_tick=false
pyramiding=0 : We only want one entry allowed in the same direction. And we don't want the order to scale by error.
initial_capital=1000 : These are 1000 USDT. By using 1% maximum loss per trade and 7% as a default stop loss by using 1000 USDT at 12000 USDT per BTC price you would entry with around 142 USDT which are converted into: 0.010 BTC . The maximum number of decimal for contracts on this BTCUSDT market is 3 decimals. E.g. the minimum might be: 0.001 BTC . So, this minimal 1000 amount ensures us not to entry with less than 0.001 entries which might have happened when using 100 USDT as an initial capital.
slippage=1 : Binance BTCUSDT mintick is: 0.01. Binance slippage: 0.1 % (Let's assume). TV has an integer slippage. It does not have a percentage based slippage. If we assume a 1000 initial capital, the recommended equity is 142 which at 11996 USDT per BTC price means: 0.011 BTC. The 0.1% slippage of: 0.011 BTC would be: 0.000011 . This is way smaller than the mintick. So our slippage is going to be 1. E.g. 1 (slippage) * 0.01 (mintick)
commission_type=strategy.commission.percent and commission_value=0.1 : According to: binance . com / en / fee / schedule in VIP 0 level both maker and taker fees are: 0.1 %.
BACKGROUND
Jaime Merino is a well known Youtuber focused on crypto trading
His channel TradingLatino
features monday to friday videos where he explains his strategy.
JAIME MERINO STANCE ON BOTS
Jaime Merino stance on bots (taken from memory out of a 2020 June video from him):
'~
You know. They can program you a bot and it might work.
But, there are some special situations that the bot would not be able to handle.
And, I, as a human, I would handle it. And the bot wouldn't do it.
~'
My long term target with this strategy script is add as many
special situations as I can to the script
so that it can match Jaime Merino behaviour even in non normal circumstances.
My alternate target is learn Pine script
and enjoy programming with it.
WARNING
This script might be bigger than other TradingView scripts.
However, please, do not be confused because the current status is beta.
This script has not been tested with real money.
This is NOT an official strategy from Jaime Merino.
This is NOT an official strategy from TradingLatino . net .
HOW IT WORKS
It basically uses ADX slope and LazyBear's Squeeze Momentum Indicator
to make its buy and sell decisions.
Fast paced EMA being bigger than slow paced EMA
(on higher timeframe) advices going long.
Fast paced EMA being smaller than slow paced EMA
(on higher timeframe) advices going short.
It finally add many substrats that TradingLatino uses.
SETTINGS
__ SETTINGS - Basics
____ SETTINGS - Basics - ADX
(ADX) Smoothing {14}
(ADX) DI Length {14}
(ADX) key level {23}
____ SETTINGS - Basics - LazyBear Squeeze Momentum
(SQZMOM) BB Length {20}
(SQZMOM) BB MultFactor {2.0}
(SQZMOM) KC Length {20}
(SQZMOM) KC MultFactor {1.5}
(SQZMOM) Use TrueRange (KC) {True}
____ SETTINGS - Basics - EMAs
(EMAS) EMA10 - Length {10}
(EMAS) EMA10 - Source {close}
(EMAS) EMA55 - Length {55}
(EMAS) EMA55 - Source {close}
____ SETTINGS - Volume Profile
Lowest and highest VPoC from last three days
is used to know if an entry has a support
VPVR of last 100 4h bars
is also taken into account
(VP) Use number of bars (not VP timeframe): Uses 'Number of bars {100}' setting instead of 'Volume Profile timeframe' setting for calculating session VPoC
(VP) Show tick difference from current price {False}: BETA . Might be useful for actions some day.
(VP) Number of bars {100}: If 'Use number of bars (not VP timeframe)' is turned on this setting is used to calculate session VPoC.
(VP) Volume Profile timeframe {1 day}: If 'Use number of bars (not VP timeframe)' is turned off this setting is used to calculate session VPoC.
(VP) Row width multiplier {0.6}: Adjust how the extra Volume Profile bars are shown in the chart.
(VP) Resistances prices number of decimal digits : Round Volume Profile bars label numbers so that they don't have so many decimals.
(VP) Number of bars for bottom VPOC {18}: 18 bars equals 3 days in suggested timeframe of 4 hours. It's used to calculate lowest session VPoC from previous three days. It's also used as a top VPOC for sells.
(VP) Ignore VPOC bottom advice on long {False}: If turned on it ignores bottom VPOC (or top VPOC on sells) when evaluating if a buy entry is worth it.
(VP) Number of bars for VPVR VPOC {100}: Number of bars to calculate the VPVR VPoC. We use 100 as Jaime once used. When the price bounces back to the EMA55 it might just bounce to this VPVR VPoC if its price it's lower than the EMA55 (Sells have inverse algorithm).
____ SETTINGS - ADX Slope
ADX Slope
help us to understand if ADX
has a positive slope, negative slope
or it is rather still.
(ADXSLOPE) ADX cut {23}: If ADX value is greater than this cut (23) then ADX has strength
(ADXSLOPE) ADX minimum steepness entry {45}: ADX slope needs to be 45 degrees to be considered as a positive one.
(ADXSLOPE) ADX minimum steepness exit {45}: ADX slope needs to be -45 degrees to be considered as a negative one.
(ADXSLOPE) ADX steepness periods {3}: In order to avoid false detection the slope is calculated along 3 periods.
____ SETTINGS - Next to EMA55
(NEXTEMA55) EMA10 to EMA55 bounce back percentage {80}: EMA10 might bounce back to EMA55 or maybe to 80% of its complete way to EMA55
(NEXTEMA55) Next to EMA55 percentage {15}: How much next to the EMA55 you need to be to consider it's going to bounce back upwards again.
____ SETTINGS - Stop Loss and Take Profit
You can set a default stop loss or a default take profit.
(STOPTAKE) Stop Loss % {7.0}
(STOPTAKE) Take Profit % {2.0}
____ SETTINGS - Trailing Take Profit
You can customize the default trailing take profit values
(TRAILING) Trailing Take Profit (%) {1.0}: Trailing take profit offset in percentage
(TRAILING) Trailing Take Profit Trigger (%) {2.0}: When 2.0% of benefit is reached then activate the trailing take profit.
____ SETTINGS - MAIN TURN ON/OFF OPTIONS
(EMAS) Ignore advice based on emas {false}.
(EMAS) Ignore advice based on emas (On closing long signal) {False}: Ignore advice based on emas but only when deciding to close a buy entry.
(SQZMOM) Ignore advice based on SQZMOM {false}: Ignores advice based on SQZMOM indicator.
(ADXSLOPE) Ignore advice based on ADX positive slope {false}
(ADXSLOPE) Ignore advice based on ADX cut (23) {true}
(STOPTAKE) Take Profit? {false}: Enables simple Take Profit.
(STOPTAKE) Stop Loss? {True}: Enables simple Stop Loss.
(TRAILING) Enable Trailing Take Profit (%) {True}: Enables Trailing Take Profit.
____ SETTINGS - Strategy mode
(STRAT) Type Strategy: 'Long and Short', 'Long Only' or 'Short Only'. Default: 'Long and Short'.
____ SETTINGS - Risk Management
(RISKM) Risk Management Type: 'Safe', 'Somewhat safe compound' or 'Unsafe compound'. ' Safe ': Calculations are always done with the initial capital (1000) in mind. The maximum losses per trade/day/week/month are taken into account. ' Somewhat safe compound ': Calculations are done with initial capital (1000) or a higher capital if it increases. The maximum losses per trade/day/week/month are taken into account. ' Unsafe compound ': In each order all the current capital is gambled and only the default stop loss per order is taken into account. That means that the maximum losses per trade/day/week/month are not taken into account. Default : 'Somewhat safe compound'.
(RISKM) Maximum loss per trade % {1.0}.
(RISKM) Maximum loss per day % {6.0}.
(RISKM) Maximum loss per week % {8.0}.
(RISKM) Maximum loss per month % {10.0}.
____ SETTINGS - Decimals
(DECIMAL) Maximum number of decimal for contracts {3}: How small (3 decimals means 0.001) an entry position might be in your exchange.
EXTRA 1 - PRICE IS IN RANGE indicator
(PRANGE) Print price is in range {False}: Enable a bottom label that indicates if the price is in range or not.
(PRANGE) Price range periods {5}: How many previous periods are used to calculate the medians
(PRANGE) Price range maximum desviation (%) {0.6} ( > 0 ): Maximum positive desviation for range detection
(PRANGE) Price range minimum desviation (%) {0.6} ( > 0 ): Mininum negative desviation for range detection
EXTRA 2 - SQUEEZE MOMENTUM Desviation indicator
(SQZDIVER) Show degrees {False}: Show degrees of each Squeeze Momentum Divergence lines to the x-axis.
(SQZDIVER) Show desviation labels {False}: Whether to show or not desviation labels for the Squeeze Momentum Divergences.
(SQZDIVER) Show desviation lines {False}: Whether to show or not desviation lines for the Squeeze Momentum Divergences.
EXTRA 3 - VOLUME PROFILE indicator
WARNING: This indicator works not on current bar but on previous bar. So in the worst case it might be VP from 4 hours ago. Don't worry, inside the strategy calculus the correct values are used. It's just that I cannot show the most recent one in the chart.
(VP) Print recent profile {False}: Show Volume Profile indicator
(VP) Avoid label price overlaps {False}: Avoid label prices to overlap on the chart.
EXTRA 4 - ZIGNALY SUPPORT
(ZIG) Zignaly Alert Type {Email}: 'Email', 'Webhook'. ' Email ': Prepare alert_message variable content to be compatible with zignaly expected email content format. ' Webhook ': Prepare alert_message variable content to be compatible with zignaly expected json content format.
EXTRA 5 - DEBUG
(DEBUG) Enable debug on order comments {False}: If set to true it prepares the order message to match the alert_message variable. It makes easier to debug what would have been sent by email or webhook on each of the times an order is triggered.
HOW TO USE THIS STRATEGY
BOT MODE: This is the default setting.
PROPER VOLUME PROFILE VIEWING: Click on this strategy settings. Properties tab. Make sure Recalculate 'each time the order was run' is turned off.
NEWBIE USER: (Check PROPER VOLUME PROFILE VIEWING above!) You might want to turn on the 'Print recent profile {False}' setting. Alternatively you can use my alternate realtime study: 'Resistances and supports based on simplified Volume Profile' but, be aware, it might consume one indicator.
ADVANCED USER 1: Turn on the 'Print price is in range {False}' setting and help us to debug this subindicator. Also help us to figure out how to include this value in the strategy.
ADVANCED USER 2: Turn on the all the (SQZDIVER) settings and help us to figure out how to include this value in the strategy.
ADVANCED USER 3: (Check PROPER VOLUME PROFILE VIEWING above!) Turn on the 'Print recent profile {False}' setting and report any problem with it.
JAIME MERINO: Just use the indicator as it comes by default. It should only show BUY signals, SELL signals and their associated closing signals. From time to time you might want to check 'ADVANCED USER 2' instructions to check that there's actually a divergence. Check also 'ADVANCED USER 1' instructions for your amusement.
EXTRA ADVICE
It's advised that you use this strategy in addition to these two other indicators:
* Squeeze Momentum Indicator
* ADX
so that your chart matches as close as possible to TradingLatino chart.
ZIGNALY INTEGRATION
This strategy supports Zignaly email integration by default. It also supports Zignaly Webhook integration.
ZIGNALY INTEGRATION - Email integration example
What you would write in your alert message:
||{{strategy.order.alert_message}}||key=MYSECRETKEY||
ZIGNALY INTEGRATION - Webhook integration example
What you would write in your alert message:
{ {{strategy.order.alert_message}} , "key" : "MYSECRETKEY" }
CREDITS
I have reused and adapted some code from
'Directional Movement Index + ADX & Keylevel Support' study
which it's from TradingView console user.
I have reused and adapted some code from
'3ema' study
which it's from TradingView hunganhnguyen1193 user.
I have reused and adapted some code from
'Squeeze Momentum Indicator ' study
which it's from TradingView LazyBear user.
I have reused and adapted some code from
'Strategy Tester EMA-SMA-RSI-MACD' study
which it's from TradingView fikira user.
I have reused and adapted some code from
'Support Resistance MTF' study
which it's from TradingView LonesomeTheBlue user.
I have reused and adapted some code from
'TF Segmented Linear Regression' study
which it's from TradingView alexgrover user.
I have reused and adapted some code from
"Poor man's volume profile" study
which it's from TradingView IldarAkhmetgaleev user.
FEEDBACK
Please check the strategy source code for more detailed information
where, among others, I explain all of the substrats
and if they are implemented or not.
Q1. Did I understand wrong any of the Jaime substrats (which I have implemented)?
Q2. The strategy yields quite profit when we should long (EMA10 from 1d timeframe is higher than EMA55 from 1d timeframe.
Why the strategy yields much less profit when we should short (EMA10 from 1d timeframe is lower than EMA55 from 1d timeframe)?
Any idea if you need to do something else rather than just reverse what Jaime does when longing?
FREQUENTLY ASKED QUESTIONS
FAQ1. Why are you giving this strategy for free?
TradingLatino and his fellow enthusiasts taught me this strategy. Now I'm giving back to them.
FAQ2. Seriously! Why are you giving this strategy for free?
I'm confident his strategy might be improved a lot. By keeping it to myself I would avoid other people contributions to improve it.
Now that everyone can contribute this is a win-win.
FAQ3. How can I connect this strategy to my Exchange account?
It seems that you can attach alerts to strategies.
You might want to combine it with a paying account which enable Webhook URLs to work.
I don't know how all of this works right now so I cannot give you advice on it.
You will have to do your own research on this subject. But, be careful. Automating trades, if not done properly,
might end on you automating losses.
FAQ4. I have just found that this strategy by default gives more than 3.97% of 'maximum series of losses'. That's unacceptable according to my risk management policy.
You might want to reduce default stop loss setting from 7% to something like 5% till you are ok with the 'maximum series of losses'.
FAQ5. Where can I learn more about your work on this strategy?
Check the source code. You might find unused strategies. Either because there's not a substantial increases on earnings. Or maybe because they have not been implemented yet.
FAQ6. How much leverage is applied in this strategy?
No leverage.
FAQ7. Any difference with original Jaime Merino strategy?
Most of the times Jaime defines an stop loss at the price entry. That's not the case here. The default stop loss is 7% (but, don't be confused it only means losing 1% of your investment thanks to risk management). There's also a trailing take profit that triggers at 2% profit with a 1% trailing.
FAQ8. Why this strategy return is so small?
The strategy should be improved a lot. And, well, backtesting in this platform is not guaranteed to return theoric results comparable to real-life returns. That's why I'm personally forward testing this strategy to verify it.
MENSAJE EN CASTELLANO
En primer lugar se agradece feedback para mejorar la estrategia.
Si eres un usuario avanzado y quieres colaborar en mejorar el script no dudes en comentar abajo.
Ten en cuenta que aunque toda esta descripción tenga que estar en inglés no es obligatorio que el comentario esté en inglés.
CHISTE - CASTELLANO
¡Pero Jaime!
¡400.000!
¡Tu da mun!
Efficient Support & Resistance LevelsThis script is a mixture of my two previous scripts "True Strong Classical Support/Resistance Levels" and "Hidden Supports & Resistances + Round Levels". This combination brings on better identification of the most efficient support/resistance levels.
Note that "Hidden SnR Levels" part of the code is only expected to work on Forex charts, but apart from that, the other parts could be applied to any chart.
The script may:
- Draw classical support/resistance levels which retraced the price previously, aided by multi-timeframe analysis
- Draw hidden support/resistance levels based on psychological patterns of the price
- Adjust to wicks better than Pine Script built-in pivot functions
- Differ the levels color based on chart reactions
- Merge nearby classical levels to avoid congestion on the chart
Feel free to use it and send me your thoughts.
[PX] External LevelHello everyone,
today I'd like to share a script, which enables you to use external logic to plot levels on your chart.
How does it work?
The concept is based on two scripts. One script, which uses an external input as a trigger to print a new level and one script that calculates an output, which will be fetched.
Sounds complicated? It really is not! Let's take a closer look.
// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © paaax
//@version=4
study("RSI OS/OB")
l = input(14, "RSI Length")
ob = input(70, "Overbought")
os = input(30, "Oversold")
r = rsi(close, l)
hline(ob)
hline(os)
plot(r, "RSI", color=color.orange)
// The following plot produces an output, which will be fetched the "External Level"-script.
// It evaluates to one of the following three values: 1.0, -1.0 or 0.0
plot(crossover(r, ob) ? 1.0 : crossunder(r, os) ? -1.0 : 0.0, "Output", transp=100)
The example script above uses an RSI and two threshold levels (70 and 30). The logic here is, that whenever the RSI is crossing down the lower threshold or crossing up the upper threshold we'd consider the current movement to be either oversold or overbought. Therefore, it's a point of interest, which we could visualize with a level.
The script creates an output when the crossover or crossunder of a threshold happens. A crossover would result in a value of 1.0, a crossunder in a value of -1.0. In all other cases the value would be 0.0.
The output of the RSI script would then be used as an input of the External Level script, which has a "Source"-parameter in its input-section. If the fetched input shows 1.0, then the script prints a resistance level. If it shows -1.0 a support level will be printed. And that's basically it. A very simple approach to print levels on your chart with an infinite number of use cases.
For example, you could use fetch outputs from a MACD script, MA script, outputs based on volume or price movement. Just remember the output has to evaluate to either 1.0 or -1.0 and has to be selected in the input-section.
Hope that might be useful to some of you :)
Please click the "Like"-button and follow me for future open-source script publications.
If you are looking for help with your custom PineScript development, don't hesitate to contact me directly here on Tradingview or through the link in my signature :)
[fikira] Fibonacci MA / EMA's (Fibma / Fibema)I've made SMA/EMA's NOT based on the principle of the 2(1+1), 3(2+1),
5(3+2), 8(5+3), 13(8+5), 21(13+8), 34(21+13), 55(34+21), ... numbers,
but based on these following Fibonacci numbers:
0,236
0,382
0,500
0,618
0,764
1
Ending up with 2 series of Fibma / Fibema:
"Tiny Fibma / Fibema":
24, 38, 50, 62, 76, 100
"Big Fibma / Fibema":
236, 382, 500, 618, 764, 1000
IMHO it is striking how these lines often act as Resistance/Support,
although (except the 50, 100 & 500) they are not typical MA/EMA's.
They perform very well on every Timeframe as well!
Week:
3 Days:
1 Day:
4h:
1h:
Even on the 15 minutes:
Or 5':
Things to watch for:
Price compared to the Tiny or Big Fibma / Fibema (below or above)
Price compared to important Fibma / Fibema (for example below or
above MA 236, MA 764, MA 1000, ...)
Crossing of Fibma / Fibema 24/76, 236/764 and 38/62, 382/618
(bullish crossover = Lime coloured "cloud", bearish crossunder = Red coloured "cloud"),
...
I've made a change in barcolor if the close crosses the "Big Fibma / Fibema 500"
If price closes above MA/EMA 500, the first bar is yellow coloured,
if price stays above this level, candles are coloured lime/orange (= very bullish)
If price closes under MA/EMA 500, the first bar is purple,
if price stays under this level, candles are standard coloured (= very bearish)
Strategy will follow,
Thanks!
SOLARIZED PERSISTENT S/R LINESSupport and Resistance Lines Persist until new S/R lines are established.
Adaptive Genesis Engine [AGE]ADAPTIVE GENESIS ENGINE (AGE)
Pure Signal Evolution Through Genetic Algorithms
Where Darwin Meets Technical Analysis
🧬 WHAT YOU'RE GETTING - THE PURE INDICATOR
This is a technical analysis indicator - it generates signals, visualizes probability, and shows you the evolutionary process in real-time. This is NOT a strategy with automatic execution - it's a sophisticated signal generation system that you control .
What This Indicator Does:
Generates Long/Short entry signals with probability scores (35-88% range)
Evolves a population of up to 12 competing strategies using genetic algorithms
Validates strategies through walk-forward optimization (train/test cycles)
Visualizes signal quality through premium gradient clouds and confidence halos
Displays comprehensive metrics via enhanced dashboard
Provides alerts for entries and exits
Works on any timeframe, any instrument, any broker
What This Indicator Does NOT Do:
Execute trades automatically
Manage positions or calculate position sizes
Place orders on your behalf
Make trading decisions for you
This is pure signal intelligence. AGE tells you when and how confident it is. You decide whether and how much to trade.
🔬 THE SCIENCE: GENETIC ALGORITHMS MEET TECHNICAL ANALYSIS
What Makes This Different - The Evolutionary Foundation
Most indicators are static - they use the same parameters forever, regardless of market conditions. AGE is alive . It maintains a population of competing strategies that evolve, adapt, and improve through natural selection principles:
Birth: New strategies spawn through crossover breeding (combining DNA from fit parents) plus random mutation for exploration
Life: Each strategy trades virtually via shadow portfolios, accumulating wins/losses, tracking drawdown, and building performance history
Selection: Strategies are ranked by comprehensive fitness scoring (win rate, expectancy, drawdown control, signal efficiency)
Death: Weak strategies are culled periodically, with elite performers (top 2 by default) protected from removal
Evolution: The gene pool continuously improves as successful traits propagate and unsuccessful ones die out
This is not curve-fitting. Each new strategy must prove itself on out-of-sample data through walk-forward validation before being trusted for live signals.
🧪 THE DNA: WHAT EVOLVES
Every strategy carries a 10-gene chromosome controlling how it interprets market data:
Signal Sensitivity Genes
Entropy Sensitivity (0.5-2.0): Weight given to market order/disorder calculations. Low values = conservative, require strong directional clarity. High values = aggressive, act on weaker order signals.
Momentum Sensitivity (0.5-2.0): Weight given to RSI/ROC/MACD composite. Controls responsiveness to momentum shifts vs. mean-reversion setups.
Structure Sensitivity (0.5-2.0): Weight given to support/resistance positioning. Determines how much price location within swing range matters.
Probability Adjustment Genes
Probability Boost (-0.10 to +0.10): Inherent bias toward aggressive (+) or conservative (-) entries. Acts as personality trait - some strategies naturally optimistic, others pessimistic.
Trend Strength Requirement (0.3-0.8): Minimum trend conviction needed before signaling. Higher values = only trades strong trends, lower values = acts in weak/sideways markets.
Volume Filter (0.5-1.5): Strictness of volume confirmation. Higher values = requires strong volume, lower values = volume less important.
Risk Management Genes
ATR Multiplier (1.5-4.0): Base volatility scaling for all price levels. Controls whether strategy uses tight or wide stops/targets relative to ATR.
Stop Multiplier (1.0-2.5): Stop loss tightness. Lower values = aggressive profit protection, higher values = more breathing room.
Target Multiplier (1.5-4.0): Profit target ambition. Lower values = quick scalping exits, higher values = swing trading holds.
Adaptation Gene
Regime Adaptation (0.0-1.0): How much strategy adjusts behavior based on detected market regime (trending/volatile/choppy). Higher values = more reactive to regime changes.
The Magic: AGE doesn't just try random combinations. Through tournament selection and fitness-weighted crossover, successful gene combinations spread through the population while unsuccessful ones fade away. Over 50-100 bars, you'll see the population converge toward genes that work for YOUR instrument and timeframe.
📊 THE SIGNAL ENGINE: THREE-LAYER SYNTHESIS
Before any strategy generates a signal, AGE calculates probability through multi-indicator confluence:
Layer 1 - Market Entropy (Information Theory)
Measures whether price movements exhibit directional order or random walk characteristics:
The Math:
Shannon Entropy = -Σ(p × log(p))
Market Order = 1 - (Entropy / 0.693)
What It Means:
High entropy = choppy, random market → low confidence signals
Low entropy = directional market → high confidence signals
Direction determined by up-move vs down-move dominance over lookback period (default: 20 bars)
Signal Output: -1.0 to +1.0 (bearish order to bullish order)
Layer 2 - Momentum Synthesis
Combines three momentum indicators into single composite score:
Components:
RSI (40% weight): Normalized to -1/+1 scale using (RSI-50)/50
Rate of Change (30% weight): Percentage change over lookback (default: 14 bars), clamped to ±1
MACD Histogram (30% weight): Fast(12) - Slow(26), normalized by ATR
Why This Matters: RSI catches mean-reversion opportunities, ROC catches raw momentum, MACD catches momentum divergence. Weighting favors RSI for reliability while keeping other perspectives.
Signal Output: -1.0 to +1.0 (strong bearish to strong bullish)
Layer 3 - Structure Analysis
Evaluates price position within swing range (default: 50-bar lookback):
Position Classification:
Bottom 20% of range = Support Zone → bullish bounce potential
Top 20% of range = Resistance Zone → bearish rejection potential
Middle 60% = Neutral Zone → breakout/breakdown monitoring
Signal Logic:
At support + bullish candle = +0.7 (strong buy setup)
At resistance + bearish candle = -0.7 (strong sell setup)
Breaking above range highs = +0.5 (breakout confirmation)
Breaking below range lows = -0.5 (breakdown confirmation)
Consolidation within range = ±0.3 (weak directional bias)
Signal Output: -1.0 to +1.0 (bearish structure to bullish structure)
Confluence Voting System
Each layer casts a vote (Long/Short/Neutral). The system requires minimum 2-of-3 agreement (configurable 1-3) before generating a signal:
Examples:
Entropy: Bullish, Momentum: Bullish, Structure: Neutral → Signal generated (2 long votes)
Entropy: Bearish, Momentum: Neutral, Structure: Neutral → No signal (only 1 short vote)
All three bullish → Signal generated with +5% probability bonus
This is the key to quality. Single indicators give too many false signals. Triple confirmation dramatically improves accuracy.
📈 PROBABILITY CALCULATION: HOW CONFIDENCE IS MEASURED
Base Probability:
Raw_Prob = 50% + (Average_Signal_Strength × 25%)
Then AGE applies strategic adjustments:
Trend Alignment:
Signal with trend: +4%
Signal against strong trend: -8%
Weak/no trend: no adjustment
Regime Adaptation:
Trending market (efficiency >50%, moderate vol): +3%
Volatile market (vol ratio >1.5x): -5%
Choppy market (low efficiency): -2%
Volume Confirmation:
Volume > 70% of 20-bar SMA: no change
Volume below threshold: -3%
Volatility State (DVS Ratio):
High vol (>1.8x baseline): -4% (reduce confidence in chaos)
Low vol (<0.7x baseline): -2% (markets can whipsaw in compression)
Moderate elevated vol (1.0-1.3x): +2% (trending conditions emerging)
Confluence Bonus:
All 3 indicators agree: +5%
2 of 3 agree: +2%
Strategy Gene Adjustment:
Probability Boost gene: -10% to +10%
Regime Adaptation gene: scales regime adjustments by 0-100%
Final Probability: Clamped between 35% (minimum) and 88% (maximum)
Why These Ranges?
Below 35% = too uncertain, better not to signal
Above 88% = unrealistic, creates overconfidence
Sweet spot: 65-80% for quality entries
🔄 THE SHADOW PORTFOLIO SYSTEM: HOW STRATEGIES COMPETE
Each active strategy maintains a virtual trading account that executes in parallel with real-time data:
Shadow Trading Mechanics
Entry Logic:
Calculate signal direction, probability, and confluence using strategy's unique DNA
Check if signal meets quality gate:
Probability ≥ configured minimum threshold (default: 65%)
Confluence ≥ configured minimum (default: 2 of 3)
Direction is not zero (must be long or short, not neutral)
Verify signal persistence:
Base requirement: 2 bars (configurable 1-5)
Adapts based on probability: high-prob signals (75%+) enter 1 bar faster, low-prob signals need 1 bar more
Adjusts for regime: trending markets reduce persistence by 1, volatile markets add 1
Apply additional filters:
Trend strength must exceed strategy's requirement gene
Regime filter: if volatile market detected, probability must be 72%+ to override
Volume confirmation required (volume > 70% of average)
If all conditions met for required persistence bars, enter shadow position at current close price
Position Management:
Entry Price: Recorded at close of entry bar
Stop Loss: ATR-based distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio
Take Profit: ATR-based distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio
Position: +1 (long) or -1 (short), only one at a time per strategy
Exit Logic:
Check if price hit stop (on low) or target (on high) on current bar
Record trade outcome in R-multiples (profit/loss normalized by ATR)
Update performance metrics:
Total trades counter incremented
Wins counter (if profit > 0)
Cumulative P&L updated
Peak equity tracked (for drawdown calculation)
Maximum drawdown from peak recorded
Enter cooldown period (default: 8 bars, configurable 3-20) before next entry allowed
Reset signal age counter to zero
Walk-Forward Tracking:
During position lifecycle, trades are categorized:
Training Phase (first 250 bars): Trade counted toward training metrics
Testing Phase (next 75 bars): Trade counted toward testing metrics (out-of-sample)
Live Phase (after WFO period): Trade counted toward overall metrics
Why Shadow Portfolios?
No lookahead bias (uses only data available at the bar)
Realistic execution simulation (entry on close, stop/target checks on high/low)
Independent performance tracking for true fitness comparison
Allows safe experimentation without risking capital
Each strategy learns from its own experience
🏆 FITNESS SCORING: HOW STRATEGIES ARE RANKED
Fitness is not just win rate. AGE uses a comprehensive multi-factor scoring system:
Core Metrics (Minimum 3 trades required)
Win Rate (30% of fitness):
WinRate = Wins / TotalTrades
Normalized directly (0.0-1.0 scale)
Total P&L (30% of fitness):
Normalized_PnL = (PnL + 300) / 600
Clamped 0.0-1.0. Assumes P&L range of -300R to +300R for normalization scale.
Expectancy (25% of fitness):
Expectancy = Total_PnL / Total_Trades
Normalized_Expectancy = (Expectancy + 30) / 60
Clamped 0.0-1.0. Rewards consistency of profit per trade.
Drawdown Control (15% of fitness):
Normalized_DD = 1 - (Max_Drawdown / 15)
Clamped 0.0-1.0. Penalizes strategies that suffer large equity retracements from peak.
Sample Size Adjustment
Quality Factor:
<50 trades: 1.0 (full weight, small sample)
50-100 trades: 0.95 (slight penalty for medium sample)
100 trades: 0.85 (larger penalty for large sample)
Why penalize more trades? Prevents strategies from gaming the system by taking hundreds of tiny trades to inflate statistics. Favors quality over quantity.
Bonus Adjustments
Walk-Forward Validation Bonus:
if (WFO_Validated):
Fitness += (WFO_Efficiency - 0.5) × 0.1
Strategies proven on out-of-sample data receive up to +10% fitness boost based on test/train efficiency ratio.
Signal Efficiency Bonus (if diagnostics enabled):
if (Signals_Evaluated > 10):
Pass_Rate = Signals_Passed / Signals_Evaluated
Fitness += (Pass_Rate - 0.1) × 0.05
Rewards strategies that generate high-quality signals passing the quality gate, not just profitable trades.
Final Fitness: Clamped at 0.0 minimum (prevents negative fitness values)
Result: Elite strategies typically achieve 0.50-0.75 fitness. Anything above 0.60 is excellent. Below 0.30 is prime candidate for culling.
🔬 WALK-FORWARD OPTIMIZATION: ANTI-OVERFITTING PROTECTION
This is what separates AGE from curve-fitted garbage indicators.
The Three-Phase Process
Every new strategy undergoes a rigorous validation lifecycle:
Phase 1 - Training Window (First 250 bars, configurable 100-500):
Strategy trades normally via shadow portfolio
All trades count toward training performance metrics
System learns which gene combinations produce profitable patterns
Tracks independently: Training_Trades, Training_Wins, Training_PnL
Phase 2 - Testing Window (Next 75 bars, configurable 30-200):
Strategy continues trading without any parameter changes
Trades now count toward testing performance metrics (separate tracking)
This is out-of-sample data - strategy has never seen these bars during "optimization"
Tracks independently: Testing_Trades, Testing_Wins, Testing_PnL
Phase 3 - Validation Check:
Minimum_Trades = 5 (configurable 3-15)
IF (Train_Trades >= Minimum AND Test_Trades >= Minimum):
WR_Efficiency = Test_WinRate / Train_WinRate
Expectancy_Efficiency = Test_Expectancy / Train_Expectancy
WFO_Efficiency = (WR_Efficiency + Expectancy_Efficiency) / 2
IF (WFO_Efficiency >= 0.55): // configurable 0.3-0.9
Strategy.Validated = TRUE
Strategy receives fitness bonus
ELSE:
Strategy receives 30% fitness penalty
ELSE:
Validation deferred (insufficient trades in one or both periods)
What Validation Means
Validated Strategy (Green "✓ VAL" in dashboard):
Performed at least 55% as well on unseen data compared to training data
Gets fitness bonus: +(efficiency - 0.5) × 0.1
Receives priority during tournament selection for breeding
More likely to be chosen as active trading strategy
Unvalidated Strategy (Orange "○ TRAIN" in dashboard):
Failed to maintain performance on test data (likely curve-fitted to training period)
Receives 30% fitness penalty (0.7x multiplier)
Makes strategy prime candidate for culling
Can still trade but with lower selection probability
Insufficient Data (continues collecting):
Hasn't completed both training and testing periods yet
OR hasn't achieved minimum trade count in both periods
Validation check deferred until requirements met
Why 55% Efficiency Threshold?
If a strategy earned 10R during training but only 5.5R during testing, it still proved an edge exists beyond random luck. Requiring 100% efficiency would be unrealistic - market conditions change between periods. But requiring >50% ensures the strategy didn't completely degrade on fresh data.
The Protection: Strategies that work great on historical data but fail on new data are automatically identified and penalized. This prevents the population from being polluted by overfitted strategies that would fail in live trading.
🌊 DYNAMIC VOLATILITY SCALING (DVS): ADAPTIVE STOP/TARGET PLACEMENT
AGE doesn't use fixed stop distances. It adapts to current volatility conditions in real-time.
Four Volatility Measurement Methods
1. ATR Ratio (Simple Method):
Current_Vol = ATR(14) / Close
Baseline_Vol = SMA(Current_Vol, 100)
Ratio = Current_Vol / Baseline_Vol
Basic comparison of current ATR to 100-bar moving average baseline.
2. Parkinson (High-Low Range Based):
For each bar: HL = log(High / Low)
Parkinson_Vol = sqrt(Σ(HL²) / (4 × Period × log(2)))
More stable than close-to-close volatility. Captures intraday range expansion without overnight gap noise.
3. Garman-Klass (OHLC Based):
HL_Term = 0.5 × ²
CO_Term = (2×log(2) - 1) × ²
GK_Vol = sqrt(Σ(HL_Term - CO_Term) / Period)
Most sophisticated estimator. Incorporates all four price points (open, high, low, close) plus gap information.
4. Ensemble Method (Default - Median of All Three):
Ratio_1 = ATR_Current / ATR_Baseline
Ratio_2 = Parkinson_Current / Parkinson_Baseline
Ratio_3 = GK_Current / GK_Baseline
DVS_Ratio = Median(Ratio_1, Ratio_2, Ratio_3)
Why Ensemble?
Takes median to avoid outliers and false spikes
If ATR jumps but range-based methods stay calm, median prevents overreaction
If one method fails, other two compensate
Most robust approach across different market conditions
Sensitivity Scaling
Scaled_Ratio = (Raw_Ratio) ^ Sensitivity
Sensitivity 0.3: Cube root - heavily dampens volatility impact
Sensitivity 0.5: Square root - moderate dampening
Sensitivity 0.7 (Default): Balanced response to volatility changes
Sensitivity 1.0: Linear - full 1:1 volatility impact
Sensitivity 1.5: Exponential - amplified response to volatility spikes
Safety Clamps: Final DVS Ratio always clamped between 0.5x and 2.5x baseline to prevent extreme position sizing or stop placement errors.
How DVS Affects Shadow Trading
Every strategy's stop and target distances are multiplied by the current DVS ratio:
Stop Loss Distance:
Stop_Distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio
Take Profit Distance:
Target_Distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio
Example Scenario:
ATR = 10 points
Strategy's ATR_Mult gene = 2.5
Strategy's Stop_Mult gene = 1.5
Strategy's Target_Mult gene = 2.5
DVS_Ratio = 1.4 (40% above baseline volatility - market heating up)
Stop = 10 × 2.5 × 1.5 × 1.4 = 52.5 points (vs. 37.5 in normal vol)
Target = 10 × 2.5 × 2.5 × 1.4 = 87.5 points (vs. 62.5 in normal vol)
Result:
During volatility spikes: Stops automatically widen to avoid noise-based exits, targets extend for bigger moves
During calm periods: Stops tighten for better risk/reward, targets compress for realistic profit-taking
Strategies adapt risk management to match current market behavior
🧬 THE EVOLUTIONARY CYCLE: SPAWN, COMPETE, CULL
Initialization (Bar 1)
AGE begins with 4 seed strategies (if evolution enabled):
Seed Strategy #0 (Balanced):
All sensitivities at 1.0 (neutral)
Zero probability boost
Moderate trend requirement (0.4)
Standard ATR/stop/target multiples (2.5/1.5/2.5)
Mid-level regime adaptation (0.5)
Seed Strategy #1 (Momentum-Focused):
Lower entropy sensitivity (0.7), higher momentum (1.5)
Slight probability boost (+0.03)
Higher trend requirement (0.5)
Tighter stops (1.3), wider targets (3.0)
Seed Strategy #2 (Entropy-Driven):
Higher entropy sensitivity (1.5), lower momentum (0.8)
Slight probability penalty (-0.02)
More trend tolerant (0.6)
Wider stops (1.8), standard targets (2.5)
Seed Strategy #3 (Structure-Based):
Balanced entropy/momentum (0.8/0.9), high structure (1.4)
Slight probability boost (+0.02)
Lower trend requirement (0.35)
Moderate risk parameters (1.6/2.8)
All seeds start with WFO validation bypassed if WFO is disabled, or must validate if enabled.
Spawning New Strategies
Timing (Adaptive):
Historical phase: Every 30 bars (configurable 10-100)
Live phase: Every 200 bars (configurable 100-500)
Automatically switches to live timing when barstate.isrealtime triggers
Conditions:
Current population < max population limit (default: 8, configurable 4-12)
At least 2 active strategies exist (need parents)
Available slot in population array
Selection Process:
Run tournament selection 3 times with different seeds
Each tournament: randomly sample active strategies, pick highest fitness
Best from 3 tournaments becomes Parent 1
Repeat independently for Parent 2
Ensures fit parents but maintains diversity
Crossover Breeding:
For each of 10 genes:
Parent1_Fitness = fitness
Parent2_Fitness = fitness
Weight1 = Parent1_Fitness / (Parent1_Fitness + Parent2_Fitness)
Gene1 = parent1's value
Gene2 = parent2's value
Child_Gene = Weight1 × Gene1 + (1 - Weight1) × Gene2
Fitness-weighted crossover ensures fitter parent contributes more genetic material.
Mutation:
For each gene in child:
IF (random < mutation_rate):
Gene_Range = GENE_MAX - GENE_MIN
Noise = (random - 0.5) × 2 × mutation_strength × Gene_Range
Mutated_Gene = Clamp(Child_Gene + Noise, GENE_MIN, GENE_MAX)
Historical mutation rate: 20% (aggressive exploration)
Live mutation rate: 8% (conservative stability)
Mutation strength: 12% of gene range (configurable 5-25%)
Initialization of New Strategy:
Unique ID assigned (total_spawned counter)
Parent ID recorded
Generation = max(parent generations) + 1
Birth bar recorded (for age tracking)
All performance metrics zeroed
Shadow portfolio reset
WFO validation flag set to false (must prove itself)
Result: New strategy with hybrid DNA enters population, begins trading in next bar.
Competition (Every Bar)
All active strategies:
Calculate their signal based on unique DNA
Check quality gate with their thresholds
Manage shadow positions (entries/exits)
Update performance metrics
Recalculate fitness score
Track WFO validation progress
Strategies compete indirectly through fitness ranking - no direct interaction.
Culling Weak Strategies
Timing (Adaptive):
Historical phase: Every 60 bars (configurable 20-200, should be 2x spawn interval)
Live phase: Every 400 bars (configurable 200-1000, should be 2x spawn interval)
Minimum Adaptation Score (MAS):
Initial MAS = 0.10
MAS decays: MAS × 0.995 every cull cycle
Minimum MAS = 0.03 (floor)
MAS represents the "survival threshold" - strategies below this fitness level are vulnerable.
Culling Conditions (ALL must be true):
Population > minimum population (default: 3, configurable 2-4)
At least one strategy has fitness < MAS
Strategy's age > culling interval (prevents premature culling of new strategies)
Strategy is not in top N elite (default: 2, configurable 1-3)
Culling Process:
Find worst strategy:
For each active strategy:
IF (age > cull_interval):
Fitness = base_fitness
IF (not WFO_validated AND WFO_enabled):
Fitness × 0.7 // 30% penalty for unvalidated
IF (Fitness < MAS AND Fitness < worst_fitness_found):
worst_strategy = this_strategy
worst_fitness = Fitness
IF (worst_strategy found):
Count elite strategies with fitness > worst_fitness
IF (elite_count >= elite_preservation_count):
Deactivate worst_strategy (set active flag = false)
Increment total_culled counter
Elite Protection:
Even if a strategy's fitness falls below MAS, it survives if fewer than N strategies are better. This prevents culling when population is generally weak.
Result: Weak strategies removed from population, freeing slots for new spawns. Gene pool improves over time.
Selection for Display (Every Bar)
AGE chooses one strategy to display signals:
Best fitness = -1
Selected = none
For each active strategy:
Fitness = base_fitness
IF (WFO_validated):
Fitness × 1.3 // 30% bonus for validated strategies
IF (Fitness > best_fitness):
best_fitness = Fitness
selected_strategy = this_strategy
Display selected strategy's signals on chart
Result: Only the highest-fitness (optionally validated-boosted) strategy's signals appear as chart markers. Other strategies trade invisibly in shadow portfolios.
🎨 PREMIUM VISUALIZATION SYSTEM
AGE includes sophisticated visual feedback that standard indicators lack:
1. Gradient Probability Cloud (Optional, Default: ON)
Multi-layer gradient showing signal buildup 2-3 bars before entry:
Activation Conditions:
Signal persistence > 0 (same directional signal held for multiple bars)
Signal probability ≥ minimum threshold (65% by default)
Signal hasn't yet executed (still in "forming" state)
Visual Construction:
7 gradient layers by default (configurable 3-15)
Each layer is a line-fill pair (top line, bottom line, filled between)
Layer spacing: 0.3 to 1.0 × ATR above/below price
Outer layers = faint, inner layers = bright
Color transitions from base to intense based on layer position
Transparency scales with probability (high prob = more opaque)
Color Selection:
Long signals: Gradient from theme.gradient_bull_mid to theme.gradient_bull_strong
Short signals: Gradient from theme.gradient_bear_mid to theme.gradient_bear_strong
Base transparency: 92%, reduces by up to 8% for high-probability setups
Dynamic Behavior:
Cloud grows/shrinks as signal persistence increases/decreases
Redraws every bar while signal is forming
Disappears when signal executes or invalidates
Performance Note: Computationally expensive due to linefill objects. Disable or reduce layers if chart performance degrades.
2. Population Fitness Ribbon (Optional, Default: ON)
Histogram showing fitness distribution across active strategies:
Activation: Only draws on last bar (barstate.islast) to avoid historical clutter
Visual Construction:
10 histogram layers by default (configurable 5-20)
Plots 50 bars back from current bar
Positioned below price at: lowest_low(100) - 1.5×ATR (doesn't interfere with price action)
Each layer represents a fitness threshold (evenly spaced min to max fitness)
Layer Logic:
For layer_num from 0 to ribbon_layers:
Fitness_threshold = min_fitness + (max_fitness - min_fitness) × (layer / layers)
Count strategies with fitness ≥ threshold
Height = ATR × 0.15 × (count / total_active)
Y_position = base_level + ATR × 0.2 × layer
Color = Gradient from weak to strong based on layer position
Line_width = Scaled by height (taller = thicker)
Visual Feedback:
Tall, bright ribbon = healthy population, many fit strategies at high fitness levels
Short, dim ribbon = weak population, few strategies achieving good fitness
Ribbon compression (layers close together) = population converging to similar fitness
Ribbon spread = diverse fitness range, active selection pressure
Use Case: Quick visual health check without opening dashboard. Ribbon growing upward over time = population improving.
3. Confidence Halo (Optional, Default: ON)
Circular polyline around entry signals showing probability strength:
Activation: Draws when new position opens (shadow_position changes from 0 to ±1)
Visual Construction:
20-segment polyline forming approximate circle
Center: Low - 0.5×ATR (long) or High + 0.5×ATR (short)
Radius: 0.3×ATR (low confidence) to 1.0×ATR (elite confidence)
Scales with: (probability - min_probability) / (1.0 - min_probability)
Color Coding:
Elite (85%+): Cyan (theme.conf_elite), large radius, minimal transparency (40%)
Strong (75-85%): Strong green (theme.conf_strong), medium radius, moderate transparency (50%)
Good (65-75%): Good green (theme.conf_good), smaller radius, more transparent (60%)
Moderate (<65%): Moderate green (theme.conf_moderate), tiny radius, very transparent (70%)
Technical Detail:
Uses chart.point array with index-based positioning
5-bar horizontal spread for circular appearance (±5 bars from entry)
Curved=false (Pine Script polyline limitation)
Fill color matches line color but more transparent (88% vs line's transparency)
Purpose: Instant visual probability assessment. No need to check dashboard - halo size/brightness tells the story.
4. Evolution Event Markers (Optional, Default: ON)
Visual indicators of genetic algorithm activity:
Spawn Markers (Diamond, Cyan):
Plots when total_spawned increases on current bar
Location: bottom of chart (location.bottom)
Color: theme.spawn_marker (cyan/bright blue)
Size: tiny
Indicates new strategy just entered population
Cull Markers (X-Cross, Red):
Plots when total_culled increases on current bar
Location: bottom of chart (location.bottom)
Color: theme.cull_marker (red/pink)
Size: tiny
Indicates weak strategy just removed from population
What It Tells You:
Frequent spawning early = population building, active exploration
Frequent culling early = high selection pressure, weak strategies dying fast
Balanced spawn/cull = healthy evolutionary churn
No markers for long periods = stable population (evolution plateaued or optimal genes found)
5. Entry/Exit Markers
Clear visual signals for selected strategy's trades:
Long Entry (Triangle Up, Green):
Plots when selected strategy opens long position (position changes 0 → +1)
Location: below bar (location.belowbar)
Color: theme.long_primary (green/cyan depending on theme)
Transparency: Scales with probability:
Elite (85%+): 0% (fully opaque)
Strong (75-85%): 10%
Good (65-75%): 20%
Acceptable (55-65%): 35%
Size: small
Short Entry (Triangle Down, Red):
Plots when selected strategy opens short position (position changes 0 → -1)
Location: above bar (location.abovebar)
Color: theme.short_primary (red/pink depending on theme)
Transparency: Same scaling as long entries
Size: small
Exit (X-Cross, Orange):
Plots when selected strategy closes position (position changes ±1 → 0)
Location: absolute (at actual exit price if stop/target lines enabled)
Color: theme.exit_color (orange/yellow depending on theme)
Transparency: 0% (fully opaque)
Size: tiny
Result: Clean, probability-scaled markers that don't clutter chart but convey essential information.
6. Stop Loss & Take Profit Lines (Optional, Default: ON)
Visual representation of shadow portfolio risk levels:
Stop Loss Line:
Plots when selected strategy has active position
Level: shadow_stop value from selected strategy
Color: theme.short_primary with 60% transparency (red/pink, subtle)
Width: 2
Style: plot.style_linebr (breaks when no position)
Take Profit Line:
Plots when selected strategy has active position
Level: shadow_target value from selected strategy
Color: theme.long_primary with 60% transparency (green, subtle)
Width: 2
Style: plot.style_linebr (breaks when no position)
Purpose:
Shows where shadow portfolio would exit for stop/target
Helps visualize strategy's risk/reward ratio
Useful for manual traders to set similar levels
Disable for cleaner chart (recommended for presentations)
7. Dynamic Trend EMA
Gradient-colored trend line that visualizes trend strength:
Calculation:
EMA(close, trend_length) - default 50 period (configurable 20-100)
Slope calculated over 10 bars: (current_ema - ema ) / ema × 100
Color Logic:
Trend_direction:
Slope > 0.1% = Bullish (1)
Slope < -0.1% = Bearish (-1)
Otherwise = Neutral (0)
Trend_strength = abs(slope)
Color = Gradient between:
- Neutral color (gray/purple)
- Strong bullish (bright green) if direction = 1
- Strong bearish (bright red) if direction = -1
Gradient factor = trend_strength (0 to 1+ scale)
Visual Behavior:
Faint gray/purple = weak/no trend (choppy conditions)
Light green/red = emerging trend (low strength)
Bright green/red = strong trend (high conviction)
Color intensity = trend strength magnitude
Transparency: 50% (subtle, doesn't overpower price action)
Purpose: Subconscious awareness of trend state without checking dashboard or indicators.
8. Regime Background Tinting (Subtle)
Ultra-low opacity background color indicating detected market regime:
Regime Detection:
Efficiency = directional_movement / total_range (over trend_length bars)
Vol_ratio = current_volatility / average_volatility
IF (efficiency > 0.5 AND vol_ratio < 1.3):
Regime = Trending (1)
ELSE IF (vol_ratio > 1.5):
Regime = Volatile (2)
ELSE:
Regime = Choppy (0)
Background Colors:
Trending: theme.regime_trending (dark green, 92-93% transparency)
Volatile: theme.regime_volatile (dark red, 93% transparency)
Choppy: No tint (normal background)
Purpose:
Subliminal regime awareness
Helps explain why signals are/aren't generating
Trending = ideal conditions for AGE
Volatile = fewer signals, higher thresholds applied
Choppy = mixed signals, lower confidence
Important: Extremely subtle by design. Not meant to be obvious, just subconscious context.
📊 ENHANCED DASHBOARD
Comprehensive real-time metrics in single organized panel (top-right position):
Dashboard Structure (5 columns × 14 rows)
Header Row:
Column 0: "🧬 AGE PRO" + phase indicator (🔴 LIVE or ⏪ HIST)
Column 1: "POPULATION"
Column 2: "PERFORMANCE"
Column 3: "CURRENT SIGNAL"
Column 4: "ACTIVE STRATEGY"
Column 0: Market State
Regime (📈 TREND / 🌊 CHAOS / ➖ CHOP)
DVS Ratio (current volatility scaling factor, format: #.##)
Trend Direction (▲ BULL / ▼ BEAR / ➖ FLAT with color coding)
Trend Strength (0-100 scale, format: #.##)
Column 1: Population Metrics
Active strategies (count / max_population)
Validated strategies (WFO passed / active total)
Current generation number
Total spawned (all-time strategy births)
Total culled (all-time strategy deaths)
Column 2: Aggregate Performance
Total trades across all active strategies
Aggregate win rate (%) - color-coded:
Green (>55%)
Orange (45-55%)
Red (<45%)
Total P&L in R-multiples - color-coded by positive/negative
Best fitness score in population (format: #.###)
MAS - Minimum Adaptation Score (cull threshold, format: #.###)
Column 3: Current Signal Status
Status indicator:
"▲ LONG" (green) if selected strategy in long position
"▼ SHORT" (red) if selected strategy in short position
"⏳ FORMING" (orange) if signal persisting but not yet executed
"○ WAITING" (gray) if no active signal
Confidence percentage (0-100%, format: #.#%)
Quality assessment:
"🔥 ELITE" (cyan) for 85%+ probability
"✓ STRONG" (bright green) for 75-85%
"○ GOOD" (green) for 65-75%
"- LOW" (dim) for <65%
Confluence score (X/3 format)
Signal age:
"X bars" if signal forming
"IN TRADE" if position active
"---" if no signal
Column 4: Selected Strategy Details
Strategy ID number (#X format)
Validation status:
"✓ VAL" (green) if WFO validated
"○ TRAIN" (orange) if still in training/testing phase
Generation number (GX format)
Personal fitness score (format: #.### with color coding)
Trade count
P&L and win rate (format: #.#R (##%) with color coding)
Color Scheme:
Panel background: theme.panel_bg (dark, low opacity)
Panel headers: theme.panel_header (slightly lighter)
Primary text: theme.text_primary (bright, high contrast)
Secondary text: theme.text_secondary (dim, lower contrast)
Positive metrics: theme.metric_positive (green)
Warning metrics: theme.metric_warning (orange)
Negative metrics: theme.metric_negative (red)
Special markers: theme.validated_marker, theme.spawn_marker
Update Frequency: Only on barstate.islast (current bar) to minimize CPU usage
Purpose:
Quick overview of entire system state
No need to check multiple indicators
Trading decisions informed by population health, regime state, and signal quality
Transparency into what AGE is thinking
🔍 DIAGNOSTICS PANEL (Optional, Default: OFF)
Detailed signal quality tracking for optimization and debugging:
Panel Structure (3 columns × 8 rows)
Position: Bottom-right corner (doesn't interfere with main dashboard)
Header Row:
Column 0: "🔍 DIAGNOSTICS"
Column 1: "COUNT"
Column 2: "%"
Metrics Tracked (for selected strategy only):
Total Evaluated:
Every signal that passed initial calculation (direction ≠ 0)
Represents total opportunities considered
✓ Passed:
Signals that passed quality gate and executed
Green color coding
Percentage of evaluated signals
Rejection Breakdown:
⨯ Probability:
Rejected because probability < minimum threshold
Most common rejection reason typically
⨯ Confluence:
Rejected because confluence < minimum required (e.g., only 1 of 3 indicators agreed)
⨯ Trend:
Rejected because signal opposed strong trend
Indicates counter-trend protection working
⨯ Regime:
Rejected because volatile regime detected and probability wasn't high enough to override
Shows regime filter in action
⨯ Volume:
Rejected because volume < 70% of 20-bar average
Indicates volume confirmation requirement
Color Coding:
Passed count: Green (success metric)
Rejection counts: Red (failure metrics)
Percentages: Gray (neutral, informational)
Performance Cost: Slight CPU overhead for tracking counters. Disable when not actively optimizing settings.
How to Use Diagnostics
Scenario 1: Too Few Signals
Evaluated: 200
Passed: 10 (5%)
⨯ Probability: 120 (60%)
⨯ Confluence: 40 (20%)
⨯ Others: 30 (15%)
Diagnosis: Probability threshold too high for this strategy's DNA.
Solution: Lower min probability from 65% to 60%, or allow strategy more time to evolve better DNA.
Scenario 2: Too Many False Signals
Evaluated: 200
Passed: 80 (40%)
Strategy win rate: 45%
Diagnosis: Quality gate too loose, letting low-quality signals through.
Solution: Raise min probability to 70%, or increase min confluence to 3 (all indicators must agree).
Scenario 3: Regime-Specific Issues
⨯ Regime: 90 (45% of rejections)
Diagnosis: Frequent volatile regime detection blocking otherwise good signals.
Solution: Either accept fewer trades during chaos (recommended), or disable regime filter if you want signals regardless of market state.
Optimization Workflow:
Enable diagnostics
Run 200+ bars
Analyze rejection patterns
Adjust settings based on data
Re-run and compare pass rate
Disable diagnostics when satisfied
⚙️ CONFIGURATION GUIDE
🧬 Evolution Engine Settings
Enable AGE Evolution (Default: ON):
ON: Full genetic algorithm (recommended for best results)
OFF: Uses only 4 seed strategies, no spawning/culling (static population for comparison testing)
Max Population (4-12, Default: 8):
Higher = more diversity, more exploration, slower performance
Lower = faster computation, less exploration, risk of premature convergence
Sweet spot: 6-8 for most use cases
4 = minimum for meaningful evolution
12 = maximum before diminishing returns
Min Population (2-4, Default: 3):
Safety floor - system never culls below this count
Prevents population extinction during harsh selection
Should be at least half of max population
Elite Preservation (1-3, Default: 2):
Top N performers completely immune to culling
Ensures best genes always survive
1 = minimal protection, aggressive selection
2 = balanced (recommended)
3 = conservative, slower gene pool turnover
Historical: Spawn Interval (10-100, Default: 30):
Bars between spawning new strategies during historical data
Lower = faster evolution, more exploration
Higher = slower evolution, more evaluation time per strategy
30 bars = ~1-2 hours on 15min chart
Historical: Cull Interval (20-200, Default: 60):
Bars between culling weak strategies during historical data
Should be 2x spawn interval for balanced churn
Lower = aggressive selection pressure
Higher = patient evaluation
Live: Spawn Interval (100-500, Default: 200):
Bars between spawning during live trading
Much slower than historical for stability
Prevents population chaos during live trading
200 bars = ~1.5 trading days on 15min chart
Live: Cull Interval (200-1000, Default: 400):
Bars between culling during live trading
Should be 2x live spawn interval
Conservative removal during live trading
Historical: Mutation Rate (0.05-0.40, Default: 0.20):
Probability each gene mutates during breeding (20% = 2 out of 10 genes on average)
Higher = more exploration, slower convergence
Lower = more exploitation, faster convergence but risk of local optima
20% balances exploration vs exploitation
Live: Mutation Rate (0.02-0.20, Default: 0.08):
Mutation rate during live trading
Much lower for stability (don't want population to suddenly degrade)
8% = mostly inherits parent genes with small tweaks
Mutation Strength (0.05-0.25, Default: 0.12):
How much genes change when mutated (% of gene's total range)
0.05 = tiny nudges (fine-tuning)
0.12 = moderate jumps (recommended)
0.25 = large leaps (aggressive exploration)
Example: If gene range is 0.5-2.0, 12% strength = ±0.18 possible change
📈 Signal Quality Settings
Min Signal Probability (0.55-0.80, Default: 0.65):
Quality gate threshold - signals below this never generate
0.55-0.60 = More signals, accept lower confidence (higher risk)
0.65 = Institutional-grade balance (recommended)
0.70-0.75 = Fewer but higher-quality signals (conservative)
0.80+ = Very selective, very few signals (ultra-conservative)
Min Confluence Score (1-3, Default: 2):
Required indicator agreement before signal generates
1 = Any single indicator can trigger (not recommended - too many false signals)
2 = Requires 2 of 3 indicators agree (RECOMMENDED for balance)
3 = All 3 must agree (very selective, few signals, high quality)
Base Persistence Bars (1-5, Default: 2):
Base bars signal must persist before entry
System adapts automatically:
High probability signals (75%+) enter 1 bar faster
Low probability signals (<68%) need 1 bar more
Trending regime: -1 bar (faster entries)
Volatile regime: +1 bar (more confirmation)
1 = Immediate entry after quality gate (responsive but prone to whipsaw)
2 = Balanced confirmation (recommended)
3-5 = Patient confirmation (slower but more reliable)
Cooldown After Trade (3-20, Default: 8):
Bars to wait after exit before next entry allowed
Prevents overtrading and revenge trading
3 = Minimal cooldown (active trading)
8 = Balanced (recommended)
15-20 = Conservative (position trading)
Entropy Length (10-50, Default: 20):
Lookback period for market order/disorder calculation
Lower = more responsive to regime changes (noisy)
Higher = more stable regime detection (laggy)
20 = works across most timeframes
Momentum Length (5-30, Default: 14):
Period for RSI/ROC calculations
14 = standard (RSI default)
Lower = more signals, less reliable
Higher = fewer signals, more reliable
Structure Length (20-100, Default: 50):
Lookback for support/resistance swing range
20 = short-term swings (day trading)
50 = medium-term structure (recommended)
100 = major structure (position trading)
Trend EMA Length (20-100, Default: 50):
EMA period for trend detection and direction bias
20 = short-term trend (responsive)
50 = medium-term trend (recommended)
100 = long-term trend (position trading)
ATR Period (5-30, Default: 14):
Period for volatility measurement
14 = standard ATR
Lower = more responsive to vol changes
Higher = smoother vol calculation
📊 Volatility Scaling (DVS) Settings
Enable DVS (Default: ON):
Dynamic volatility scaling for adaptive stop/target placement
Highly recommended to leave ON
OFF only for testing fixed-distance stops
DVS Method (Default: Ensemble):
ATR Ratio: Simple, fast, single-method (good for beginners)
Parkinson: High-low range based (good for intraday)
Garman-Klass: OHLC based (sophisticated, considers gaps)
Ensemble: Median of all three (RECOMMENDED - most robust)
DVS Memory (20-200, Default: 100):
Lookback for baseline volatility comparison
20 = very responsive to vol changes (can overreact)
100 = balanced adaptation (recommended)
200 = slow, stable baseline (minimizes false vol signals)
DVS Sensitivity (0.3-1.5, Default: 0.7):
How much volatility affects scaling (power-law exponent)
0.3 = Conservative, heavily dampens vol impact (cube root)
0.5 = Moderate dampening (square root)
0.7 = Balanced response (recommended)
1.0 = Linear, full 1:1 vol response
1.5 = Aggressive, amplified response (exponential)
🔬 Walk-Forward Optimization Settings
Enable WFO (Default: ON):
Out-of-sample validation to prevent overfitting
Highly recommended to leave ON
OFF only for testing or if you want unvalidated strategies
Training Window (100-500, Default: 250):
Bars for in-sample optimization
100 = fast validation, less data (risky)
250 = balanced (recommended) - about 1-2 months on daily, 1-2 weeks on 15min
500 = patient validation, more data (conservative)
Testing Window (30-200, Default: 75):
Bars for out-of-sample validation
Should be ~30% of training window
30 = minimal test (fast validation)
75 = balanced (recommended)
200 = extensive test (very conservative)
Min Trades for Validation (3-15, Default: 5):
Required trades in BOTH training AND testing periods
3 = minimal sample (risky, fast validation)
5 = balanced (recommended)
10+ = conservative (slow validation, high confidence)
WFO Efficiency Threshold (0.3-0.9, Default: 0.55):
Minimum test/train performance ratio required
0.30 = Very loose (test must be 30% as good as training)
0.55 = Balanced (recommended) - test must be 55% as good
0.70+ = Strict (test must closely match training)
Higher = fewer validated strategies, lower risk of overfitting
🎨 Premium Visuals Settings
Visual Theme:
Neon Genesis: Cyberpunk aesthetic (cyan/magenta/purple)
Carbon Fiber: Industrial look (blue/red/gray)
Quantum Blue: Quantum computing (blue/purple/pink)
Aurora: Northern lights (teal/orange/purple)
⚡ Gradient Probability Cloud (Default: ON):
Multi-layer gradient showing signal buildup
Turn OFF if chart lags or for cleaner look
Cloud Gradient Layers (3-15, Default: 7):
More layers = smoother gradient, more CPU intensive
Fewer layers = faster, blockier appearance
🎗️ Population Fitness Ribbon (Default: ON):
Histogram showing fitness distribution
Turn OFF for cleaner chart
Ribbon Layers (5-20, Default: 10):
More layers = finer fitness detail
Fewer layers = simpler histogram
⭕ Signal Confidence Halo (Default: ON):
Circular indicator around entry signals
Size/brightness scales with probability
Minimal performance cost
🔬 Evolution Event Markers (Default: ON):
Diamond (spawn) and X (cull) markers
Shows genetic algorithm activity
Minimal performance cost
🎯 Stop/Target Lines (Default: ON):
Shows shadow portfolio stop/target levels
Turn OFF for cleaner chart (recommended for screenshots/presentations)
📊 Enhanced Dashboard (Default: ON):
Comprehensive metrics panel
Should stay ON unless you want zero overlays
🔍 Diagnostics Panel (Default: OFF):
Detailed signal rejection tracking
Turn ON when optimizing settings
Turn OFF during normal use (slight performance cost)
📈 USAGE WORKFLOW - HOW TO USE THIS INDICATOR
Phase 1: Initial Setup & Learning
Add AGE to your chart
Recommended timeframes: 15min, 30min, 1H (best signal-to-noise ratio)
Works on: 5min (day trading), 4H (swing trading), Daily (position trading)
Load 1000+ bars for sufficient evolution history
Let the population evolve (100+ bars minimum)
First 50 bars: Random exploration, poor results expected
Bars 50-150: Population converging, fitness improving
Bars 150+: Stable performance, validated strategies emerging
Watch the dashboard metrics
Population should grow toward max capacity
Generation number should advance regularly
Validated strategies counter should increase
Best fitness should trend upward toward 0.50-0.70 range
Observe evolution markers
Diamond markers (cyan) = new strategies spawning
X markers (red) = weak strategies being culled
Frequent early activity = healthy evolution
Activity slowing = population stabilizing
Be patient. Evolution takes time. Don't judge performance before 150+ bars.
Phase 2: Signal Observation
Watch signals form
Gradient cloud builds up 2-3 bars before entry
Cloud brightness = probability strength
Cloud thickness = signal persistence
Check signal quality
Look at confidence halo size when entry marker appears
Large bright halo = elite setup (85%+)
Medium halo = strong setup (75-85%)
Small halo = good setup (65-75%)
Verify market conditions
Check trend EMA color (green = uptrend, red = downtrend, gray = choppy)
Check background tint (green = trending, red = volatile, clear = choppy)
Trending background + aligned signal = ideal conditions
Review dashboard signal status
Current Signal column shows:
Status (Long/Short/Forming/Waiting)
Confidence % (actual probability value)
Quality assessment (Elite/Strong/Good)
Confluence score (2/3 or 3/3 preferred)
Only signals meeting ALL quality gates appear on chart. If you're not seeing signals, population is either still learning or market conditions aren't suitable.
Phase 3: Manual Trading Execution
When Long Signal Fires:
Verify confidence level (dashboard or halo size)
Confirm trend alignment (EMA sloping up, green color)
Check regime (preferably trending or choppy, avoid volatile)
Enter long manually on your broker platform
Set stop loss at displayed stop line level (if lines enabled), or use your own risk management
Set take profit at displayed target line level, or trail manually
Monitor position - exit if X marker appears (signal reversal)
When Short Signal Fires:
Same verification process
Confirm downtrend (EMA sloping down, red color)
Enter short manually
Use displayed stop/target levels or your own
AGE tells you WHEN and HOW CONFIDENT. You decide WHETHER and HOW MUCH.
Phase 4: Set Up Alerts (Never Miss a Signal)
Right-click on indicator name in legend
Select "Add Alert"
Choose condition:
"AGE Long" = Long entry signal fired
"AGE Short" = Short entry signal fired
"AGE Exit" = Position reversal/exit signal
Set notification method:
Sound alert (popup on chart)
Email notification
Webhook to phone/trading platform
Mobile app push notification
Name the alert (e.g., "AGE BTCUSD 15min Long")
Save alert
Recommended: Set alerts for both long and short, enable mobile push notifications. You'll get alerted in real-time even if not watching charts.
Phase 5: Monitor Population Health
Weekly Review:
Check dashboard Population column:
Active count should be near max (6-8 of 8)
Validated count should be >50% of active
Generation should be advancing (1-2 per week typical)
Check dashboard Performance column:
Aggregate win rate should be >50% (target: 55-65%)
Total P&L should be positive (may fluctuate)
Best fitness should be >0.50 (target: 0.55-0.70)
MAS should be declining slowly (normal adaptation)
Check Active Strategy column:
Selected strategy should be validated (✓ VAL)
Personal fitness should match best fitness
Trade count should be accumulating
Win rate should be >50%
Warning Signs:
Zero validated strategies after 300+ bars = settings too strict or market unsuitable
Best fitness stuck <0.30 = population struggling, consider parameter adjustment
No spawning/culling for 200+ bars = evolution stalled (may be optimal or need reset)
Aggregate win rate <45% sustained = system not working on this instrument/timeframe
Health Check Pass:
50%+ strategies validated
Best fitness >0.50
Aggregate win rate >52%
Regular spawn/cull activity
Selected strategy validated
Phase 6: Optimization (If Needed)
Enable Diagnostics Panel (bottom-right) for data-driven tuning:
Problem: Too Few Signals
Evaluated: 200
Passed: 8 (4%)
⨯ Probability: 140 (70%)
Solutions:
Lower min probability: 65% → 60% or 55%
Reduce min confluence: 2 → 1
Lower base persistence: 2 → 1
Increase mutation rate temporarily to explore new genes
Check if regime filter is blocking signals (⨯ Regime high?)
Problem: Too Many False Signals
Evaluated: 200
Passed: 90 (45%)
Win rate: 42%
Solutions:
Raise min probability: 65% → 70% or 75%
Increase min confluence: 2 → 3
Raise base persistence: 2 → 3
Enable WFO if disabled (validates strategies before use)
Check if volume filter is being ignored (⨯ Volume low?)
Problem: Counter-Trend Losses
⨯ Trend: 5 (only 5% rejected)
Losses often occur against trend
Solutions:
System should already filter trend opposition
May need stronger trend requirement
Consider only taking signals aligned with higher timeframe trend
Use longer trend EMA (50 → 100)
Problem: Volatile Market Whipsaws
⨯ Regime: 100 (50% rejected by volatile regime)
Still getting stopped out frequently
Solutions:
System is correctly blocking volatile signals
Losses happening because vol filter isn't strict enough
Consider not trading during volatile periods (respect the regime)
Or disable regime filter and accept higher risk
Optimization Workflow:
Enable diagnostics
Run 200+ bars with current settings
Analyze rejection patterns and win rate
Make ONE change at a time (scientific method)
Re-run 200+ bars and compare results
Keep change if improvement, revert if worse
Disable diagnostics when satisfied
Never change multiple parameters at once - you won't know what worked.
Phase 7: Multi-Instrument Deployment
AGE learns independently on each chart:
Recommended Strategy:
Deploy AGE on 3-5 different instruments
Different asset classes ideal (e.g., ES futures, EURUSD, BTCUSD, SPY, Gold)
Each learns optimal strategies for that instrument's personality
Take signals from all 5 charts
Natural diversification reduces overall risk
Why This Works:
When one market is choppy, others may be trending
Different instruments respond to different news/catalysts
Portfolio-level win rate more stable than single-instrument
Evolution explores different parameter spaces on each chart
Setup:
Same settings across all charts (or customize if preferred)
Set alerts for all
Take every validated signal across all instruments
Position size based on total account (don't overleverage any single signal)
⚠️ REALISTIC EXPECTATIONS - CRITICAL READING
What AGE Can Do
✅ Generate probability-weighted signals using genetic algorithms
✅ Evolve strategies in real-time through natural selection
✅ Validate strategies on out-of-sample data (walk-forward optimization)
✅ Adapt to changing market conditions automatically over time
✅ Provide comprehensive metrics on population health and signal quality
✅ Work on any instrument, any timeframe, any broker
✅ Improve over time as weak strategies are culled and fit strategies breed
What AGE Cannot Do
❌ Win every trade (typical win rate: 55-65% at best)
❌ Predict the future with certainty (markets are probabilistic, not deterministic)
❌ Work perfectly from bar 1 (needs 100-150 bars to learn and stabilize)
❌ Guarantee profits under all market conditions
❌ Replace your trading discipline and risk management
❌ Execute trades automatically (this is an indicator, not a strategy)
❌ Prevent all losses (drawdowns are normal and expected)
❌ Adapt instantly to regime changes (re-learning takes 50-100 bars)
Performance Realities
Typical Performance After Evolution Stabilizes (150+ bars):
Win Rate: 55-65% (excellent for trend-following systems)
Profit Factor: 1.5-2.5 (realistic for validated strategies)
Signal Frequency: 5-15 signals per 100 bars (quality over quantity)
Drawdown Periods: 20-40% of time in equity retracement (normal trading reality)
Max Consecutive Losses: 5-8 losses possible even with 60% win rate (probability says this is normal)
Evolution Timeline:
Bars 0-50: Random exploration, learning phase - poor results expected, don't judge yet
Bars 50-150: Population converging, fitness climbing - results improving
Bars 150-300: Stable performance, most strategies validated - consistent results
Bars 300+: Mature population, optimal genes dominant - best results
Market Condition Dependency:
Trending Markets: AGE excels - clear directional moves, high-probability setups
Choppy Markets: AGE struggles - fewer signals generated, lower win rate
Volatile Markets: AGE cautious - higher rejection rate, wider stops, fewer trades
Market Regime Changes:
When market shifts from trending to choppy overnight
Validated strategies can become temporarily invalidated
AGE will adapt through evolution, but not instantly
Expect 50-100 bar re-learning period after major regime shifts
Fitness may temporarily drop then recover
This is NOT a holy grail. It's a sophisticated signal generator that learns and adapts using genetic algorithms. Your success depends on:
Patience during learning periods (don't abandon after 3 losses)
Proper position sizing (risk 0.5-2% per trade, not 10%)
Following signals consistently (cherry-picking defeats statistical edge)
Not abandoning system prematurely (give it 200+ bars minimum)
Understanding probability (60% win rate means 40% of trades WILL lose)
Respecting market conditions (trending = trade more, choppy = trade less)
Managing emotions (AGE is emotionless, you need to be too)
Expected Drawdowns:
Single-strategy max DD: 10-20% of equity (normal)
Portfolio across multiple instruments: 5-15% (diversification helps)
Losing streaks: 3-5 consecutive losses expected periodically
No indicator eliminates risk. AGE manages risk through:
Quality gates (rejecting low-probability signals)
Confluence requirements (multi-indicator confirmation)
Persistence requirements (no knee-jerk reactions)
Regime awareness (reduced trading in chaos)
Walk-forward validation (preventing overfitting)
But it cannot prevent all losses. That's inherent to trading.
🔧 TECHNICAL SPECIFICATIONS
Platform: TradingView Pine Script v5
Indicator Type: Overlay indicator (plots on price chart)
Execution Type: Signals only - no automatic order placement
Computational Load:
Moderate to High (genetic algorithms + shadow portfolios)
8 strategies × shadow portfolio simulation = significant computation
Premium visuals add additional load (gradient cloud, fitness ribbon)
TradingView Resource Limits (Built-in Caps):
Max Bars Back: 500 (sufficient for WFO and evolution)
Max Labels: 100 (plenty for entry/exit markers)
Max Lines: 150 (adequate for stop/target lines)
Max Boxes: 50 (not heavily used)
Max Polylines: 100 (confidence halos)
Recommended Chart Settings:
Timeframe: 15min to 1H (optimal signal/noise balance)
5min: Works but noisier, more signals
4H/Daily: Works but fewer signals
Bars Loaded: 1000+ (ensures sufficient evolution history)
Replay Mode: Excellent for testing without risk
Performance Optimization Tips:
Disable gradient cloud if chart lags (most CPU intensive visual)
Disable fitness ribbon if still laggy
Reduce cloud layers from 7 to 3
Reduce ribbon layers from 10 to 5
Turn off diagnostics panel unless actively tuning
Close other heavy indicators to free resources
Browser/Platform Compatibility:
Works on all modern browsers (Chrome, Firefox, Safari, Edge)
Mobile app supported (full functionality on phone/tablet)
Desktop app supported (best performance)
Web version supported (may be slower on older computers)
Data Requirements:
Real-time or delayed data both work
No special data feeds required
Works with TradingView's standard data
Historical + live data seamlessly integrated
🎓 THEORETICAL FOUNDATIONS
AGE synthesizes advanced concepts from multiple disciplines:
Evolutionary Computation
Genetic Algorithms (Holland, 1975): Population-based optimization through natural selection metaphor
Tournament Selection: Fitness-based parent selection with diversity preservation
Crossover Operators: Fitness-weighted gene recombination from two parents
Mutation Operators: Random gene perturbation for exploration of new parameter space
Elitism: Preservation of top N performers to prevent loss of best solutions
Adaptive Parameters: Different mutation rates for historical vs. live phases
Technical Analysis
Support/Resistance: Price structure within swing ranges
Trend Following: EMA-based directional bias
Momentum Analysis: RSI, ROC, MACD composite indicators
Volatility Analysis: ATR-based risk scaling
Volume Confirmation: Trade activity validation
Information Theory
Shannon Entropy (1948): Quantification of market order vs. disorder
Signal-to-Noise Ratio: Directional information vs. random walk
Information Content: How much "information" a price move contains
Statistics & Probability
Walk-Forward Analysis: Rolling in-sample/out-of-sample optimization
Out-of-Sample Validation: Testing on unseen data to prevent overfitting
Monte Carlo Principles: Shadow portfolio simulation with realistic execution
Expectancy Theory: Win rate × avg win - loss rate × avg loss
Probability Distributions: Signal confidence quantification
Risk Management
ATR-Based Stops: Volatility-normalized risk per trade
Volatility Regime Detection: Market state classification (trending/choppy/volatile)
Drawdown Control: Peak-to-trough equity measurement
R-Multiple Normalization: Performance measurement in risk units
Machine Learning Concepts
Online Learning: Continuous adaptation as new data arrives
Fitness Functions: Multi-objective optimization (win rate + expectancy + drawdown)
Exploration vs. Exploitation: Balance between trying new strategies and using proven ones
Overfitting Prevention: Walk-forward validation as regularization
Novel Contribution:
AGE is the first TradingView indicator to apply genetic algorithms to real-time indicator parameter optimization while maintaining strict anti-overfitting controls through walk-forward validation.
Most "adaptive" indicators simply recalibrate lookback periods or thresholds. AGE evolves entirely new strategies through competitive selection - it's not parameter tuning, it's Darwinian evolution of trading logic itself.
The combination of:
Genetic algorithm population management
Shadow portfolio simulation for realistic fitness evaluation
Walk-forward validation to prevent overfitting
Multi-indicator confluence for signal quality
Dynamic volatility scaling for adaptive risk
...creates a system that genuinely learns and improves over time while avoiding the curse of curve-fitting that plagues most optimization approaches.
🏗️ DEVELOPMENT NOTES
This project represents months of intensive development, facing significant technical challenges:
Challenge 1: Making Genetics Actually Work
Early versions spawned garbage strategies that polluted the gene pool:
Random gene combinations produced nonsensical parameter sets
Weak strategies survived too long, dragging down population
No clear convergence toward optimal solutions
Solution:
Comprehensive fitness scoring (4 factors: win rate, P&L, expectancy, drawdown)
Elite preservation (top 2 always protected)
Walk-forward validation (unproven strategies penalized 30%)
Tournament selection (fitness-weighted breeding)
Adaptive culling (MAS decay creates increasing selection pressure)
Challenge 2: Balancing Evolution Speed vs. Stability
Too fast = population chaos, no convergence. Too slow = can't adapt to regime changes.
Solution:
Dual-phase timing: Fast evolution during historical (30/60 bar intervals), slow during live (200/400 bar intervals)
Adaptive mutation rates: 20% historical, 8% live
Spawn/cull ratio: Always 2:1 to prevent population collapse
Challenge 3: Shadow Portfolio Accuracy
Needed realistic trade simulation without lookahead bias:
Can't peek at future bars for exits
Must track multiple portfolios simultaneously
Stop/target checks must use bar's high/low correctly
Solution:
Entry on close (realistic)
Exit checks on current bar's high/low (realistic)
Independent position tracking per strategy
Cooldown periods to prevent unrealistic rapid re-entry
ATR-normalized P&L (R-multiples) for fair comparison across volatility regimes
Challenge 4: Pine Script Compilation Limits
Hit TradingView's execution limits multiple times:
Too many array operations
Too many variables
Too complex conditional logic
Solution:
Optimized data structures (single DNA array instead of 8 separate arrays)
Minimal visual overlays (only essential plots)
Efficient fitness calculations (vectorized where possible)
Strategic use of barstate.islast to minimize dashboard updates
Challenge 5: Walk-Forward Implementation
Standard WFO is difficult in Pine Script:
Can't easily "roll forward" through historical data
Can't re-optimize strategies mid-stream
Must work in real-time streaming environment
Solution:
Age-based phase detection (first 250 bars = training, next 75 = testing)
Separate metric tracking for train vs. test
Efficiency calculation at fixed interval (after test period completes)
Validation flag persists for strategy lifetime
Challenge 6: Signal Quality Control
Early versions generated too many signals with poor win rates:
Single indicators produced excessive noise
No trend alignment
No regime awareness
Instant entries on single-bar spikes
Solution:
Three-layer confluence system (entropy + momentum + structure)
Minimum 2-of-3 agreement requirement
Trend alignment checks (penalty for counter-trend)
Regime-based probability adjustments
Persistence requirements (signals must hold multiple bars)
Volume confirmation
Quality gate (probability + confluence thresholds)
The Result
A system that:
Truly evolves (not just parameter sweeps)
Truly validates (out-of-sample testing)
Truly adapts (ongoing competition and breeding)
Stays within TradingView's platform constraints
Provides institutional-quality signals
Maintains transparency (full metrics dashboard)
Development time: 3+ months of iterative refinement
Lines of code: ~1500 (highly optimized)
Test instruments: ES, NQ, EURUSD, BTCUSD, SPY, AAPL
Test timeframes: 5min, 15min, 1H, Daily
🎯 FINAL WORDS
The Adaptive Genesis Engine is not just another indicator - it's a living system that learns, adapts, and improves through the same principles that drive biological evolution. Every bar it observes adds to its experience. Every strategy it spawns explores new parameter combinations. Every strategy it culls removes weakness from the gene pool.
This is evolution in action on your charts.
You're not getting a static formula locked in time. You're getting a system that thinks , that competes , that survives through natural selection. The strongest strategies rise to the top. The weakest die. The gene pool improves generation after generation.
AGE doesn't claim to predict the future - it adapts to whatever the future brings. When markets shift from trending to choppy, from calm to volatile, from bullish to bearish - AGE evolves new strategies suited to the new regime.
Use it on any instrument. Any timeframe. Any market condition. AGE will adapt.
This indicator gives you the pure signal intelligence. How you choose to act on it - position sizing, risk management, execution discipline - that's your responsibility. AGE tells you when and how confident . You decide whether and how much .
Trust the process. Respect the evolution. Let Darwin work.
"In markets, as in nature, it is not the strongest strategies that survive, nor the most intelligent - but those most responsive to change."
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
— Happy Holiday's
On Balance Volume [BrightSideTrading]
# On Balance Volume - Complete User Guide
## Overview
This enhanced OBV indicator provides clean, actionable volume analysis with intelligent signal filtering. It combines On-Balance Volume (OBV) with a smoothed signal line to identify shifts in buying and selling pressure without chart clutter.
**Key Features:**
- Real-time OBV and signal line visualization
- Smart crossover detection with confirmation filtering
- Z-Score momentum analysis
- Customizable signal alerts with V-shaped markers
- Window-normalized option for detrended analysis
---
## What is On-Balance Volume (OBV)?
OBV is a volume-based momentum indicator that accumulates volume on up days and subtracts volume on down days. It answers a fundamental question: **Is volume flowing in (buying) or out (selling)?**
**Formula:**
- If Close > Previous Close: OBV = Previous OBV + Volume
- If Close < Previous Close: OBV = Previous OBV - Volume
- If Close = Previous Close: OBV = Previous OBV (unchanged)
**What it tells you:**
- **Rising OBV** = Accumulation (smart money buying)
- **Falling OBV** = Distribution (smart money selling)
- **OBV above zero line** = Net positive buying pressure
- **OBV below zero line** = Net negative selling pressure
---
## Interface & Settings
### **MAIN VISUALIZATION**
**OBV Line (Green/Red Ribbon)**
- Green when OBV is above the signal line (bullish trend)
- Red when OBV is below the signal line (bearish trend)
- Toggles between window-normalized (detrended) and raw values
**Signal Line (Orange)**
- Smoothed average of OBV
- Crossovers with OBV generate buy/sell signals
- Default: 21-period SMA
**V-Shaped Markers**
- Green upward V = Bullish crossover (buy signal)
- Red downward V = Bearish crossover (sell signal)
- Appears at the OBV value when signal is triggered
**Zero Line (Yellow)**
- Center equilibrium point for volume balance
- Acts as support/resistance for OBV
- Separates buying pressure (above) from selling pressure (below)
---
### **SOURCE GROUP**
**Source**
- **Default:** Close
- **Options:** Open, High, Low, or any custom value
- Controls which price value triggers OBV direction changes
- Most traders use Close for standard OBV calculation
---
### **SIGNAL SMOOTHING GROUP**
**Show Signal?**
- **Default:** ON
- Toggle visibility of the signal line
- Disable if you prefer to see raw OBV only
**Smoothing Type**
- **SMA (Simple Moving Average)** - Default, standard smoothing
- **EMA (Exponential Moving Average)** - Faster response, weights recent bars more heavily
- **Choose SMA** for consistent, traditional OBV signals
- **Choose EMA** for faster trend identification (more whipsaws possible)
**Smoothing Length**
- **Default:** 21 bars
- **Range:** 1-200 bars
- **Lower values** (5-14): Faster signals, more noise
- **Higher values** (30-50): Slower signals, fewer false alarms
- **Recommendation:** Use 21-25 for most timeframes
---
### **SIGNAL FILTERING GROUP**
This is your primary control for signal quality and frequency.
**Show Signal Markers?**
- **Default:** ON
- Toggle the V-shaped buy/sell markers on/off
- Disable if markers distract from your analysis
**Signal Filter Type**
- **None** - Shows every single crossover (noisy, best for skilled traders)
- **Confirmation Bars** - Waits N bars before confirming signal (recommended)
- **Strength-Based** - Only signals during strong momentum (filters weakest moves)
#### **CONFIRMATION BARS MODE** (Recommended)
Best for reducing false signals while staying responsive to real moves.
**Confirmation Bars**
- **Default:** 2 bars
- **Range:** 1-10 bars
- Waits for the signal to hold for N consecutive bars after crossover
- **Setting 1:** Every crossover (same as "None")
- **Setting 2:** Wait 1 bar confirmation (good balance)
- **Setting 3:** Wait 2 bars confirmation (filters 50% of noise)
- **Setting 4+:** Very selective, misses quick reversals
**How it works:**
1. OBV crosses signal line → Confirmation counter starts
2. If OBV stays on correct side for 2 bars → V-marker appears
3. If OBV crosses back → Counter resets, no signal
#### **STRENGTH-BASED MODE**
Only signals when momentum is statistically significant.
**Min Z-Score Strength**
- **Default:** 0.3
- **Range:** 0.0-3.0
- Requires OBV deviation from its mean to reach this threshold
- **Setting 0.1-0.3:** More signals, lower quality
- **Setting 0.5-0.8:** Moderate signals, good quality
- **Setting 1.0+:** Only the strongest momentum shifts
**How it works:**
- Calculates how far OBV is from its 50-bar average (Z-score)
- Only shows signals when this distance is meaningful
- Automatically avoids weak, choppy market conditions
---
### **VISUALS & COLORS GROUP**
**Highlight Crossovers?**
- **Default:** ON
- Master toggle for all signal markers
- Turn OFF to see only the OBV/signal lines
**Apply Ribbon Filling?**
- **Default:** ON
- Colors the space between OBV and signal line
- Green fill = OBV above signal (bullish)
- Red fill = OBV below signal (bearish)
- Provides clear visual trend confirmation
- Turn OFF for minimal chart clutter
---
### **STATS & ZONES GROUP**
**Use Window-Normalized OBV (visual only)?**
- **Default:** ON
- Removes long-term trend from OBV for clearer short-term signals
- Detrends the indicator to highlight recent momentum changes
- **ON:** Better for swing trading and identifying reversals
- **OFF:** Better for trend-following strategies
- Note: Z-Score always uses raw OBV for statistical accuracy
**OBV Normalize Window**
- **Default:** 200 bars
- Lookback period for detrending calculation
- Larger values = more aggressive detrending
- Adjust if you want OBV to oscillate more/less around zero
**Show Z-Score (OBV)?**
- **Default:** ON
- Displays statistical momentum indicator below main chart
- Ranges from -3 to +3 (most data within -2 to +2)
- High Z-Score = Strong buying momentum
- Low Z-Score = Strong selling momentum
**Z-Score Lookback**
- **Default:** 50 bars
- Period for calculating Z-Score mean and standard deviation
- Larger = smoother Z-Score, slower response
- Smaller = noisier Z-Score, faster response
**Show ROC (OBV Momentum)?**
- **Default:** OFF
- Rate of Change indicator for OBV velocity
- Useful for identifying momentum turning points
- Enable if you want to see speed of volume changes
**ROC Lookback**
- **Default:** 14 bars
- Period for ROC calculation
**Show Z-Score StdDev Zones?**
- **Default:** ON
- Shaded regions around zero line showing statistical boundaries
- Inner Zone (±1 Z) = Normal variation
- Outer Zone (±2 Z) = Extreme moves, potential reversals
- Helps identify overbought/oversold volume conditions
**Inner Zone (±Z)**
- **Default:** 1.0
- First boundary for standard deviation zones
- Most normal trading occurs within ±1
**Outer Zone (±Z)**
- **Default:** 2.0
- Second boundary for extreme conditions
- Crossing these zones indicates significant momentum shift
---
## Trading Strategy Examples
### **Strategy 1: Signal Line Crossovers (Beginner)**
**Setup:**
- Signal Filter Type: **Confirmation Bars**
- Confirmation Bars: **2-3**
- Show Signal Markers: **ON**
**Rules:**
1. **BUY signal** (green V): When OBV crosses above signal line and holds for 2-3 bars
- Confirms buying pressure is building
- Look for price to follow within 1-3 bars
2. **SELL signal** (red V): When OBV crosses below signal line and holds for 2-3 bars
- Confirms selling pressure is increasing
- Expect price decline
3. **Exit:** Take profits at next signal or use price support/resistance
**Best For:** Swing trading, intraday reversals, timeframes 5m-1h
---
### **Strategy 2: Zero Line Bounce (Intermediate)**
**Setup:**
- Signal Filter Type: **Strength-Based**
- Min Z-Score Strength: **0.5**
- Show Z-Score StdDev Zones: **ON**
**Rules:**
1. **Watch OBV approach zero line** during established trends
- OBV bouncing repeatedly off zero = trend is healthy
- OBV breaking through zero = trend reversal imminent
2. **Enter on bounce:** Buy when OBV bounces from zero line in uptrend
3. **Exit on break:** Close position when OBV breaks below zero line
4. **Confirm with Z-Score:** Only take trades when Z-Score shows momentum (|Z| > 0.5)
**Best For:** Trend traders, identifying trend strength, medium timeframes 15m-4h
---
### **Strategy 3: Momentum Extremes (Advanced)**
**Setup:**
- Signal Filter Type: **None**
- Show Z-Score StdDev Zones: **ON**
- Outer Zone: **2.0**
**Rules:**
1. **Identify extremes:** When Z-Score breaks outer zone (±2.0)
- Indicator is in extreme territory
- Likely overextended
2. **Fade extremes:** Take opposite position when Z-Score hits extreme
- High Z (>2.0) = OBV overbought, expect pullback
- Low Z (<-2.0) = OBV oversold, expect bounce
3. **Confirm:** Wait for crossover signal to enter
4. **Target:** Outer zone of opposite side or zero line
**Best For:** Range trading, mean reversion, experienced traders only
---
## Reading the Indicator in Different Markets
### **Strong Uptrend**
- OBV consistently above signal line (green)
- OBV well above zero line, rising higher lows
- Z-Score positive, trending upward
- **Action:** Buy dips to signal line, sell at resistance
### **Strong Downtrend**
- OBV consistently below signal line (red)
- OBV well below zero line, making lower highs
- Z-Score negative, trending downward
- **Action:** Sell rallies to signal line, cover at support
### **Consolidation/Choppy Market**
- OBV whipsaws around signal line frequently
- Crossovers occur every few bars
- Z-Score oscillating between -1 and +1
- **Action:** Increase confirmation bars to 3-4, or switch to strength-based filter
### **Accumulation (Bottom Formation)**
- OBV rising while price is flat or falling
- Volume flowing in despite downtrend (bullish divergence)
- Z-Score climbing while price lows hold
- **Action:** Expect breakout up; prepare buy near support
### **Distribution (Top Formation)**
- OBV falling while price is flat or rising
- Volume flowing out despite uptrend (bearish divergence)
- Z-Score falling while price continues higher
- **Action:** Expect breakdown down; prepare short near resistance
---
## Parameter Tuning Guide
### **Aggressive Settings (More Signals)**
- Smoothing Length: 14
- Signal Filter: None or Confirmation Bars: 1
- Min Z-Score: 0.1
- Best for: Day trading, high volatility stocks
- Risk: More false signals
### **Balanced Settings (Recommended)**
- Smoothing Length: 21
- Signal Filter: Confirmation Bars: 2
- Min Z-Score: 0.3
- Best for: Swing trading, most market conditions
- Risk/Reward: Moderate
### **Conservative Settings (Fewer Signals)**
- Smoothing Length: 30-40
- Signal Filter: Confirmation Bars: 3-4 or Strength-Based: 0.7+
- Min Z-Score: 0.8
- Best for: Position trading, high-conviction trades only
- Risk: May miss some moves
---
## Common Questions & Troubleshooting
**Q: Why are there more sell signals than buy signals?**
A: This reflects the actual market action. Markets often decline faster than they rise (fear > greed). Confirm signals with price action and support/resistance.
**Q: The indicator keeps whipsawing, should I hide it?**
A: Increase Confirmation Bars to 3-4 or switch to Strength-Based filter. Market conditions matter—choppy markets require stricter filters.
**Q: What's the difference between normalized and raw OBV?**
A: Normalized (detrended) shows shorter-term momentum by removing long-term trends. Raw OBV shows absolute accumulation/distribution over the full period. Use normalized for swing signals, raw for trend confirmation.
**Q: My signals come too late. How do I get faster entry?**
A: Reduce Smoothing Length (try 14 instead of 21), use EMA instead of SMA, or set Confirmation Bars to 1. Trade-off: More false signals.
**Q: Can I use this for day trading?**
A: Yes, on 1m-5m charts with aggressive settings. Use Confirmation Bars: 1 and focus on Z-Score > 0.5 entries only.
**Q: Should I trade every signal?**
A: No. Filter signals using: price near support/resistance, multiple indicators confirming, and Z-Score showing momentum. Best signals occur at key levels.
---
## Best Practices
1. **Always confirm with price action:** OBV signals work best when price is near support, resistance, or moving average. Don't trade signals in a vacuum.
2. **Use volume context:** Check if volume is increasing or decreasing on the signal. Strong signals have volume confirmation (increasing volume on OBV spikes).
3. **Adjust settings per timeframe:**
- 1m-5m: Smoothing 12, Confirmation 1, Z-Score 0.2
- 15m-1h: Smoothing 20, Confirmation 2, Z-Score 0.3
- 4h-1d: Smoothing 25, Confirmation 3, Z-Score 0.5
4. **Watch the zero line:** It's your friend. OBV behavior at the zero line reveals trend strength. Bounces = healthy trend. Breaks = reversal.
5. **Risk management:** No indicator is perfect. Use proper position sizing and stop losses. OBV should confirm your thesis, not be the only reason to trade.
6. **Combine with other indicators:**
- Price moving averages for trend confirmation
- RSI or Stochastic for overbought/oversold levels
- Support/resistance for entry/exit zones
- MACD for momentum divergences
---
## Disclaimer
This indicator is for educational and informational purposes only. It is not financial advice. Past performance does not guarantee future results. Always conduct your own research and consult with a financial advisor before making trading decisions. Trading carries risk, including potential loss of principal.
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## Version History
**Version 1.0** - Initial release with enhanced signal filtering, Z-Score analysis, and customizable parameters.
