[GrandAlgo] Moving Averages Cross LevelsMoving Averages Cross Levels
Many traders watch for moving average crossovers – such as the golden cross (50 MA crossing above 200 MA) or death cross – as signals of changing trends. However, once a crossover happens, the exact price level where it occurred often fades from view, even though that level can be an important reference point. Moving Averages Cross Levels is an indicator that keeps those crossover price levels visible on your chart, helping you track where momentum shifts occurred and how price behaves relative to those key levels.
This tool plots horizontal line segments at the price where each pair of selected moving averages crossed within a recent window of bars. Each level is labeled with the moving average lengths (for example, “21×50” for a 21/50 MA cross) and is color-coded – green for bullish crossovers (short-term MA crossing above long-term MA) and red for bearish crossunders (short-term crossing below). By visualizing these crossover levels, you can quickly identify past trend change points and use them as potential support/resistance or decision levels in your trading. Importantly, this indicator is non-repainting – once a crossover level is plotted, it remains fixed at the historical price where the cross occurred, allowing you to continually monitor that level going forward. (As with any moving average-based analysis, crossover signals are lagging, so use these levels in conjunction with other tools for confirmation.)
Key Features:
✅ Multiple Moving Averages: Track up to 7 different MAs (e.g. 5, 8, 21, 50, 64, 83, 200 by default) simultaneously. You can enable/disable each MA and set its length, allowing flexible combinations of short-term and long-term averages.
✅ Selectable MA Type: Each average can be calculated as a Simple (SMA), Exponential (EMA), Volume-Weighted (VWMA), or Smoothed (RMA) moving average, giving you flexibility to match your preferred method.
✅ Auto Crossover Detection: The script automatically detects all crosses between any enabled MA pairs, so you don’t have to specify pairs manually. Whether it’s a fast cross (5×8) or a long-term cross (50×200), every crossover within the lookback period will be identified and marked.
✅ Horizontal Level Markers: For each detected crossover, a horizontal line segment is drawn at the exact price where the crossover occurred. This makes it easy to glance at your chart and see precisely where two moving averages intersected in the recent past.
✅ Labeled and Color-Coded: Each crossover line is labeled with the two MA lengths that crossed (e.g. “50×200”) for clear identification. Colors indicate crossover direction – by default green for bullish (positive) crossovers and red for bearish (negative) crossovers – so you can tell at a glance which way the trend shifted. (You can customize these colors in the settings.)
✅ Adjustable Lookback: A “Crosses with X candles” input lets you control how far back the script looks for crossovers to plot. This prevents your chart from getting cluttered with too many old levels – for example, set X = 100 to show crossovers from roughly the last 100 bars. Older crossover lines beyond this lookback window will automatically clear off the chart.
✅ Optional MA Plots: You can toggle the display of each moving average line on the chart. This means you can either view just the crossover levels alone for a clean look, or also overlay the MA curves themselves for additional context (to see how price and MAs were moving around the crossover).
✅ No Repainting or Hindsight Bias: Once a crossover level is plotted, it stays at that fixed price. The indicator doesn’t move levels around after the fact – each line is a true historical event marker. This allows you to backtest visually: see how price acted after the crossover by observing if it retested or respected that level later.
How It Works:
1️⃣ Add to Chart & Configure – Simply add the indicator to your chart. In the settings, choose which moving averages you want to include and set their lengths. For example, you might enable 21, 50, 200 to focus on medium and long-term crosses (including the golden cross), or turn on shorter MAs like 5 and 8 for quick momentum shifts. Adjust the lookback (number of bars to scan for crosses) if needed.
2️⃣ Visualization – The script continuously checks the latest X bars for any points where one MA crossed above or below another. Whenever a crossover is found, it calculates the exact price level at which the two moving averages intersected. On the last bar of your chart, it will draw a horizontal line segment extending from the crossover bar to the current bar at that price level, and place a label to the right of the line with the MA lengths. Green lines/labels signify bullish crossovers (where the first MA crossed above the second), and red lines indicate bearish crossunders.
3️⃣ On Your Chart – You will see these labeled levels aligned with the price scale. For example, if a 50 MA crossed above a 200 MA (bullish) 50 bars ago at price $100, there will be a green “50×200” line at $100 extending to the present, showing you exactly where that golden cross happened. You might notice price pulling back near that level and bouncing, or if price falls back through it, it could signal a failed crossover. The indicator updates in real-time: if a new crossover happens on the latest bar, a new line and label will instantly appear, and if any old cross moves out of the lookback range, its line is removed to keep the chart focused.
4️⃣ Customization – You can fine-tune the appearance: toggle any MA’s visibility, change line colors or label styles, and modify the lookback length to suit different timeframes. For instance, on a 1-hour chart you might use a lookback of 500 bars to see a few weeks of cross history, whereas on a daily chart 100 bars (about 4–5 months) may be sufficient. Adjust these settings based on how many crossover levels you find useful to display.
Ideal for Traders Who:
Use MA Crossovers in Strategy: If your strategy involves moving average crossovers (for trend confirmation or entry/exit signals), this indicator provides an extra layer of insight by keeping the price of those crossover events in sight. For example, trend-followers can watch if price stays above a bullish crossover level as a sign of trend strength, or falls below it as a sign of weakness.
Identify Support/Resistance from MA Events: Crossover levels often coincide with pivot points in market sentiment. A crossover can act like a regime change – the level where it happened may turn into support or resistance. This tool helps you mark those potential S/R levels automatically. Rather than manually noting where a golden cross occurred, you’ll have it highlighted, which can be useful for setting stop-losses (e.g. below the crossover price in a bullish scenario) or profit targets.
Track Multiple Averages at Once: Instead of focusing on just one pair of moving averages, you might be interested in the interaction of several (short, medium, and long-term trends). This indicator caters to that by plotting all relevant crossovers among your chosen MAs. It’s great for multi-timeframe thinkers as well – e.g. you could apply it on a higher timeframe chart to mark major cross levels, then drill down to lower timeframes knowing those key prices.
Value Clean Visualization: There are no flashing signals or arrows – just simple lines and labels that enhance your chart’s storytelling. It’s ideal if you prefer to make trading decisions based on understanding price interaction with technical levels rather than following automatic trade calls. Moving Averages Cross Levels gives you information to act on, without imposing any bias or strategy – you interpret the crossover levels in the context of your own trading system.
Moving_average
HawkEye EMA Cloud
# HawkEye EMA Cloud - Enhanced Multi-Timeframe EMA Analysis
## Overview
The HawkEye EMA Cloud is an advanced technical analysis indicator that visualizes multiple Exponential Moving Average (EMA) relationships through dynamic color-coded cloud formations. This enhanced version builds upon the original Ripster EMA Clouds concept with full customization capabilities.
## Credits
**Original Author:** Ripster47 (Ripster EMA Clouds)
**Enhanced Version:** HawkEye EMA Cloud with advanced customization features
## Key Features
### 🎨 **Full Color Customization**
- Individual bullish and bearish colors for each of the 5 EMA clouds
- Customizable rising and falling colors for EMA lines
- Adjustable opacity levels (0-100%) for each cloud independently
### 📊 **Multi-Layer EMA Analysis**
- **5 Configurable EMA Cloud Pairs:**
- Cloud 1: 8/9 EMAs (default)
- Cloud 2: 5/12 EMAs (default)
- Cloud 3: 34/50 EMAs (default)
- Cloud 4: 72/89 EMAs (default)
- Cloud 5: 180/200 EMAs (default)
### ⚙️ **Advanced Customization Options**
- Toggle individual clouds on/off
- Adjustable EMA periods for all timeframes
- Optional EMA line display with color coding
- Leading period offset for cloud projection
- Choice between EMA and SMA calculations
- Configurable source data (HL2, Close, Open, etc.)
## How It Works
### Cloud Formation
Each cloud is formed by the area between two EMAs of different periods. The cloud color dynamically changes based on:
- **Bullish (Green/Custom):** When the shorter EMA is above the longer EMA
- **Bearish (Red/Custom):** When the shorter EMA is below the longer EMA
### Multiple Timeframe Analysis
The indicator provides a comprehensive view of trend strength across multiple timeframes:
- **Short-term:** Clouds 1-2 (faster EMAs)
- **Medium-term:** Cloud 3 (intermediate EMAs)
- **Long-term:** Clouds 4-5 (slower EMAs)
## Trading Applications
### Trend Identification
- **Strong Uptrend:** Multiple clouds stacked bullishly with price above
- **Strong Downtrend:** Multiple clouds stacked bearishly with price below
- **Consolidation:** Mixed cloud colors indicating sideways movement
### Entry Signals
- **Bullish Entry:** Price breaking above bearish clouds turning bullish
- **Bearish Entry:** Price breaking below bullish clouds turning bearish
- **Confluence:** Multiple cloud confirmations strengthen signal reliability
### Support/Resistance Levels
- Cloud boundaries often act as dynamic support and resistance
- Thicker clouds (higher opacity) may provide stronger S/R levels
- Multiple cloud intersections create significant price levels
## Customization Guide
### Color Schemes
Create your own visual style by customizing:
1. **Bullish/Bearish colors** for each cloud pair
2. **Rising/Falling colors** for EMA lines
3. **Opacity levels** to layer clouds effectively
### Recommended Settings
- **Day Trading:** Focus on Clouds 1-2 with higher opacity
- **Swing Trading:** Use Clouds 1-3 with moderate opacity
- **Position Trading:** Emphasize Clouds 3-5 with lower opacity
## Technical Specifications
- **Version:** Pine Script v6
- **Type:** Overlay indicator
- **Calculations:** Real-time EMA computations
- **Performance:** Optimized for all timeframes
- **Alerts:** Configurable long/short alerts available
## Risk Disclaimer
This indicator is for educational and informational purposes only. Always combine with proper risk management and additional analysis before making trading decisions. Past performance does not guarantee future results.
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*Enhanced and customized version of the original Ripster EMA Clouds by Ripster47. This modification adds comprehensive color customization and enhanced user control while preserving the core analytical framework.*
KAMA Trend Flip with Snap & Follow - SightLing Labs🔭 OVERVIEW
KAMA Snap Follow is a customized adaptation of the Kaufman Adaptive Moving Average (KAMA) that overlays a trend-tracking line on the chart. It computes an adaptive smoothing constant from the efficiency ratio, then incorporates conditional enhancements: a "snap" mechanism to boost responsiveness on significant counter-trend bars surpassing an ATR-based threshold, and a temporary "follow" mode after trend flips to intensify adaptation for a user-defined number of bars. This allows the line to hug price more closely during early reversal phases before returning to standard smoothing for noise filtration. The line colors green for upward trends (rising KAMA), red for downward (falling KAMA), and gray for neutral, with optional alerts on trend changes. If the structure invalidates (e.g., via excessive lag or unconfirmed flips), no automatic cleanup occurs—users manage via settings tweaks and backtesting.
🔭 CONCEPTS
* Adaptive smoothing core: Builds on KAMA's efficiency ratio to dynamically adjust between fast and slow constants, gliding over minor volatility while aiming to react to directional shifts.
* Snap trigger: Detects potential reversals via large bar changes opposing the prior trend, exceeding a multiplier of ATR; this temporarily amplifies the smoothing constant (capped at 1.0) to pull KAMA toward price.
* Follow mode activation: Post-flip, engages a boosted adaptation phase for a fixed bar count, forcing tighter shadowing in the new direction to reduce lag on true turns, then reverts to absorber mode.
* Trend detection: Simple comparison of current vs. prior KAMA values defines up/down/neutral, with no embedded signals—purely for visual trend context.
* Risk-aware design: No guarantees; focuses on lag reduction in simulations (e.g., 38-54% trough lag cuts on synthetic volatile series), but real-market performance varies—backtest thoroughly.
🔭 FEATURES
* Custom KAMA calculation with manual efficiency ratio and smoothing powers for baseline adaptation.
* ATR-integrated snap for reversal sensitivity, with adjustable multiplier and boost.
* Post-flip follow mode with configurable period and boost to enhance new-trend hugging.
* Trend coloring and flip alerts: Green/red/gray line with conditions for up/down/neutral; alerts on changes.
* User controls:
Source (e.g., close).
Efficiency Ratio Length (pivot-like sensitivity).
Fast/Slow Powers (adaptation speed).
ATR Length (volatility measure).
Snap Multiplier/Boost (reversal threshold/amplification).
Follow Period/Boost (post-flip duration/intensity).
* Efficient execution: Lightweight, no heavy buffers—suitable for intraday charts via backtested tweaks.
🔭 HOW TO USE
* Tune sensitivity: Shorten Efficiency Ratio Length on lower timeframes for quicker reactions; lengthen on higher for smoother trends. Test ATR Length against asset volatility.
* Monitor flips: Use green/red shifts as trend context—combine with your strategy (e.g., crossovers, support/resistance) for potential entries; alerts notify changes.
* Leverage modes: Snap helps catch sharp turns; follow mode tightens tracking post-reversal—observe on historical data to gauge lag reduction (e.g., 30-57% miss cuts on 0.20 moves in tests).
* Apply MTF: Spot broader trends on 5m; refine on 30s/1m near flips. Backtest configurations to avoid over-optimization.
* Integrate confluence: Pair with volume, RSI, or your filters; never rely solely—markets evolve, so validate via simulations and live observation.
🔭 CONCLUSION
KAMA Snap Follow evolves standard KAMA by adding snap and follow mechanics to combat reversal lag while filtering bumps, offering a visual tool for trend analysis in volatile intraday setups. Developed to address traditional adaptive averages' delays without introducing excessive whipsaw (e.g., zero added in noisy flats per tests), it provides adjustable parameters for customization. No performance promises—results hinge on backtesting and market fit; use as a framework for scenario evaluation, not automated trading.
Example Configurations (derived from synthetic tests on SOFI-like intraday volatility; backtest and adjust):
- For 30s charts (high noise, rapid shifts): Efficiency Ratio Length=20, Fast Power=1, Slow Power=15, ATR Length=10, Snap Multiplier=1.2, Snap Boost=2.0, Follow Period=5, Follow Boost=2.5—yields ~40% lag reduction on turns, filtering 85% of <0.01 fluctuations.
- For 1m charts (moderate volatility): Efficiency Ratio Length=30, Fast Power=2, Slow Power=20, ATR Length=14, Snap Multiplier=1.5, Snap Boost=2.5, Follow Period=8, Follow Boost=3.0—achieves ~30% lower reversal misses (e.g., 0.08 vs. 0.12 on 0.20 swings), stable in 50-bar chops.
- For 5m charts (trendier flows): Efficiency Ratio Length=50, Fast Power=3, Slow Power=40, ATR Length=20, Snap Multiplier=1.8, Snap Boost=3.0, Follow Period=12, Follow Boost=3.5—boosts post-flip hug by 25%, ignoring 90% of ±0.05 noise across 100 bars.
ConeWave MACoRa Wave is a custom-weighted moving average designed to adapt intelligently to market dynamics. It builds upon the foundational logic of the Comp_Ratio_MA by @redktrader, incorporating a compound ratio-based weighting curve that emphasizes recent price action while preserving smoothness and structure with pinescript version 6.
This version introduces modular enhancements, including:
A Comp Ratio Multiplier for fine-tuned responsiveness
Optional Auto Smoothing based on wave length
Streamlined plotting for clarity and performance
Whether you're confirming market structure, identifying trend shifts, or seeking a cleaner alternative to noisy indicators, CoRa Wave offers a visually intuitive and mathematically elegant solution.
🛠 Reimagined by @atulgalande75 — optimized for traders who value precision, adaptability, and clean charting. Original concept by @redktrader.
Moving Average Adaptive RSI [BackQuant]Moving Average Adaptive RSI
What this is
A momentum oscillator that reshapes classic RSI into a zero-centered column plot and makes it adaptive. It builds RSI from two parts:
• A sensitivity window that scans several recent bars to capture the strongest up and down impulses.
• A selectable moving average that smooths those impulses before computing RSI.
The output ranges roughly from −100 to +100 with 0 as the midline, with optional extra smoothing and built-in divergence detection.
How it works
Impulse extraction
• For each bar the script inspects the last rsi_sen bars and collects upward and downward price changes versus the current price.
• It keeps the maximum upward change and maximum downward change from that window, emphasizing true bursts over single-bar noise.
MA-based averaging
• The up and down impulse series are averaged with your chosen MA over rsi_len bars.
• Supported MA types: SMA, EMA, DEMA, WMA, HMA, SMMA (RMA), TEMA.
Zero-centered RSI transform
• RS = UpMA ÷ DownMA, then mapped to a symmetric scale: 100 − 200 ÷ (1 + RS) .
• Above 0 implies positive momentum bias. Below 0 implies negative momentum bias.
Optional extra smoothing
• A second smoothing pass can be applied to the final oscillator using smoothing_len and smooth_type . Toggle with “Use Extra Smoothing”.
Visual encoding
• The oscillator is drawn as columns around the zero line with a gradient that intensifies toward extremes.
• Static bands mark 80 to 100 and −80 to −100 for extreme conditions.
Key inputs and what they change
• Price Source : input series for momentum.
• Calculation Period (rsi_len) : primary averaging window on up and down components. Higher = smoother, slower.
• Sensitivity (rsi_sen) : how many recent bars are scanned to find max impulses. Higher = more responsive to bursts.
• Calculation Type (ma_type) : MA family that shapes the core behavior. HMA or DEMA is faster, SMA or SMMA is slower.
• Smoothing Type and Length : optional second pass to calm noise on the final output.
• UI toggles : show or hide the oscillator, candle painting, and extreme bands.
Reading the oscillator
• Midline cross up (0) : momentum bias turning positive.
• Midline cross down (0) : momentum bias turning negative.
• Positive territory :
– 0 to 40: constructive but not stretched.
– 40 to 80: strong momentum, continuation more likely.
– Above 80: extreme risk of mean reversion grows.
• Negative territory : mirror the same levels for the downside.
Divergence detection
The script plots four divergence types using pivot highs and lows on both price and the oscillator. Lookbacks are set by lbL and lbR .
• Regular bullish : price lower low, oscillator higher low. Possible downside exhaustion.
• Hidden bullish : price higher low, oscillator lower low. Bias to trend continuation up.
• Regular bearish : price higher high, oscillator lower high. Possible upside exhaustion.
• Hidden bearish : price lower high, oscillator higher high. Bias to trend continuation down.
Labels: ℝ for regular, ℍ for hidden. Green for bullish, red for bearish.
Candle coloring
• Optional bar painting: green when the oscillator is above 0, red when below 0. This is for visual scanning only.
Strengths
• Adaptive sensitivity via a rolling impulse window that responds to genuine bursts.
• Configurable MA core so you can match responsiveness to the instrument.
• Zero-centered scale for simple regime reads with 0 as a clear bias line.
• Built-in regular and hidden divergence mapping.
• Flexible across symbols and timeframes once tuned.
Limitations and cautions
• Trends can remain extended. Treat extremes as context rather than automatic reversal signals.
• Divergence quality depends on pivot lookbacks. Short lookbacks give more signals with more noise. Long lookbacks reduce noise but add lag.
• Double smoothing can delay zero-line transitions. Balance smoothness and timeliness.
Practical usage ideas
• Regime filter : only take long setups from your separate method when the oscillator is above 0, shorts when below 0.
• Pullback confirmation : in uptrends, look for dips that hold above 0 or turn up from 0 to 40. Reverse for downtrends.
• Divergence as a heads-up : wait for a zero-line cross or a price trigger before acting on divergence.
• Sensitivity tuning : start with rsi_sen 2 to 5 on faster timeframes, increase slightly on slower charts.
Alerts
• MA-A RSI Long : oscillator crosses above 0.
• MA-A RSI Short : oscillator crosses below 0.
Use these as bias or timing aids, not standalone trade commands.
Settings quick reference
• Calculation : Price Source, Calculation Type, Calculation Period, Sensitivity.
• Smoothing : Smoothing Type, Smoothing Length, Use Extra Smoothing.
• UI : Show Oscillator, Paint Candles, Show Static High and Low Levels.
• Divergences : Pivot Lookback Left and Right, Div Signal Length, Show Detected Divergences.
Final thoughts
This tool reframes RSI by extracting strong short-term impulses and averaging them with a moving-average model of your choice, then presenting a zero-centered output for clear regime reads. Pair it with your structure, risk and execution process, and tune sensitivity and smoothing to the market you trade.
KAMA Trend Flip - SightLing LabsBuckle up, traders—this open-source KAMA Trend Flip indicator is your ticket to sniping trend reversals with a Kaufman Adaptive Moving Average (KAMA) that’s sharper than a Wall Street shark’s tooth. No voodoo, no fluff—just raw, volatility-adaptive math that dances with the market’s rhythm. It zips through trending rockets and chills in choppy waters, slashing false signals like a samurai. Not laggy like the others - this thing is the real deal!
Core Mechanics:
• Efficiency Ratio (ER): Reads the market’s pulse (0-1). High ER = turbo-charged MA, low ER = smooth operator.
• Adaptive Smoothing: Mixes fast (default power 2) and slow (default 30) constants to match market mood swings.
• Trend Signals: KAMA climbs = blue uptrend (bulls run wild). KAMA dips = yellow downtrend (bears take over). Flat = gray snooze-fest.
• Alerts: Instant pings on flips—“Trend Flip Up” for long plays, “Down” for shorts. Plug into bots for set-and-forget domination.
Why It Crushes:
• Smokes static MAs in volatile arenas (crypto, stocks, you name it). Backtests show 20-30% fewer fakeouts than SMA50.
• Visual Pop: Overlays price with bold blue/yellow signals. Slap it on BTC 1D to see trends light up like Times Square.
• Tweakable: Dial ER length (default 50) to your timeframe. Short for scalps, long for swing trades.
Example Settings in Action:
• 10s Chart (Hyper-Scalping): Set Source: Close, ER Length: 100, Fast Power: 1, Slow Power: 6. Catches micro-trends in crypto like a heat-seeking missile. Blue/yellow flips scream entry/exit on fast moves.
• 2m Chart (Quick Trades): Set Source: Close, ER Length: 14, Fast Power: 1, Slow Power: 6. Perfect for rapid trend shifts in stocks or forex. Signals align with momentum bursts—check historical flips for proof.
Deployment:
• Drop it on any chart. Backtest settings to match your asset’s volatility—tweak until it sings.
• Pair with RSI or volume spikes for killer confirmation. Pro move: Enter on flip + volume pop, exit on reverse.
• Strategy-Ready: Slap long/short logic on alerts to build a lean, mean trading machine.
Open source from SightLing Labs—grab it, hack it, profit from it. Share your tweaks in the comments and let’s outsmart the market together. Trade hard, win big!
Multi-Timeframe Bollinger Band PositionBeta version.
My hope is to optimize the settings for this indicator and reintroduce it as a "strategy" with suggested position entry and exit points shown in the price pane.
Any feedback is appreciated.
Overview
This indicator is an oscillator that measures the normalized position of the price relative to Bollinger Bands across multiple timeframes. It takes the price's position within the Bollinger Bands (calculated on different timeframes) and averages those positions to create a single value that oscillates between 0 and 1. This value is then plotted as the oscillator, with reference lines and colored regions to help interpret the price's relative strength or weakness.
How It Works
Bollinger Band Calculation:
The indicator uses a custom function f_getBBPosition() to calculate the position of the price within Bollinger Bands for a given timeframe.
Price Position Normalization:
For each timeframe, the function normalizes the price's position between the upper and lower Bollinger Bands.
It calculates three positions based on the high, low, and close prices of the requested timeframe:
pos_high = (High - Lower Band) / (Upper Band - Lower Band)
pos_low = (Low - Lower Band) / (Upper Band - Lower Band)
pos_close = (Close - Lower Band) / (Upper Band - Lower Band)
If the upper band is not greater than the lower band or if the data is invalid (e.g., na), it defaults to 0.5 (the midline).
The average of these three positions (avg_pos) represents the normalized position for that timeframe, ranging from 0 (at the lower band) to 1 (at the upper band).
Multi-Timeframe Averaging:
The indicator fetches Bollinger Band data from four customizable timeframes (default: 30min, 60min, 240min, daily) using request.security() with lookahead=barmerge.lookahead_on to get the latest available data.
It calculates the normalized position (pos1, pos2, pos3, pos4) for each timeframe using f_getBBPosition().
These four positions are then averaged to produce the final avg_position:avg_position = (pos1 + pos2 + pos3 + pos4) / 4
This average is the oscillator value, which is plotted and typically oscillates between 0 and 1.
Moving Averages:
Two optional moving averages (MA1 and MA2) of the avg_position can be enabled, calculated using simple moving averages (ta.sma) with customizable lengths (default: 5 and 10).
These can be potentially used for MA crossover strategies.
What Is Being Averaged?
The oscillator (avg_position) is the average of the normalized price positions within the Bollinger Bands across the four selected timeframes. Specifically:It averages the avg_pos values (pos1, pos2, pos3, pos4) calculated for each timeframe.
Each avg_pos is itself an average of the normalized positions of the high, low, and close prices relative to the Bollinger Bands for that timeframe.
This multi-timeframe averaging smooths out short-term fluctuations and provides a broader perspective on the price's position within the volatility bands.
Interpretation:
0.0 The price is at or below the lower Bollinger Band across all timeframes (indicating potential oversold conditions).
0.15: A customizable level (green band) which can be used for exiting short positions or entering long positions.
0.5: The midline, where the price is at the average of the Bollinger Bands (neutral zone).
0.85: A customizable level (orange band) which can be used for exiting long positions or entering short positions.
1.0: The price is at or above the upper Bollinger Band across all timeframes (indicating potential overbought conditions).
The colored regions and moving averages (if enabled) help identify trends or crossovers for trading signals.
Example:
If the 30min timeframe shows the close at the upper band (position = 1.0), the 60min at the midline (position = 0.5), the 240min at the lower band (position = 0.0), and the daily at the upper band (position = 1.0), the avg_position would be:(1.0 + 0.5 + 0.0 + 1.0) / 4 = 0.625
This value (0.625) would plot in the orange region (between 0.85 and 0.5), suggesting the price is relatively strong but not at an extreme.
Notes:
The use of lookahead=barmerge.lookahead_on ensures the indicator uses the latest available data, making it more real-time, though its effectiveness depends on the chart timeframe and TradingView's data feed.
The indicator’s sensitivity can be adjusted by changing bb_length ("Bollinger Band MA Length" in the Input tab), bb_mult ("Bollinger Band Standard Deviation," also in the Input tab), or the selected timeframes.
[Pandora][Swarm] Rapid Exponential Moving AverageENVISIONING POSSIBILITY
What is the theoretical pinnacle of possibility? The current state of algorithmic affairs falls far short of my aspirations for achievable feasibility. I'm lifting the lid off of Pandora's box once again, very publicly this time, as a brute force challenge to conventional 'wisdom'. The unfolding series of time mandates a transcendental systemic alteration...
THE MOVING AVERAGE ZOO:
The realm of digital signal processing for trading is filled with familiar antiquated filtering tools. Two families of filtration, being 'infinite impulse response' (EMA, RMA, etc.) and 'finite impulse response' (WMA, SMA, etc.), are prevalently employed without question. These filter types are the mules and donkeys of data analysis, broadly accepted for use in finance.
At first glance, they appear sufficient for most tasks, offering a basic straightforward way to reduce noise and highlight trends. Yet, beneath their simplistic facade lies a constellation of limitations and impediments, each having its own finicky quirks. Upon closer inspection, identifiable drawbacks render them far from ideal for many real-world applications in today's volatile markets.
KNOWN FUNDAMENTAL FLAWS:
Despite commonplace moving average (MA) popularity, these conventional filters suffer from an assortment of fundamental flaws. Most of them don't genuinely address core challenges of how to preserve the true dynamics of a signal while suppressing noise and retaining cutoff frequency compliance. Their simple cookie cutter structures make them ill-suited in actuality for dynamic market environments. In reality, they often trade one problem for another dilemma, forsaking analytics to choose between distortion and delay.
A deeper seeded issue remains within frequency compliance, how adequately a filter respects (or disrespects) the underlying signal’s spectral properties according to it's assigned periodic parameter. Traditional MAs habitually distort phase relationships, causing delayed reactions with surplus lag or exaggerations with excessive undershoot/overshoot. For applications requiring timely resilience, such as algorithmic trading, these shortcomings are often functionally unacceptable. What’s needed is vigorous filters that can more accurately retain signal behaviors while minimizing lag without sacrificing smoothness and uniformity. Until then, the public MA zoo remains as a collection of corny compromises, rather than a favorable toolbelt of solutions.
P.S.: In PSv7+, in my opinion, many of these geriatric MAs deserve no future with ease of access for the naive, simply not knowing these filters are most likely creating bigger problems than solving any.
R.E.M.A.
What is this? I prefer to think of it as the "radical EMA", definitely along my lines of a retire everything morte algorithm. This isn't your run of the mill average from the petting zoo. I would categorize it as a paradigm shifting rampant economic masochistic annihilator, sufficiently good enough to begin ruthlessly executing moving averages left and right. Um, yeah... that kind of moving average destructor as you may soon recognize with a few 'Filters+' settings adjustments, realizing ordinary EMA has been doing us an injustice all this time.
Does it possess the capability to relentlessly exterminate most averaging filters in existence? Well, it's about time we find out, by uncaging it on the loose into the greater economic wilderness. Only then can we truly find out if it is indeed a radical exponential market accelerant whose time has come. If it is, then it may eventually become a reality erasing monolithic anomaly destined for greatness, ultimately changing the entire landscape of trading in perpetuity.
UNLEASHING NEXT-GEN:
This lone next generation exoweapon algorithm is intended to initiate the transformative beginning stages of mass filtration deprecation. However, it won't be the only one, just the first arrival of it's alien kind from me. Welcome to notion #1 of my future filtration frontier, on this episode of the algorithmic twilight zone. Where reality takes a twisting turn one dimension beyond practical logic, after persistent models of mindset disintegrate into insignificance, followed by illusory perception confronted into cognitive dissonance.
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SCRIPT INTENTION:
Deprecate anything and everything as any non-commercial member sees desirably fit. This includes your existing code formulations already in working functional modes of operation AND/OR future projects in the works. Swapping is nearly as simple as copying and pasting with meager modifications, after you have identified comparable likeness in this indicators settings with a visual assessment. Results may become eye opening, but only if you dare to look and test.
Where you may suspect a ta.filter() is lacking sufficient luster or may be flat out majorly deficient, employing rema, drema, trema, or qrema configurations may be a more suitable replacement. That's up to you to discern. My code satire already identifies likely bottom of the barrel suspects that either belong in the extinction record or have already been marked for deprecation. They are ordered more towards the bottom by rank where they belong. SuperSmoother is a masterpiece here to stay, being my original go-to reference filter. Everything you see here is already deprecated, including REMA...
REMA CHARACTERISTICS
- VERY low lag
- No overshoot
- Frequency compliant
- Proper initialization at bar_index==0
- Period parameter accepts poitive floating point numerics (AND integers!)
- Infinite impulse response (IIR) filter
- Compact code footprint
- Minimized computational overhead
Multi SMA + Golden/Death + Heatmap + BB**Multi SMA (50/100/200) + Golden/Death + Candle Heatmap + BB**
A practical trend toolkit that blends classic 50/100/200 SMAs with clear crossover labels, special 🚀 Golden / 💀 Death Cross markers, and a readable candle heatmap based on a dynamic regression midline and volatility bands. Optional Bollinger Bands are included for context.
* See trend direction at a glance with SMAs.
* Get minimal, de-cluttered labels on important crosses (50↔100, 50↔200, 100↔200).
* Highlight big regime shifts with special Golden/Death tags.
* Read momentum and volatility with the candle heatmap.
* Add Bollinger Bands if you want classic mean-reversion context.
Designed to be lightweight, non-repainting on confirmed bars, and flexible across timeframes.
# What This Indicator Does (plain English)
* **Tracks trend** using **SMA 50/100/200** and lets you optionally compute each SMA on a higher or different timeframe (HTF-safe, no lookahead).
* **Prints labels** when SMAs cross each other (up or down). You can force signals only after bar close to avoid repaint.
* **Marks Golden/Death Crosses** (50 over/under 200) with special labels so major regime changes stand out.
* **Colors candles** with a **heatmap** built from a regression midline and volatility bands—greenish above, reddish below, with a smooth gradient.
* **Optionally shows Bollinger Bands** (basis SMA + stdev bands) and fills the area between them.
* **Includes alert conditions** for Golden and Death Cross so you can automate notifications.
---
# Settings — Simple Explanations
## Source
* **Source**: Price source used to calculate SMAs and Bollinger basis. Default: `close`.
## SMA 50
* **Show 50**: Turn the SMA(50) line on/off.
* **Length 50**: How many bars to average. Lower = faster but noisier.
* **Color 50** / **Width 50**: Visual style.
* **Timeframe 50**: Optional alternate timeframe for SMA(50). Leave empty to use the chart timeframe.
## SMA 100
* **Show 100**: Turn the SMA(100) line on/off.
* **Length 100**: Bars used for the mid-term trend.
* **Color 100** / **Width 100**: Visual style.
* **Timeframe 100**: Optional alternate timeframe for SMA(100).
## SMA 200
* **Show 200**: Turn the SMA(200) line on/off.
* **Length 200**: Bars used for the long-term trend.
* **Color 200** / **Width 200**: Visual style.
* **Timeframe 200**: Optional alternate timeframe for SMA(200).
## Signals (crossover labels)
* **Show crossover signals**: Prints triangle labels on SMA crosses (50↔100, 50↔200, 100↔200).
* **Wait for bar close (confirmed)**: If ON, signals only appear after the candle closes (reduces repaint).
* **Min bars between same-pair signals**: Minimum spacing to avoid duplicate labels from the same SMA pair too often.
* **Trend filter (buy: 50>100>200, sell: 50<100<200)**: Only show bullish labels when SMAs are stacked bullish (50 above 100 above 200), and only show bearish labels when stacked bearish.
### Label Offset
* **Offset mode**: Choose how to push labels away from price:
* **Percent**: Offset is a % of price.
* **ATR x**: Offset is ATR(14) × multiplier.
* **Percent of price (%)**: Used when mode = Percent.
* **ATR multiplier (for ‘ATR x’)**: Used when mode = ATR x.
### Label Colors
* **Bull color** / **Bear color**: Background of triangle labels.
* **Bull label text color** / **Bear label text color**: Text color inside the triangles.
## Golden / Death Cross
* **Show 🚀 Golden Cross (50↑200)**: Show a special “Golden” label when SMA50 crosses above SMA200.
* **Golden label color** / **Golden text color**: Styling for Golden label.
* **Show 💀 Death Cross (50↓200)**: Show a special “Death” label when SMA50 crosses below SMA200.
* **Death label color** / **Death text color**: Styling for Death label.
## Candle Heatmap
* **Enable heatmap candle colors**: Turns the heatmap on/off.
* **Length**: Lookback for the regression midline and volatility measure.
* **Deviation Multiplier**: Band width around the midline (bigger = wider).
* **Volatility basis**:
* **RMA Range** (smoothed high-low range)
* **Stdev** (standard deviation of close)
* **Upper/Middle/Lower color**: Gradient colors for the heatmap.
* **Heatmap transparency (0..100)**: 0 = solid, 100 = invisible.
* **Force override base candles**: Repaint base candles so heatmap stays visible even if your chart has custom coloring.
## Bollinger Bands (optional)
* **Show Bollinger Bands**: Toggle the overlay on/off.
* **Length**: Basis SMA length.
* **StdDev Multiplier**: Distance of bands from the basis in standard deviations.
* **Basis color** / **Band color**: Line colors for basis and bands.
* **Bands fill transparency**: Opacity of the fill between upper/lower bands.
---
# Features & How It Works
## 1) HTF-Safe SMAs
Each SMA can be calculated on the chart timeframe or a higher/different timeframe you choose. The script pulls HTF values **without lookahead** (non-repainting on confirmed bars).
## 2) Crossover Labels (Three Pairs)
* **50↔100**, **50↔200**, **100↔200**:
* **Triangle Up** label when the first SMA crosses **above** the second.
* **Triangle Down** label when it crosses **below**.
* Optional **Trend Filter** ensures only signals aligned with the overall stack (50>100>200 for bullish, 50<100<200 for bearish).
* **Debounce** spacing avoids repeated labels for the same pair too close together.
## 3) Golden / Death Cross Highlights
* **🚀 Golden Cross**: SMA50 crosses **above** SMA200 (often a longer-term bullish regime shift).
* **💀 Death Cross**: SMA50 crosses **below** SMA200 (often a longer-term bearish regime shift).
* Separate styling so they stand out from regular cross labels.
## 4) Candle Heatmap
* Builds a **regression midline** with **volatility bands**; colors candles by their position inside that channel.
* Smooth gradient: lower side → reddish, mid → yellowish, upper side → greenish.
* Helps you see momentum and “where price sits” relative to a dynamic channel.
## 5) Bollinger Bands (Optional)
* Classic **basis SMA** ± **StdDev** bands.
* Light visual context for mean-reversion and volatility expansion.
## 6) Alerts
* **Golden Cross**: `🚀 GOLDEN CROSS: SMA 50 crossed ABOVE SMA 200`
* **Death Cross**: `💀 DEATH CROSS: SMA 50 crossed BELOW SMA 200`
Add these to your alerts to get notified automatically.
---
# Tips & Notes
* For fewer false positives, keep **“Wait for bar close”** ON, especially on lower timeframes.
* Use the **Trend Filter** to align signals with the broader stack and cut noise.
* For HTF context, set **Timeframe 50/100/200** to higher frames (e.g., H1/H4/D) while you trade on a lower frame.
* Heatmap “Length” and “Deviation Multiplier” control smoothness and channel width—tune for your asset’s volatility.
Multi-Timeframe MA 200Multi-Timeframe MA 200
This powerful tool plots the 200-period Moving Average across multiple timeframes (5m, 15m, 30m, 1h, 4h, Daily) directly on your active chart. You can switch between SMA (Simple Moving Average) and EMA (Exponential Moving Average) for all timeframes at once.
Key features:
✅ 100% accurate calculation using the original timeframe
✅ Option to choose SMA or EMA
✅ Visual smoothing for cleaner display
✅ Floating labels showing the origin timeframe
✅ Clean interface – no clutter or legends
✅ Ideal for scalping, intraday, and swing traders
Developed by BELOTTO TRADER, founder of the CLUBE DO GAIN – one of the most engaged trading communities in the Portuguese-speaking world.
Moving Average Exponential (Daily Frozen EMA)This script plots an Exponential Moving Average (EMA) based on the daily timeframe, but with a unique twist:
✅ The EMA value is frozen for the entire current daily session, only updating when a new daily candle begins.
🔍 How it works:
The EMA is calculated using the 1-day timeframe, regardless of the chart's current timeframe.
This EMA value remains fixed throughout the day — it doesn't fluctuate intrabar.
It updates only once the daily candle has closed, providing a stable and reliable reference point during the trading day.
The default is the 5 day EMA but can be changed to any EMA timeframe you desire such as 9, 21, 50, 100. 200, etc.
✨ Additional Features:
✅ Optional smoothing with various moving average types (SMA, EMA, WMA, SMMA, VWMA).
✅ Optional Bollinger Bands on top of the smoothed EMA.
✅ Adjustable settings for EMA length, smoothing type, Bollinger Band deviation, and display options.
🛠️ Use Cases:
Ideal for traders who want a non-reactive EMA during intraday trading.
Helps reduce signal noise by anchoring EMA to higher timeframe structure.
Useful for strategy development where EMA should represent confirmed daily bias only.
Hope this helps, happy trading!
Candle Ghosts: MTF 3 Candle Viewer by Chaitu50cCandle Ghosts: MTF 3 Candle Viewer helps you see candles from other timeframes directly on your chart. It shows the last 3 candles from a selected timeframe as semi-transparent boxes, so you can compare different timeframes without switching charts.
You can choose to view candles from 30-minute, 1-hour, 4-hour, daily, or weekly timeframes. The candles are drawn with their full open, high, low, and close values, including the wicks, so you get a clear view of their actual shape and size.
The indicator lets you adjust the position of the candles using horizontal and vertical offset settings. You can also control the spacing between the candles for better visibility.
An optional EMA (Exponential Moving Average) from the selected timeframe is also included to help you understand the overall trend direction.
This tool is useful for:
Intraday traders who want to see higher timeframe candles for better decisions
Swing traders checking lower timeframe setups
Anyone doing top-down analysis using multiple timeframes on a single chart
This is a simple and visual way to study how candles from different timeframes behave together in one place.
Dynamic Gap Probability ToolDynamic Gap Probability Tool measures the percentage gap between price and a chosen moving average, then analyzes your chart history to estimate the likelihood of the next candle moving up or down. It dynamically adjusts its sample size to ensure statistical robustness while focusing on the exact deviation level.
Originality and Value:
• Combines gap-based analysis with dynamic sample aggregation to balance precision and reliability.
• Automatically extends the sample when exact matches are scarce, avoiding misleading signals on rare extreme moves.
• Provides real “next-candle” probabilities based on historical occurrences rather than fixed thresholds or untested heuristics.
• Adds value by giving traders an evidence-based edge: you see how similar past deviations actually played out.
How It Works:
1. Calculate gap = (close – moving average) / moving average * 100.
2. Round the absolute gap to nearest percent (X%).
3. Count historical bars where gap ≥ X% above or ≤ –X% below.
4. If exact X% count is below the minimum occurrences threshold, include gaps at X+1%, X+2%, etc., until threshold is reached.
5. Compute “next-candle” green vs. red probabilities from the aggregated sample.
6. Display current gap, sample size, green probability, and red probability in a table.
Inputs:
• Moving Average Type (SMA, EMA, WMA, VWMA, HMA, SMMA, TMA)
• Moving Average Period (default 200)
• Minimum Occurrences Threshold (default 50)
• Table position and styling options
Examples:
• If price is 3% above the 200-period SMA and 120 occurrences ≥3% are found, with 84 green next candles (70%) and 36 red (30%), the script displays “3% | 120 | 70% green | 30% red.”
• If price is 8% below the SMA but only 20 exact matches exist, the script will include 9% and 10% gaps until it reaches 50 samples, then calculate probabilities from that broader set.
Why It’s Useful:
• Mean-reversion traders see green-probability signals at extreme overbought or oversold levels.
• Trend-followers identify continuation likelihood when red probability is high.
• Risk managers gauge reliability by inspecting sample size before acting on any signal.
Limitations:
• Historical probabilities do not guarantee future performance.
• Results depend on timeframe and symbol, backtest with your data before trading.
• Use realistic slippage and commission when overlaying on strategy scripts.
SMA Crossing Background Color (Multi-Timeframe)When day trading or scalping on lower timeframes, it’s often difficult to determine whether the broader market trend is moving upward or downward. To address this, I usually check higher timeframes. However, splitting the layout makes the charts too small and hard to read.
To solve this issue, I created an indicator that uses the background color to show whether the current price is above or below a moving average from a higher timeframe.
For example, if you set the SMA Length to 200 and the MT Timeframe to 5 minutes, the indicator will display a red background on the 1-minute chart when the price drops below the 200 SMA on the 5-minute chart. This helps you quickly recognize that the trend on the higher timeframe has turned bearish—without having to open a separate chart.
デイトレード、スキャルピングで短いタイムフレームでトレードをするときに、大きな動きは上に向いているのか下に向いているのかトレンドがわからなくなることがあります。
その時に上位足を確認するのですが、レイアウトをスプリットすると画面が小さくて見えにくくなるので、バックグラウンドの色で上位足の移動平均線では価格が上なのか下なのかを表示させるインジケーターを作りました。
例えば、SMA Length で200を選び、MT Timeframeで5分を選べば、1分足タイムフレームでトレードしていて雲行きが怪しくなってくるとBGが赤になり、5分足では200線以下に突入しているようだと把握することができます。
Contrarian 100 MAPairs nicely with Enhanced-Stock-Ticker-with-50MA-vs-200MA located here:
Description
The Contrarian 100 MA is a sophisticated Pine Script v6 indicator designed for traders seeking to identify key market structure shifts and trend reversals using a combination of a 100-period Simple Moving Average (SMA) envelope and Inner Circle Trader (ICT) Break of Structure (BoS) and Market Structure Shift (MSS) logic. By overlaying a semi-transparent SMA-based shadow on the price chart and plotting bullish and bearish structure signals, this indicator helps traders visualize critical price levels and potential trend changes. It leverages higher timeframe (HTF) pivot points and dynamic logic to adapt to various chart timeframes, making it ideal for swing and contrarian trading strategies. Customizable colors, timeframes, and alert conditions enhance its versatility for manual and automated trading setups.
Key Features
SMA Envelope: Plots a 100-period SMA for high and low prices, creating a semi-transparent (50% opacity) purple shadow to highlight the price range and provide context for price movements.
ICT BoS/MSS Logic: Identifies Break of Structure (BoS) and Market Structure Shift (MSS) signals for both bullish and bearish conditions, based on HTF pivot points.
Dynamic Timeframe Support: Adjusts pivot detection based on user-selected HTF (default: 1D) and chart timeframe (1M, 5M, 15M, 30M, 1H, 4H, 1D), ensuring adaptability across markets.
Visual Signals: Draws dotted lines for BoS (bullish/bearish) and MSS (bullish/bearish) signals at pivot levels, with customizable colors for easy identification.
Contrarian Approach: Signals potential reversals by combining SMA context with ICT structure breaks, ideal for traders looking to capitalize on trend shifts.
Alert Conditions: Supports alerts for bullish/bearish BoS and MSS signals, enabling integration with TradingView’s alert system for automated trading.
Performance Optimization: Uses efficient pivot detection and line management to minimize resource usage while maintaining accuracy.
Technical Details
SMA Calculation:
Computes 100-period SMAs for high (smaHigh) and low (smaLow) prices.
Plots invisible SMAs (fully transparent) and fills the area between them with 50% transparent purple for visual context.
Pivot Detection:
Uses ta.pivothigh and ta.pivotlow to identify HTF swing points, with dynamic lookback periods (rlBars: 5 for daily, 2 for intraday).
Tracks pivot highs (pH, nPh) and lows (pL, nPl) using a custom piv type for price and time.
BoS/MSS Logic:
Bullish BoS: Triggered when price breaks above a pivot high in a bullish trend, drawing a line at the pivot level.
Bearish BoS: Triggered when price breaks below a pivot low in a bearish trend.
Bullish MSS: Occurs when price breaks a pivot high in a bearish trend, signaling a potential trend reversal.
Bearish MSS: Occurs when price breaks a pivot low in a bullish trend.
Lines are drawn using line.new with xloc.bar_time for precise alignment, styled as dotted with customizable colors.
HTF Integration: Fetches HTF close prices and pivot data using request.security with lookahead_on for accurate signal timing.
Line Management: Maintains an array of lines (lin), removing outdated lines when new MSS signals occur to keep the chart clean.
Pivot Reset: Clears broken pivots (e.g., when price exceeds a pivot high or falls below a pivot low) to ensure fresh signal generation.
How to Use
Add to Chart:
Copy the script into TradingView’s Pine Editor and apply it to your chart.
Configure Settings:
SMA Length: Adjust the SMA period (default: 100 bars) to suit your trading style.
Structure Timeframe: Set the HTF for pivot detection (default: 1D).
Chart Timeframe: Select the chart timeframe (1M, 5M, 15M, 30M, 1H, 4H, 1D) to adjust pivot sensitivity.
Colors: Customize bullish/bearish BoS and MSS line colors via input settings.
Interpret Signals:
Bullish BoS: White dotted line (default) at a broken pivot high in a bullish trend, indicating trend continuation.
Bearish BoS: White dotted line at a broken pivot low in a bearish trend.
Bullish MSS: White dotted line at a broken pivot high in a bearish trend, suggesting a reversal to bullish.
Bearish MSS: White dotted line at a broken pivot low in a bullish trend, suggesting a reversal to bearish.
Use the SMA shadow to gauge price position within the recent range.
Set Alerts:
Create alerts for bullish/bearish BoS and MSS signals using TradingView’s alert system.
Customize Visuals:
Adjust line colors or SMA fill transparency via TradingView’s settings for better visibility.
Example Use Cases
Swing Trading: Use MSS signals to enter trades at potential trend reversals, with the SMA envelope confirming price extremes.
Contrarian Trading: Capitalize on BoS and MSS signals to trade against prevailing trends, using the SMA shadow for context.
Automated Trading: Integrate BoS/MSS alerts with trading bots for systematic entries and exits.
Multi-Timeframe Analysis: Combine HTF signals (e.g., 1D) with lower timeframe charts (e.g., 1H) for precise entries.
Notes
Testing: Backtest the indicator on your chosen market and timeframe to validate performance.
Compatibility: Built for Pine Script v6 and tested on TradingView as of June 19, 2025.
Limitations: Signals rely on HTF pivot accuracy, which may lag in fast-moving markets. Adjust rlBars or timeframe for sensitivity.
Optional Enhancements: Consider uncommenting or adding a histogram for SMA divergence (e.g., smaHigh - smaLow) for additional insights.
Acknowledgments
This indicator combines ICT’s market structure concepts with a dynamic SMA envelope to provide a unique contrarian trading tool. Share your feedback or suggestions in the TradingView comments, and happy trading!
Trend Blend
Trend blend is my new indicator. I use it to identify my bias when trading and filter out fake setups that are going in the wrong direction.
Trend blend utilises the 9 EMA (Red), 21 EMA (Black), and if you trade futures or Bitcoin, you can also use the VWAP (Blue).
There is also a table at the top right that displays the chart time frame bias
I prefer to use the 1-hour time frame for bias and execute the trades on 5-minute charts, mainly, and sometimes on the 1-minute for a smaller stoploss.
Here's an example of the trade I took during the London session on XAU/USD
1 hour bias was Bearish
Price broke out of the range
I waited for the London session to open, where I ended up taking a short on the 5-minute time frame as we broke out of the pre-London range
Entry was at the Fair Value Gap (5-minute bias was also Bearish as price traded into the FVG)
Stoploss was at the last high
Take Profit was the next major support level
Another set that I like to trade with the Trend blend is when price is trending bullish and price trades inside the 9 and 21 EMA, and there is a bullish candle closer above the 9 EMA with Stoploss below the low of the bullish candle and Take profit between 1-2 Risk to Reward
Same when there's a bearish trend, I wait for price to trade inside the 9 and 21 EMA, and I'll take sells when a bearish candle closes below the 9 EMA.
This setup works best in strong trends, or it can be used to enter a trade on a pullback or to scale into an existing trade.
PRO Investing - LevelPRO Investing - Level
📊 Dynamic Support/Resistance
This indicator plots the PRO Investing Level, defined as the midpoint between the highest high and lowest low over the past 252 trading days (default lookback period, equivalent to ~1 year). It acts as a key mean-reversion reference level, useful for identifying potential support/resistance zones or market equilibrium levels.
Features:
🕰️ Option to display only today’s level or historical levels.
⚙️ Customizable lookback period for flexibility across timeframes and strategies.
📉 Teal line plotted directly on the chart, highlighting this institutional-grade level.
Ideal for traders looking to anchor price action to significant historical ranges—particularly useful in mean-reversion, breakout, or volatility compression strategies.
OBV with MA & Bollinger Bands by Marius1032OBV with MA & Bollinger Bands by Marius1032
This script adds customizable moving averages and Bollinger Bands to the classic OBV (On Balance Volume) indicator. It helps identify volume-driven momentum and trend strength.
Features:
OBV-based trend tracking
Optional smoothing: SMA, EMA, RMA, WMA, VWMA
Optional Bollinger Bands with SMA
Potential Combinations and Trading Strategies:
Breakouts: Look for price breakouts from the Bollinger Bands, and confirm with a rising OBV for an uptrend or falling OBV for a downtrend.
Trend Reversals: When the price touches a Bollinger Band, examine the OBV for divergence. A bullish divergence (price lower low, OBV higher low) near the lower band could signal a reversal.
Volume Confirmation: Use OBV to confirm the strength of the trend indicated by Bollinger Bands. For example, if the BBs indicate an uptrend and OBV is also rising, it reinforces the bullish signal.
1. On-Balance Volume (OBV):
Purpose: OBV is a momentum indicator that uses volume flow to predict price movements.
Calculation: Volume is added on up days and subtracted on down days.
Interpretation: Rising OBV suggests potential upward price movement. Falling OBV suggests potential lower prices.
Divergence: Divergence between OBV and price can signal potential trend reversals.
2. Moving Average (MA):
Purpose: Moving Averages smooth price fluctuations and help identify trends.
Combination with OBV: Pairing OBV with MAs helps confirm trends and identify potential reversals. A crossover of the OBV line and its MA can signal a trend reversal or continuation.
3. Bollinger Bands (BB):
Purpose: BBs measure market volatility and help identify potential breakouts and trend reversals.
Structure: They consist of a moving average (typically 20-period) and two standard deviation bands.
Combination with OBV: Combining BBs with OBV allows for a multifaceted approach to market analysis. For example, a stock hitting the lower BB with a rising OBV could indicate accumulation and a potential upward reversal.
Created by: Marius1032
Chebyshev-Gauss Convergence DivergenceThe Chebyshev-Gauss Convergence Divergence is a momentum indicator that leverages the Chebyshev-Gauss Moving Average (CG-MA) to provide a smoother and more responsive alternative to traditional oscillators like the MACD. For more information see the moving average script:
How it works:
It calculates a fast CG-MA and a slow CG-MA. The CG-MA uses Gauss-Chebyshev quadrature to compute a weighted average, which can offer a better trade-off between lag and smoothness compared to simple or exponential MAs.
The Oscillator line is the difference between the fast CG-MA and the slow CG-MA.
A Signal Line, which is a simple moving average of the Oscillator line, is plotted to show the average trend of the oscillator.
A Histogram is plotted, representing the difference between the Oscillator and the Signal Line. The color of the histogram bars changes to indicate whether momentum is strengthening or weakening.
How to use:
Crossovers: A buy signal can be generated when the Oscillator line crosses above the Signal line. A sell signal can be generated when it crosses below.
Zero Line: When the Oscillator crosses above the zero line, it indicates upward momentum (fast MA is above slow MA).When it crosses below zero, it indicates downward momentum.
Divergence: Like with the MACD, look for divergences between the oscillator and price action to spot potential reversals.
Histogram: The histogram provides a visual representation of the momentum. When the bars are growing, momentum is increasing. When they are shrinking, momentum is fading.
Chebyshev-Gauss Moving AverageThis indicator applies the principles of Chebyshev-Gauss Quadrature to create a novel type of moving average. Inspired by reading rohangautam.github.io
What is Chebyshev-Gauss Quadrature?
It's a numerical method to approximate the integral of a function f(x) that is weighted by 1/sqrt(1-x^2) over the interval . The approximation is a simple sum: ∫ f(x)/sqrt(1-x^2) dx ≈ (π/n) * Σ f(xᵢ) where xᵢ are special points called Chebyshev nodes.
How is this applied to a Moving Average?
A moving average can be seen as the "mean value" of the price over a lookback window. The mean value of a function with the Chebyshev weight is calculated as:
Mean = /
The math simplifies beautifully, resulting in the mean being the simple arithmetic average of the function evaluated at the Chebyshev nodes:
Mean = (1/n) * Σ f(xᵢ)
What's unique about this MA?
The Chebyshev nodes xᵢ are not evenly spaced. They are clustered towards the ends of the interval . We map this interval to our lookback period. This means the moving average samples prices more intensely from the beginning and the end of the lookback window, and less intensely from the middle. This gives it a unique character, responding quickly to recent changes while also having a long "memory" of the start of the trend.
Advanced Moving Average ChannelAdvanced Moving Average Channel (MAC) is a comprehensive technical analysis tool that combines multiple moving average types with volume analysis to provide a complete market perspective.
Key Features:
1. Dynamic Channel Formation
- Configurable moving average types (SMA, EMA, WMA, VWMA, HMA, TEMA)
- Separate upper and lower band calculations
- Customizable band offsets for precise channel adjustment
2. Volume Analysis Integration
- Multi-timeframe volume analysis (1H, 24H, 7D)
- Relative volume comparison against historical averages
- Volume trend detection with visual indicators
- Price-level volume distribution profile
3. Market Context Indicators
- RSI integration for overbought/oversold conditions
- Channel position percentage
- Volume-weighted price levels
- Breakout detection with visual signals
Usage Guidelines:
1. Channel Interpretation
- Price within channel: Normal market conditions
- Price above upper band: Potential overbought condition
- Price below lower band: Potential oversold condition
- Channel width: Indicates market volatility
2. Volume Analysis
- High relative volume (>150%): Strong market interest
- Low relative volume (<50%): Weak market interest
- Volume trend arrows: Indicate increasing/decreasing market participation
- Volume profile: Shows price levels with highest trading activity
3. Trading Signals
- Breakout arrows: Potential trend continuation
- RSI extremes: Confirmation of overbought/oversold conditions
- Volume confirmation: Validates price movements
Customization:
- Adjust MA length for different market conditions
- Modify band offsets for tighter/looser channels
- Fine-tune volume analysis parameters
- Customize visual appearance
This indicator is designed for traders who want to combine price action, volume analysis, and market structure in a single, comprehensive tool.
Best EMA FinderThis script, Best EMA Finder, is based on the same original logic as the Best SMA Finder I published previously. Although it was not the initial goal of the project, several users asked for an EMA version, so here it is.
The script scans a wide range of Exponential Moving Average (EMA) lengths, from 10 to 500, and identifies the one that historically delivered the most robust performance on the current chart. The choice to stop at 500 is deliberate: beyond that point, EMA curves tend to flatten and converge, adding processing time without meaningful differences in signals or outcomes.
Each EMA is evaluated using a custom robustness score:
Profit Factor × log(Number of Trades) × sqrt(Win Rate)
Only EMA lengths that exceed a user-defined minimum number of trades are considered valid. Among these, the one with the highest robustness score is selected and displayed on the chart.
A table summarizes the results:
- Best EMA length
- Total number of trades
- Profit Factor
- Win Rate
- Robustness Score
You can adjust:
- Strategy type: Long Only or Buy & Sell
- Minimum number of trades required
- Table visibility
This script is designed for analysis and optimization only. It does not execute trades or handle position sizing. Only one open trade per direction is considered at a time.
