[SHORT ONLY] Consecutive Close>High[1] Mean Reversion Strategy█ STRATEGY DESCRIPTION
The "Consecutive Close > High " Mean Reversion Strategy is a contrarian daily trading system for stocks and ETFs. It identifies potential shorting opportunities by counting consecutive days where the closing price exceeds the previous day's high. When this consecutive day count reaches a predetermined threshold, and if the close is below a 200-period EMA (if enabled), a short entry is triggered, anticipating a corrective pullback.
█ HOW ARE THE CONSECUTIVE BULLISH COUNTS CALCULATED?
The strategy uses a counter variable called `bullCount` to track how many consecutive bars meet a bullish condition. Here’s a breakdown of the process:
Initialize the Counter
var int bullCount = 0
Bullish Bar Detection
Every time the close exceeds the previous bar's high, increment the counter:
if close > high
bullCount += 1
Reset on Bearish Bar
When there is a clear bearish reversal, the counter is reset to zero:
if close < low
bullCount := 0
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The count of consecutive bullish closes (where close > high ) reaches or exceeds the defined threshold (default: 3).
The signal occurs within the specified trading window (between Start Time and End Time).
2. EXIT CONDITION
An exit Signal is generated when the current close falls below the previous bar’s low (close < low ), prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
Threshold: The number of consecutive bullish closes required to trigger a short entry (default is 3).
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
EMA Filter (Optional): When enabled, short entries are only triggered if the current close is below the 200-period EMA.
█ PERFORMANCE OVERVIEW
This strategy is designed for Stocks and ETFs on the Daily timeframe and targets overextended bullish moves.
It aims to capture mean reversion by entering short after a series of consecutive bullish closes.
Further optimization is possible with additional filters (e.g., EMA, volume, or volatility).
Backtesting should be used to fine-tune the threshold and filter settings for specific market conditions.
Meanreversion
[SHORT ONLY] Internal Bar Strength (IBS) Mean Reversion Strategy█ STRATEGY DESCRIPTION
The "Internal Bar Strength (IBS) Strategy" is a mean-reversion strategy designed to identify trading opportunities based on the closing price's position within the daily price range. It enters a short position when the IBS indicates overbought conditions and exits when the IBS reaches oversold levels. This strategy is Short-Only and was designed to be used on the Daily timeframe for Stocks and ETFs.
█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) measures where the closing price falls within the high-low range of a bar. It is calculated as:
IBS = (Close - Low) / (High - Low)
- Low IBS (≤ 0.2) : Indicates the close is near the bar's low, suggesting oversold conditions.
- High IBS (≥ 0.8) : Indicates the close is near the bar's high, suggesting overbought conditions.
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The IBS value rises to or above the Upper Threshold (default: 0.9).
The Closing price is greater than the previous bars High (close>high ).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
An exit Signal is generated when the IBS value drops to or below the Lower Threshold (default: 0.3). This prompts the strategy to exit the position.
█ ADDITIONAL SETTINGS
Upper Threshold: The IBS level at which the strategy enters trades. Default is 0.9.
Lower Threshold: The IBS level at which the strategy exits short positions. Default is 0.3.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for Stocks and ETFs markets and performs best when prices frequently revert to the mean.
The strategy can be optimized further using additional conditions such as using volume or volatility filters.
It is sensitive to extreme IBS values, which help identify potential reversals.
Backtesting results should be analyzed to optimize the Upper/Lower Thresholds for specific instruments and market conditions.
ATR/CCI Adaptive Trend BandsATR/CCI Trend Bands is a dynamic trend-following indicator that combines the power of the Average True Range (ATR) and Commodity Channel Index (CCI) to create adaptive support and resistance bands. The indicator plots upper and lower trend bands based on ATR deviations while using CCI to confirm trend direction. The bands visually highlight areas of trend strength and potential reversals, helping traders identify key price zones."
🔹 Key Features:
✅ ATR-Based Trend Bands – Dynamically adjust to market volatility.
✅ CCI Confirmation – Determines whether price is in an uptrend or downtrend.
✅ Color-Coded Trendline – Blue for bullish trends, red for bearish trends.
✅ Shaded Support & Resistance Zones – Red upper bands (resistance), blue lower bands (support).
✅ Customizable Parameters – ATR length, multipliers, and CCI period can be adjusted.
🔹 How to Use:
Trend Trading: Follow the bands to ride trends with confidence.
Breakout Confirmation: Watch for price breaking above/below the bands for potential strong moves.
Reversal Trading: Use the shaded zones as dynamic support and resistance levels.
This indicator is suitable for all timeframes and markets and is designed to be a versatile tool for both trend-followers and breakout traders. 🚀📈
[SHORT ONLY] 10 Bar Low Pullback█ STRATEGY DESCRIPTION
The "10 Bar Low Pullback" strategy is a contrarian short trading system designed to capture pullbacks after a new 10‐bar low is made. it identifies a potential short opportunity when the current bar’s low breaks below the lowest low of the previous 10 bars, provided that the bar exhibits strong internal momentum as measured by its IBS value. An optional trend filter further refines entries by requiring that the close is below a 200-period EMA.
█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) measures where the closing price falls within the high-low range of a bar. It is calculated as:
ibs = (close - low) / (high - low)
- Low IBS (≤ 0.2): Indicates the close is near the bar's low, suggesting oversold conditions.
- High IBS (≥ 0.8): Indicates the close is near the bar's high, suggesting overbought conditions.
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The current bar’s low is below the lowest low of the past X bars (default: 10).
The bar’s IBS is greater than the specified threshold (default: 0.85).
The signal occurs within the defined trading window (between Start Time and End Time).
If the EMA Filter is enabled, the close must be below the 200-period EMA.
2. EXIT CONDITION
An exit Signal is generated when the current close falls below the previous bar’s low (close < low ), indicating a potential bearish reversal and prompting the strategy to close its short position.
█ ADDITIONAL SETTINGS
Lookback Period: Defines the number of bars (default is 10) over which the lowest low is calculated.
IBS Threshold: Sets the minimum required IBS value (default is 0.85) to qualify as a pullback.
Trading Window: Trades are only executed between the user-defined Start Time and End Time.
EMA Filter (Optional): When enabled, short entries are only considered if the current close is below the 200-period EMA, with the EMA period being adjustable (default is 200).
█ PERFORMANCE OVERVIEW
Designed for shorting opportunities, this strategy aims to capture pullbacks following an aggressive 10-bar low break.
It leverages a combination of a lookback low and IBS measurement to identify overextended bullish moves that may revert.
The optional EMA filter helps confirm a bearish market environment by ensuring the price remains under the trend line.
Suitable for use on various assets, including stocks and ETFs, on daily or similar timeframes.
Backtesting and parameter optimization are recommended to tailor the strategy to specific market conditions.
BB & SMA Alerts (Universal)This script will:
Plot Bollinger Bands (BB 20, 2 StdDev)
Plot SMA 50 & SMA 200 for trend analysis
Send alerts when price crosses BB, SMA 50, or SMA 200
Detect Golden Cross (Bullish) & Death Cross (Bearish) signals
Do note that this is not a guarantee as markets are often irrational, hence these indicators are supposed to supplement your decision making process and not to be used as 100% truth.
The assumptions are made as a universal format that can be used for most asset classes in Equities, Futures, Crypto.
Have not tested it on Funds, Bonds.
Appendix:
Best Practice: Use 20-SMA for Bollinger Bands and keep 50/200-SMA for trend confirmation.
SMA
• Short-Term (Fast) → 9 SMA (Great for intraday trades)
• Medium-Term → 50 SMA (Good for swing trading)
• Long-Term (Slow) → 200 SMA (For overall trend direction)
BB
Why Bollinger Bands Use SMA 20?
• Shorter time frame captures price fluctuations.
• More reactive to price changes → good for reversion trades.
• If you increase it to 50 or 200, Bollinger Bands will be too wide → making it hard to trade reversion.
• Bollinger Bands (50-SMA) → Becomes less sensitive to short-term price swings.
• Bollinger Bands (200-SMA) → Almost useless for mean reversion, since price barely touches bands.
Suggested Use Case:
🔹 Use BB (20-SMA) for entry signals.
🔹 Use 50-SMA & 200-SMA to confirm trend direction.
🔹 Example Trading Strategy:
• If price touches lower BB AND is above 200-SMA → Look for a BUY.
• If price touches upper BB AND is below 200-SMA → Look for a SELL.
3-Bar Low Strategy█ STRATEGY DESCRIPTION
The "3-Bar Low Strategy" is a mean-reversion strategy designed to identify potential buying opportunities when the price drops below the lowest low of the previous three bars. It enters a long position when specific conditions are met and exits when the price exceeds the highest high of the previous seven bars. This strategy is suitable for use on various timeframes.
█ WHAT IS THE 3-BAR LOW?
The 3-Bar Low is the lowest price observed over the last three bars. This level is used as a reference to identify potential oversold conditions and reversal points.
█ WHAT IS THE 7-BAR HIGH?
The 7-Bar High is the highest price observed over the last seven bars. This level is used as a reference to identify potential overbought conditions and exit points.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The close price is below the lowest low of the previous three bars (`close < _lowest `).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
If the EMA Filter is enabled, the close price must also be above the 200-period Exponential Moving Average (EMA).
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the highest high of the previous seven bars (`close > _highest `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
MA Period: The lookback period for the 200-period EMA used in the EMA Filter. Default is 200.
Use EMA Filter: Enables or disables the EMA Filter for long entries. Default is disabled.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for mean-reverting markets and performs best when the price frequently oscillates around key support and resistance levels.
It is sensitive to oversold conditions, as indicated by the 3-Bar Low, and overbought conditions, as indicated by the 7-Bar High.
Backtesting results should be analyzed to optimize the MA Period and EMA Filter settings for specific instruments.
[SHORT ONLY] ATR Sell the Rip Mean Reversion Strategy█ STRATEGY DESCRIPTION
The "ATR Sell the Rip Mean Reversion Strategy" is a contrarian system that targets overextended price moves on stocks and ETFs. It calculates an ATR‐based trigger level to identify shorting opportunities. When the current close exceeds this smoothed ATR trigger, and if the close is below a 200-period EMA (if enabled), the strategy initiates a short entry, aiming to profit from an anticipated corrective pullback.
█ HOW IS THE ATR SIGNAL BAND CALCULATED?
This strategy computes an ATR-based signal trigger as follows:
Calculate the ATR
The strategy computes the Average True Range (ATR) using a configurable period provided by the user:
atrValue = ta.atr(atrPeriod)
Determine the Threshold
Multiply the ATR by a predefined multiplier and add it to the current close:
atrThreshold = close + atrValue * atrMultInput
Smooth the Threshold
Apply a Simple Moving Average over a specified period to smooth out the threshold, reducing noise:
signalTrigger = ta.sma(atrThreshold, smoothPeriodInput)
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The current close is above the smoothed ATR signal trigger.
The trade occurs within the specified trading window (between Start Time and End Time).
If the EMA filter is enabled, the close must also be below the 200-period EMA.
2. EXIT CONDITION
An exit Signal is generated when the current close falls below the previous bar’s low (close < low ), indicating a potential bearish reversal and prompting the strategy to close its short position.
█ ADDITIONAL SETTINGS
ATR Period: The period used to calculate the ATR, allowing for adaptability to different volatility conditions (default is 20).
ATR Multiplier: The multiplier applied to the ATR to determine the raw threshold (default is 1.0).
Smoothing Period: The period over which the raw ATR threshold is smoothed using an SMA (default is 10).
Start Time and End Time: Defines the time window during which trades are allowed.
EMA Filter (Optional): When enabled, short entries are only executed if the current close is below the 200-period EMA, confirming a bearish trend.
█ PERFORMANCE OVERVIEW
This strategy is designed for use on the Daily timeframe, targeting stocks and ETFs by capitalizing on overextended price moves.
It utilizes a dynamic, ATR-based trigger to identify when prices have potentially peaked, setting the stage for a mean reversion short entry.
The optional EMA filter helps align trades with broader market trends, potentially reducing false signals.
Backtesting is recommended to fine-tune the ATR multiplier, smoothing period, and EMA settings to match the volatility and behavior of specific markets.
[SHORT ONLY] Consecutive Bars Above MA Strategy█ STRATEGY DESCRIPTION
The "Consecutive Bars Above MA Strategy" is a contrarian trading system aimed at exploiting overextended bullish moves in stocks and ETFs. It monitors the number of consecutive bars that close above a chosen short-term moving average (which can be either a Simple Moving Average or an Exponential Moving Average). Once the count reaches a preset threshold and the current bar’s close exceeds the previous bar’s high within a designated trading window, a short entry is initiated. An optional EMA filter further refines entries by requiring that the current close is below the 200-period EMA, helping to ensure that trades are taken in a bearish environment.
█ HOW ARE THE CONSECUTIVE BULLISH COUNTS CALCULATED?
The strategy utilizes a counter variable, `bullCount`, to track consecutive bullish bars based on their relation to the short-term moving average. Here’s how the count is determined:
Initialize the Counter
The counter is initialized at the start:
var int bullCount = na
Bullish Bar Detection
For each bar, if the close is above the selected moving average (either SMA or EMA, based on user input), the counter is incremented:
bullCount := close > signalMa ? (na(bullCount) ? 1 : bullCount + 1) : 0
Reset on Non-Bullish Condition
If the close does not exceed the moving average, the counter resets to zero, indicating a break in the consecutive bullish streak.
█ SIGNAL GENERATION
1. SHORT ENTRY
A short signal is generated when:
The number of consecutive bullish bars (i.e., bars closing above the short-term MA) meets or exceeds the defined threshold (default: 3).
The current bar’s close is higher than the previous bar’s high.
The signal occurs within the specified trading window (between Start Time and End Time).
Additionally, if the EMA filter is enabled, the entry is only executed when the current close is below the 200-period EMA.
2. EXIT CONDITION
An exit signal is triggered when the current close falls below the previous bar’s low, prompting the strategy to close the short position.
█ ADDITIONAL SETTINGS
Threshold: The number of consecutive bullish bars required to trigger a short entry (default is 3).
Trading Window: The Start Time and End Time inputs define when the strategy is active.
Moving Average Settings: Choose between SMA and EMA, and set the MA length (default is 5), which is used to assess each bar’s bullish condition.
EMA Filter (Optional): When enabled, this filter requires that the current close is below the 200-period EMA, supporting entries in a downtrend.
█ PERFORMANCE OVERVIEW
This strategy is designed for stocks and ETFs and can be applied across various timeframes.
It seeks to capture mean reversion by shorting after a series of bullish bars suggests an overextended move.
The approach employs a contrarian short entry by waiting for a breakout (close > previous high) following consecutive bullish bars.
The adjustable moving average settings and optional EMA filter allow for further optimization based on market conditions.
Comprehensive backtesting is recommended to fine-tune the threshold, moving average parameters, and filter settings for optimal performance.
HFT Liquidity Hunter]Indicator Name: HFT Liquidity Hunter
Category: Institutional Liquidity & Momentum Analysis Tool
Purpose: Identify high-probability trading zones by combining liquidity gaps, volume anomalies, and momentum extremes.
Core Components & Functionality
1. Liquidity Gap Detection
What It Does:
Tracks price "gaps" from the previous trading session where liquidity clustered.
Plots static horizontal lines at the most significant gap levels:
Red Line: Resistance zone (highest high of prior gaps).
Teal Line: Support zone (lowest low of prior gaps).
Highlights background green/red when price is above/below these zones.
2. Volume Spike Identification
Key Feature:
Detects abnormal trading volume (>1.5x 20-period average).
Critical for confirming institutional participation at key levels.
3. Momentum Extremes
Tools Included:
RSI (14-period): Flags overbought (>65) and oversold (<35) conditions.
Stochastic Oscillator (14,3,3): Measures momentum velocity via %K line.
4. Volatility Boundaries
Dynamic Bands:
Upper Band (Orange): 2 standard deviations above 20-period SMA.
Lower Band (Blue): 2 standard deviations below 20-period SMA.
Price tends to revert toward the mean (basis line) after touching bands.
5. Volume-Weighted Average Price (VWAP)
Role: Serves as a dynamic support/resistance level for the trading session.
6. Real-Time Debug Table
Function:
Tracks 6 critical conditions for trade setups (top-right corner).
✅/❌ system shows whether each criterion is met.
Key Parameters (Customizable)
Gap Lookback Bars: Number of bars analyzed to detect liquidity gaps (default: 5).
Volume Multiplier: Sensitivity for volume spikes (1.5x = 150% of average volume).
RSI/Stochastic Thresholds: Adjust overbought/oversold levels.
Zone Resolution: Timeframe for gap validity (default: 15 minutes).
How to Interpret the Indicator
Visual Elements
Green/Red Background:
Green: Price trading above prior gap high (bullish bias).
Red: Price below prior gap low (bearish bias).
Horizontal Lines:
Teal Line: Static support (demand zone) from prior gaps.
Red Line: Static resistance (supply zone) from prior gaps.
Volatility Bands:
Price at upper band = overextended rally (potential reversal).
Price at lower band = oversold drop (potential bounce).
Purple VWAP Line:
Bullish setups favored above VWAP, bearish below.
Strategic Insights
Bullish Scenario Setup
Ideal Conditions:
Price touches Lower Band (blue line).
RSI < 35 (oversold).
Stochastic %K < 20 (momentum low).
Volume Spike (blue triangle).
Price holds Above VWAP.
Near Teal Demand Zone (gap low).
Bearish Scenario Setup
Ideal Conditions:
Price tests Upper Band (orange line).
RSI > 65 (overbought).
Stochastic %K > 80 (overextended).
Volume Spike (blue triangle).
Price below VWAP.
Near Red Supply Zone (gap high).
Pro Usage Tips
Confluence Trading: Only act when ≥5/6 debug table conditions are ✅.
Time Sensitivity: Most effective during first 2 hours of market opens.
Risk Management:
Stop Loss: 1% beyond static zones (teal/red lines).
Take Profit: Opposite volatility band or gap zone.
Asset-Specific Adjustments:
High Volatility (e.g., Crypto): Increase Volume Multiplier to 2.0x.
Range-Bound Markets: Tighten RSI thresholds to 30/70.
Why Traders Use This
Institutional Edge: Maps liquidity pools where large orders cluster.
False Signal Filter: Requires volume + momentum + volatility alignment.
Multi-Timeframe Valid: Zones auto-adjust to higher timeframe flows.
This tool is designed for traders who want to align with institutional order flow while avoiding retail market noise. Always confirm with the debug table and practice disciplined risk management.
Range Filtered Trend Signals [AlgoAlpha]Introducing the Range Filtered Trend Signals , a cutting-edge trading indicator designed to detect market trends and ranging conditions with high accuracy. This indicator leverages a combination of Kalman filtering and Supertrend analysis to smooth out price fluctuations while maintaining responsiveness to trend shifts. By incorporating volatility-based range filtering, it ensures traders can differentiate between trending and ranging conditions effectively, reducing false signals and enhancing trade decision-making.
:key: Key Features
:white_check_mark: Kalman Filter Smoothing – Minimizes market noise while preserving trend clarity.
:bar_chart: Supertrend Integration – A dynamic trend-following mechanism for spotting reversals.
:fire: Volatility-Based Range Detection – Detects trending vs. ranging conditions with precision.
:art: Color-Coded Trend Signals – Instantly recognize bullish, bearish, and ranging market states.
:gear: Customizable Inputs – Fine-tune Kalman parameters, Supertrend settings, and color themes to match your strategy.
:bell: Alerts for Trend Shifts – Get real-time notifications when market conditions change!
:tools: How to Use
Add the Indicator – Click the star icon to add it to your TradingView favorites.
Analyze Market Conditions – Observe the color-coded signals and range boundaries to identify trend strength and direction.
Use Alerts for Trade Execution – Set alerts for trend shifts and market conditions to stay ahead without constantly monitoring charts.
:mag: How It Works
The Kalman filter smooths price fluctuations by dynamically adjusting its weighting based on market volatility. It helps remove noise while keeping the signal reactive to trend changes. The Supertrend calculation is then applied to the filtered price data, providing a robust trend-following mechanism. To enhance signal accuracy, a volatility-weighted range filter is incorporated, creating upper and lower boundaries that define trend conditions. When price breaks out of these boundaries, the indicator confirms trend continuation, while signals within the range indicate market consolidation. Traders can leverage this tool to enhance trade timing, filter false breakouts, and identify optimal entry/exit zones.
Enhanced Momentum Divergence Radar+ [Alpha Extract]Enhanced Momentum Divergence Radar+
The AE's Enhanced Momentum Divergence Radar+ is designed to detect momentum shifts and divergence patterns, helping traders identify potential trend reversals and continuation points. By normalizing momentum readings and applying divergence detection, it enhances market timing for entries and exits.
🔶 CALCULATION
The indicator calculates normalized momentum using a combination of Detrended Price Oscillator (DPO) and volatility-adjusted smoothing techniques. It highlights overbought and oversold conditions while identifying bullish and bearish divergences.
Core Calculation:
ATR-based volatility adjustment ensures dynamic sensitivity.
DPO is derived from the price minus a simple moving average (SMA) to isolate cyclical movements.
Momentum score is normalized using historical max values for consistent scaling.
Thresholds are dynamically adjusted based on average absolute momentum.
dpo = close - ma
sd = (dpo / volatility) * 100
normalizedSD = sd / maxAbsSD
The momentum score is plotted as a histogram, where:
Green bars indicate strong upward momentum.
Red bars indicate strong downward momentum.
Neutral values fade into gray.
🔶 DETAILS
📊 Visual Features:
Histogram bars dynamically color-coded based on momentum strength.
Threshold bands provide reference points for overbought and oversold levels.
Divergence markers (Bullish/Bearish & Hidden Bullish/Bearish) highlight key reversal signals.
🛠 How Divergences Work:
Bullish Divergence (𝓞𝓢): Price makes a lower low while momentum makes a higher low.
Bearish Divergence (𝓞𝓑): Price makes a higher high while momentum makes a lower high.
Hidden Divergences confirm trend continuations rather than reversals.
📌 Example of Divergence Logic:
bullishDiv = (low == priceLow) and (sd > momentumLow)
bearishDiv = (high == priceHigh) and (sd < momentumHigh)
🔶 EXAMPLES
📍 The chart below illustrates price reacting to momentum divergences, identifying potential tops and bottoms before major price moves.
📌 Example snapshots:
A bullish divergence leading to a reversal in price.
A bearish divergence marking the beginning of a downtrend.
🔶 SETTINGS
🔹 Customization Options:
Lookback Period: Adjusts sensitivity to market cycles.
Smoothing Period: Controls signal clarity.
Color Options: Enables bar coloring based on momentum strength.
Divergence Sensitivity: Choose to display hidden divergences.
Price Step Channel [BigBeluga]Price Step Channel is designed to provide a structured look at price trends through a dynamic step line channel, highlighting trend direction and volatility boundaries.
🔵 Key Features:
Step Line with Boundaries: The central step line adjusts with price movements, creating upper and lower boundaries based on price volatility. The channel is green during uptrends and red during downtrends, visually signaling the trend’s direction.
Fakeout Markers: "✖" markers identify potential fakeouts—moments when the price breaches the channel boundary without confirming a trend change. These markers help you spot possible mean reversion points.
Dynamic Boundary Labels: Labels at the end of the channel show the price levels of the upper and lower boundaries. In uptrends, the upper label turns green; in downtrends, the lower label turns red, providing an instant read on the trend's direction.
Customizable Display: You can toggle off the boundaries and labels for a cleaner view, focusing only on the step line and its color-coded trend signals.
🔵 When to Use:
Price Step Channel is ideal for traders looking to follow structured trends with defined volatility boundaries. The step line and color-coded channel provide clear trend insights, while the fakeout markers and customizable display options enhance flexibility in different market conditions. Whether you’re focusing on clean trend signals or detailed boundary interactions, this tool adapts to your style.
Fibonacci Volume Profiles [AlgoAlpha]Unlock a deeper understanding of price action with the Fibonacci Volume Profiles indicator by AlgoAlpha! This powerful tool blends Fibonacci retracement levels with customizable volume profiles, helping traders identify high-probability areas of support, resistance, and accumulation. Designed for both continuous dynamic levels and custom time periods, this indicator is a must-have for traders seeking confluence in market structure analysis.
🔑 Key Features
📈 Dual Mode Selection : Choose between Continuous Fibonacci levels, which adapt dynamically to pivots, or a Custom Period mode, where you set your own start and end points.
📊 Integrated Volume Profile : Visualize volume distributions at key Fibonacci retracement levels, revealing areas of strong buying/selling interest.
🎨 Customizable Colors & Transparency : Adjust Fibonacci level colors, fill zones, and profile transparency for a visually clear experience.
🔍 Profile Resolution & Scaling : Control the number of price levels and width of the volume profile for detailed market insights.
🛠 Extendable Levels : Optionally extend Fibonacci levels to the right of the chart for better visualization of future price interaction.
📌 How to Use
Add the Indicator: Click on the star icon to add it to your favorites and apply it to your TradingView chart.
Analyze The Market: Observe how price interacts with Fibonacci levels alongside the volume profile to confirm support/resistance zones. Switch between custom range or continuous mode to align the tool with your trading style.
⚙️ How It Works
The indicator calculates pivot highs/lows dynamically (or uses user-defined time periods) to plot Fibonacci retracement levels. It then builds a volume profile by analyzing historical volume data, grouping it into price bins to highlight volume-heavy zones. The Point of Control (PoC) is identified as the level with the highest traded volume, acting as a key price magnet. The color-coded Fibonacci levels help traders spot retracement zones, while the volume profile confirms strength or weakness in those areas.
AE - ATR Exhaustion ChannelAE - ATR Exhaustion Channel
📈 Overview
Identify Exhaustion Zones & Trend Breakouts with ATR Precision!
The AE - ATR Exhaustion Channel is a powerful volatility-based trading tool that combines an averaged SMA with ATR bands to dynamically highlight potential trend exhaustion zones. It provides real-time breakout detection by marking when price moves beyond key volatility bands, helping traders spot overextensions and reversals with ease.
🔑 Key Features
✔️ ATR-SMA Hybrid Channel: Uses an averaged SMA as the core trend filter while incorporating adaptive ATR-based bands for precise volatility tracking.
✔️ Dynamic Exhaustion Markers: Marks red crosses when price exceeds the upper band and green crosses when price drops below the lower band.
✔️ Customizable ATR Sensitivity: Adjust the ATR multiplier and length settings to fine-tune band sensitivity based on market conditions.
✔️ Clear Channel Visualization: A gray SMA midpoint and a blue-filled ATR band zone make it easy to track market structure.
📚 How It Works
1️⃣ Averaged SMA Calculation: The script calculates an averaged SMA over a user-defined range (min/max period). This smooths out short-term fluctuations while preserving trend direction.
2️⃣ ATR Band Construction: The ATR value (adjusted by a multiplier) is added to/subtracted from the SMA to form dynamic upper and lower volatility bands.
3️⃣ Exhaustion Detection:
If high > upper ATR band, a red cross is plotted (potential overextension).
If low < lower ATR band, a green cross is plotted (potential reversal zone).
4️⃣ Filled ATR Channel: The area between the upper and lower bands is shaded blue, providing a visual trading range.
🎨 Customization & Settings
⚙️ ATR Length – Adjusts the ATR calculation period (default: 14).
⚙️ ATR Multiplier – Scales the ATR bands for tighter or wider volatility tracking (default: 0.8, adjustable in 0.1 steps).
⚙️ SMA Range (Min/Max Length) – Defines the period range for calculating the averaged SMA (default: 5-20).
⚙️ Rolling Lookback Length – Controls how far back the high/low comparison is calculated (default: 50 bars).
🚀 Practical Usage
📌 Spotting Exhaustion Zones – Look for red/green markers appearing outside the ATR bands, signaling potential trend exhaustion and possible reversal opportunities.
📌 Breakout Confirmation – Price consistently breaching the upper band with momentum could indicate continuation, while repeated touches without strong closes may hint at reversal zones.
📌 Trend Reversal Signals – Watch for green markers below the lower band in uptrends (buy signals) and red markers above the upper band in downtrends (sell signals).
🔔 Alerts & Notifications
📢 Set Alerts for Exhaustion Signals!
Traders can configure alerts to trigger when price breaches the ATR bands, allowing for instant notifications when volatility-based exhaustion is detected.
📊 Example Scenarios
✔ Trend Exhaustion in Overextended Moves – A series of red crosses near resistance may indicate a short opportunity.
✔ Trend Exhaustion in Overextended Moves – A series of red crosses near resistance may indicate an opportunity to open a short trade.
✔ Volatility Compression Breakouts – If price consolidates within the ATR bands and suddenly breaks out, it could signify a momentum shift.
✔ Reversal Catching in Trending Markets – Spot potential trend reversals by looking for green markers below the ATR bands in bullish markets.
🌟 Why Choose AE - ATR Exhaustion Channel?
Trade with Confidence. Spot Volatility. Catch Breakouts.
The AE - ATR Exhaustion Channel is an essential tool for traders looking to identify trend exhaustion, detect breakouts, and manage volatility effectively. Whether you're trading stocks, crypto, or forex, this ATR-SMA hybrid system provides clear visual cues to help you stay ahead of market moves.
✅ Customizable to Fit Any Market
✅ Combines Volatility & Trend Analysis
✅ Easy-to-Use with Instant Breakout Detection
Adaptive Resonance Oscillator [AlgoAlpha]Introducing the Adaptive Resonance Oscillator , an advanced momentum-based oscillator designed to dynamically adjust to changing market conditions. This innovative indicator detects market frequency through a Hilbert Transform approach, adapting in real-time to identify overbought and oversold conditions with improved accuracy. With built-in divergence detection, trend analysis, and customizable smoothing, this tool is perfect for traders looking to refine their entries and exits based on adaptive oscillation mechanics.
🚀 Key Features :
🔹 Adaptive Frequency Detection – Uses Hilbert Transform principles to dynamically determine market cycle length for precise oscillator calculation.
⚙️ Customizable Smoothing – Option to apply a Hull Moving Average (HMA) for enhanced signal clarity.
📈 Divergence Detection – Identifies bullish and bearish divergences with visual markers, helping traders spot early trend reversals.
🟢 Overbought & Oversold Signals – Highlights extreme momentum conditions with adjustable thresholds.
🔔 Real-Time Alerts – Get notified for crossovers, divergences, and strong trend shifts directly on your TradingView chart.
🎨 Fully Customizable Appearance – Modify colors, divergence sensitivity, and smoothing options to fit your trading style.
🛠 How to Use :
Add the Adaptive Resonance Oscillator to your TradingView chart by clicking the ★ to favorite it.
Monitor the Charts , switch between smoothed and I smoothed modes to identify trend and price swings, use divergences and reversal signals for potential entry/exits.
Set alerts for bullish/bearish crossovers and divergence signals to stay ahead of market moves.
⚙ How It Works :
The indicator begins by applying a Hilbert Transform frequency estimation to the price series, identifying the dominant market cycle length. This is used to calculate a period for the RSI that matches its resonant frequency with the dominant market frequency, dynamically adjusting the Oscillator. The oscillator then applies an optional Hull Moving Average (HMA) smoothing for signal refinement. Additionally, the indicator scans for bullish and bearish divergences by comparing oscillator movements against price action, plotting signals accordingly. When overbought/oversold conditions or divergence events occur, alerts are triggered to notify the trader in real time.
Overextension Oscillator [by DanielM]The Overextension Oscillator is an indicator that detects when a market move has extended significantly beyond its typical range, signaling potential areas for a correction or reversal. Unlike traditional oscillators that rely on fixed overbought/oversold levels, this tool dynamically adjusts its thresholds based on historical swing high and swing low movements.
By analyzing all swing points on the chart, the indicator determines the expected range of price movements and identifies when the price extends beyond normal levels. Since every asset has different price behavior and volatility, swing lengths may vary from asset to asset, ensuring that overextension is measured relative to each market's historical price behavior.
How It Works
1️⃣ Swing Detection & Data Collection
The indicator scans all available swing highs and swing lows on the chart to gather a complete dataset of past price fluctuations.
It records the percentage differences between swings to determine how much price typically moves in a given market.
2️⃣ Overextension Calculation
Using the stored swing data, the indicator calculates:
Average Swing Difference – Measures the average percentage difference between swings.
Average Move Percentage – Determines the typical magnitude of price moves within a trend cycle.
These values are used to create dynamic overextension thresholds that adjust based on historical data.
3️⃣ Price Distance & Overextension Measurement
The indicator calculates the distance between the current price and the closest historical swing point. If this distance exceeds the predefined threshold based on past swings, the move is considered overextended. The greater the deviation, the higher the probability of a pullback or short-term reversal.
4️⃣ Buy/Sell Signal Generation
A Buy signal is generated when the price has dropped below an overextended threshold relative to a past swing low.
A Sell signal is generated when the price has risen beyond an overextended threshold relative to a past swing high.
These signals indicate that the price has reached a level where it historically tends to slow down or reverse.
Two-Pole Oscillator [BigBeluga]
The Two-Pole Oscillator is an advanced smoothing oscillator designed to provide traders with precise market signals by leveraging deviation-based calculations combined with a unique two-pole filtering technique. It offers clear visual representation and actionable signals for smart trading decisions.
🔵Key Features:
Two-Pole Filtering: Smooths out the main oscillator signal to reduce noise, providing a cleaner and more reliable view of market momentum and trend strength.
// Two-pole smooth filter function
f_two_pole_filter(source, length) =>
var float smooth1 = na
var float smooth2 = na
alpha = 2.0 / (length + 1)
if na(smooth1)
smooth1 := source
else
smooth1 := (1 - alpha) * smooth1 + alpha * source
if na(smooth2)
smooth2 := smooth1
else
smooth2 := (1 - alpha) * smooth2 + alpha * smooth1
Deviation-Based Oscillator: Utilizes price deviations from the mean to generate dynamic signals, making it ideal for detecting overbought and oversold conditions.
float sma1 = ta.sma(close, 25)
float sma_n1 = ((close - sma1) - ta.sma(close - sma1, 25)) / ta.stdev(close - sma1, 25)
Signal Gradient Strength: Signals on the main oscillator line feature gradient coloring based on their proximity to the 0 level:
➔ Closer to 0: More transparent, indicating weaker signals.
➔ Closer to 1 or -1: Less transparent, highlighting stronger signals.
Level-Based Signal Validation: Parallel levels are plotted on the chart for each signal:
➔ If a level is crossed by price, the signal is invalidated, marked by an "X" at the invalidation point.
Trend Continuation
Invalidation Levels: Serve as potential stop-loss or trade-reversal zones, enabling traders to make more informed and disciplined trading decisions.
Dynamic Chart Plotting: Signals are plotted directly on the chart with corresponding levels, providing a comprehensive visual representation for easy interpretation.
🔵How It Works:
The oscillator calculates price deviation from a mean value and applies two-pole filtering to smooth the resulting signal.
Gradient-colored signals reflect their strength, with transparency indicating proximity to the 0 level on the oscillator scale.
Buy and sell signals are generated based on crossovers and crossunders of the oscillator line with a signal line.
If a level is crossed, the corresponding signal is marked with a "X" plotted on the chart at the crossover point.
🔵Use Cases:
Detecting overbought or oversold market conditions with a smoother, noise-free oscillator.
Using invalidation levels to set clear stop-loss or trade exit points.
Identifying strong momentum signals and filtering out weaker, less reliable ones.
Combining oscillator signals with price action for more precise trade entries and exits.
This indicator is perfect for traders seeking a refined approach to oscillator analysis, combining signal strength visualization with actionable invalidation levels to enhance trading precision and strategy.
Bearish Wick Reversal█ STRATEGY OVERVIEW
The "Bearish Wick Reversal Strategy" identifies potential bullish reversals following significant bearish price rejection (long lower wicks). This counter-trend approach enters long positions when bearish candles show exaggerated downside wicks relative to closing prices, then exits on bullish confirmation signals. Includes optional EMA trend filtering for improved reliability.
█ What is a Bearish Wick?
A price rejection pattern where:
Bearish candle (close < open) forms with extended lower wick
Wick represents failed selloff: Low drops significantly below close
Measured as: (Low - Close)/Close × 100 (Negative percentage indicates downward extension)
█ SIGNAL GENERATION
1. LONG ENTRY CONDITION
Bearish candle forms with close < open
Lower wick exceeds user-defined threshold (Default: -1% of close price)
The signal occurs within the specified time window
If enabled, the close price must also be above the 200-period EMA (Exponential Moving Average)
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the highest high of the previous seven bars (`close > _highest `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ PERFORMANCE OVERVIEW
Ideal Market: Volatile instruments with frequent price rejections
Key Risk: False signals in sustained bearish trends
Optimization Tip: Test various thresholds
Filter Impact: EMA reduces trades but improves win rate and reduces drawdown
Gap Down Reversal Strategy█ STRATEGY OVERVIEW
The "Gap Down Reversal Strategy" capitalizes on price recovery patterns following bearish gap-down openings. This mean-reversion approach enters long positions on confirmed intraday recoveries and exits when prices breach previous session highs. This strategy is NOT optimized.
█ What is a Gap Down Reversal?
A gap down reversal occurs when:
An instrument opens significantly below its prior session's low (price gap)
Selling pressure exhausts itself during the session
Buyers regain control, pushing price back above the opening level
Creates a candlestick with:
• Open < Prior Session Low (true gap)
• Close > Open (bullish reversal candle)
█ SIGNAL GENERATION
1. LONG ENTRY CONDITION
Previous candle closes BELOW its opening price (bearish candle)
Current session opens BELOW prior candle's low (gap down)
Current candle closes ABOVE its opening price (bullish reversal)
Executes market order at session close
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the highest high of the previous seven bars (`close > _highest `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ PERFORMANCE OVERVIEW
Ideal Market: High volatility instruments with frequent gaps
Key Risk: False reversals in sustained downtrends
Optimization Tip: Test varying gap thresholds (1-3% ranges)
3 Down, 3 Up Strategy█ STRATEGY DESCRIPTION
The "3 Down, 3 Up Strategy" is a mean-reversion strategy designed to capitalize on short-term price reversals. It enters a long position after consecutive bearish closes and exits after consecutive bullish closes. This strategy is NOT optimized and can be used on any timeframes.
█ WHAT ARE CONSECUTIVE DOWN/UP CLOSES?
- Consecutive Down Closes: A sequence of trading bars where each close is lower than the previous close.
- Consecutive Up Closes: A sequence of trading bars where each close is higher than the previous close.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The price closes lower than the previous close for Consecutive Down Closes for Entry (default: 3) consecutive bars.
The signal occurs within the specified time window (between Start Time and End Time).
If enabled, the close price must also be above the 200-period EMA (Exponential Moving Average).
2. EXIT CONDITION
A Sell Signal is generated when the price closes higher than the previous close for Consecutive Up Closes for Exit (default: 3) consecutive bars.
█ ADDITIONAL SETTINGS
Consecutive Down Closes for Entry: Number of consecutive lower closes required to trigger a buy. Default = 3.
Consecutive Up Closes for Exit: Number of consecutive higher closes required to exit. Default = 3.
EMA Filter: Optional 200-period EMA filter to confirm long entries in bullish trends. Default = disabled.
Start Time and End Time: Restrict trading to specific dates (default: 2014-2099).
█ PERFORMANCE OVERVIEW
Designed for volatile markets with frequent short-term reversals.
Performs best when price oscillates between clear support/resistance levels.
The EMA filter improves reliability in trending markets but may reduce trade frequency.
Backtest to optimize consecutive close thresholds and EMA period for specific instruments.
RSI OB/OS Strategy Analyzer█ OVERVIEW
The RSI OB/OS Strategy Analyzer is a comprehensive trading tool designed to help traders identify and evaluate overbought/oversold reversal opportunities using the Relative Strength Index (RSI). It provides visual signals, performance metrics, and a detailed table to analyze the effectiveness of RSI-based strategies over a user-defined lookback period.
█ KEY FEATURES
RSI Calculation
Calculates RSI with customizable period (default 14)
Plots dynamic overbought (70) and oversold (30) levels
Adds background coloring for OB/OS regions
Reversal Signals
Identifies signals based on RSI crossing OB/OS levels
Two entry strategies available:
Revert Cross: Triggers when RSI exits OB/OS zone
Cross Threshold: Triggers when RSI enters OB/OS zone
Trade Direction
Users can select a trade bias:
Long: Focuses on oversold reversals (bullish signals)
Short: Focuses on overbought reversals (bearish signals)
Performance Metrics
Calculates three key statistics for each lookback period:
Win Rate: Percentage of profitable trades
Mean Return: Average return across all trades
Median Return: Median return across all trades
Metrics calculated as percentage changes from entry price
Visual Signals
Dual-layer signal display:
BUY: Green triangles + text labels below price
SELL: Red triangles + text labels above price
Semi-transparent background highlighting in OB/OS zones
Performance Table
Interactive table showing metrics for each lookback period
Color-coded visualization:
Win Rate: Gradient from red (low) to green (high)
Returns: Green for positive, red for negative
Time Filtering
Users can define a specific time window for the indicator to analyze trades, ensuring that performance metrics are calculated only for the desired period.
Customizable Display
Adjustable table font sizes: Auto/Small/Normal/Large
Toggle option for table visibility
█ PURPOSE
The RSI OB/OS Strategy Analyzer helps traders:
Identify mean-reversion opportunities through RSI extremes
Backtest entry strategy effectiveness across multiple time horizons
Optimize trade timing through visual historical performance data
Quickly assess strategy robustness with color-coded metrics
█ IDEAL USERS
Counter-Trend Traders: Looking to capitalize on RSI extremes
Systematic Traders: Needing quantitative strategy validation
Educational Users: Studying RSI behavior in different market conditions
Multi-Timeframe Analysts: Interested in forward returns analysis
Internal Bar Strength (IBS) Strategy█ STRATEGY DESCRIPTION
The "Internal Bar Strength (IBS) Strategy" is a mean-reversion strategy designed to identify trading opportunities based on the closing price's position within the daily price range. It enters a long position when the IBS indicates oversold conditions and exits when the IBS reaches overbought levels. This strategy was designed to be used on the daily timeframe.
█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) measures where the closing price falls within the high-low range of a bar. It is calculated as:
IBS = (Close - Low) / (High - Low)
- **Low IBS (≤ 0.2)**: Indicates the close is near the bar's low, suggesting oversold conditions.
- **High IBS (≥ 0.8)**: Indicates the close is near the bar's high, suggesting overbought conditions.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The IBS value drops below the Lower Threshold (default: 0.2).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
A Sell Signal is generated when the IBS value rises to or above the Upper Threshold (default: 0.8). This prompts the strategy to exit the position.
█ ADDITIONAL SETTINGS
Upper Threshold: The IBS level at which the strategy exits trades. Default is 0.8.
Lower Threshold: The IBS level at which the strategy enters long positions. Default is 0.2.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for ranging markets and performs best when prices frequently revert to the mean.
It is sensitive to extreme IBS values, which help identify potential reversals.
Backtesting results should be analyzed to optimize the Upper/Lower Thresholds for specific instruments and market conditions.
Bollinger Bands Reversal Strategy Analyzer█ OVERVIEW
The Bollinger Bands Reversal Overlay is a versatile trading tool designed to help traders identify potential reversal opportunities using Bollinger Bands. It provides visual signals, performance metrics, and a detailed table to analyze the effectiveness of reversal-based strategies over a user-defined lookback period.
█ KEY FEATURES
Bollinger Bands Calculation
The indicator calculates the standard Bollinger Bands, consisting of:
A middle band (basis) as the Simple Moving Average (SMA) of the closing price.
An upper band as the basis plus a multiple of the standard deviation.
A lower band as the basis minus a multiple of the standard deviation.
Users can customize the length of the Bollinger Bands and the multiplier for the standard deviation.
Reversal Signals
The indicator identifies potential reversal signals based on the interaction between the price and the Bollinger Bands.
Two entry strategies are available:
Revert Cross: Waits for the price to close back above the lower band (for longs) or below the upper band (for shorts) after crossing it.
Cross Threshold: Triggers a signal as soon as the price crosses the lower band (for longs) or the upper band (for shorts).
Trade Direction
Users can select a trade bias:
Long: Focuses on bullish reversal signals.
Short: Focuses on bearish reversal signals.
Performance Metrics
The indicator calculates and displays the performance of trades over a user-defined lookback period ( barLookback ).
Metrics include:
Win Rate: The percentage of trades that were profitable.
Mean Return: The average return across all trades.
Median Return: The median return across all trades.
These metrics are calculated for each bar in the lookback period, providing insights into the strategy's performance over time.
Visual Signals
The indicator plots buy and sell signals on the chart:
Buy Signals: Displayed as green triangles below the price bars.
Sell Signals: Displayed as red triangles above the price bars.
Performance Table
A customizable table is displayed on the chart, showing the performance metrics for each bar in the lookback period.
The table includes:
Win Rate: Highlighted with gradient colors (green for high win rates, red for low win rates).
Mean Return: Colored based on profitability (green for positive returns, red for negative returns).
Median Return: Colored similarly to the mean return.
Time Filtering
Users can define a specific time window for the indicator to analyze trades, ensuring that performance metrics are calculated only for the desired period.
Customizable Display
The table's font size can be adjusted to suit the user's preference, with options for "Auto," "Small," "Normal," and "Large."
█ PURPOSE
The Bollinger Bands Reversal Overlay is designed to:
Help traders identify high-probability reversal opportunities using Bollinger Bands.
Provide actionable insights into the performance of reversal-based strategies.
Enable users to backtest and optimize their trading strategies by analyzing historical performance metrics.
█ IDEAL USERS
Swing Traders: Looking for reversal opportunities within a trend.
Mean Reversion Traders: Interested in trading price reversals to the mean.
Strategy Developers: Seeking to backtest and refine Bollinger Bands-based strategies.
Performance Analysts: Wanting to evaluate the effectiveness of reversal signals over time.
Buy on 5 day low Strategy█ STRATEGY DESCRIPTION
The "Buy on 5 Day Low Strategy" is a mean-reversion strategy designed to identify potential buying opportunities when the price drops below the lowest low of the previous five days. It enters a long position when specific conditions are met and exits when the price exceeds the high of the previous day. This strategy is optimized for use on daily or higher timeframes.
█ WHAT IS THE 5-DAY LOW?
The 5-Day Low is the lowest price observed over the last five days. This level is used as a reference to identify potential oversold conditions and reversal points.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The close price is below the lowest low of the previous five days (`close < _lowest `).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the high of the previous day (`close > high `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for mean-reverting markets and performs best when the price frequently oscillates around key support levels.
It is sensitive to oversold conditions, as indicated by the 5-Day Low, and overbought conditions, as indicated by the previous day's high.
Backtesting results should be analyzed to optimize the strategy for specific instruments and market conditions.