U.T.M.S v2🇷🇺 ОПИСАНИЕ (РУССКИЙ)
U.T.M.S v2 — Чистый EMA-кроссовер с фильтрами
Стратегия для 15м (в первую очередь) и 1ч таймфреймов.
Генерирует сигналы при пересечении EMA(8) и EMA(19) только при подтверждении тренда, объёма, волатильности и времени суток.
Каждая сделка закрывается по фиксированному Take Profit и Stop Loss.
✅ Минимум ложных входов
✅ Работает только в ликвидные часы
✅ Полная фильтрация шума и флэта
🔧 Настройки:
Fast EMA / Slow EMA — периоды скользящих (по умолчанию 8 / 19)
Take Profit % — уровень фиксации прибыли (рек. 2.5%)
Stop Loss % — уровень стоп-лосса (рек. 2.0%)
Фильтры (все включены по умолчанию):
Use 1H Trend Filter — вход разрешён только по направлению тренда на 1H (EMA50 > EMA200 для лонга)
Use Volume Filter — объём должен быть ≥ 1.5× среднего за 20 баров
Min Volume Multiplier — нижний порог объёма (рек. 1.5)
Max Volume Multiplier — верхний порог (рек. 3.0–4.0), отсекает аномальные пампы
Use ATR Volatility Filter — минимальная волатильность (рек. 0.3%)
Use Time Filter (UTC) — торговля только в часы высокой ликвидности: 12:00–18:00 и 20:00–02:00 UTC
💡 Идеальна для ручной торговли или подключения сигнальных ботов.
🇬🇧 DESCRIPTION (ENGLISH)
U.T.M.S v2 — Clean EMA Crossover with Filters
Strategy for 15m (primarily) and 1h timeframes.
Generates signals when the EMA(8) and EMA(19) cross, only if trend, volume, volatility, and time of day are confirmed.
Each trade is closed with a fixed Take Profit and Stop Loss.
✅ Low noise, high-quality signals
✅ Active only during high-liquidity hours
✅ Fully protected against flat and fakeouts
🔧 Inputs:
Fast EMA / Slow EMA — moving average periods (default: 8 / 19)
Take Profit % — profit target (suggested: 2.5%)
Stop Loss % — stop loss level (suggested: 2.0%)
Filters (all enabled by default):
Use 1H Trend Filter — trades only in 1H trend direction (EMA50 > EMA200 for long)
Use Volume Filter — volume must be ≥ 1.5× 20-bar average
Min Volume Multiplier — minimum volume threshold (suggested: 1.5)
Max Volume Multiplier — maximum volume cap (suggested: 3.0–4.0), filters out pumps/dumps
Use ATR Volatility Filter — minimum volatility (suggested: 0.3%)
Use Time Filter (UTC) — active only during high-liquidity sessions: 12:00–18:00 & 20:00–02:00 UTC
💡 Perfect for manual trading or webhook-based signal bots.
Medie mobili
MESA Adaptive Ehlers Flow | AlphaNattMESA Adaptive Ehlers Flow | AlphaNatt
An advanced adaptive indicator based on John Ehlers' MESA (Maximum Entropy Spectrum Analysis) algorithm that automatically adjusts to market cycles in real-time, providing superior trend identification with minimal lag across all market conditions.
🎯 What Makes This Indicator Revolutionary?
Unlike traditional moving averages with fixed parameters, this indicator uses Hilbert Transform mathematics to detect the dominant market cycle and adapts its responsiveness accordingly:
Automatically detects market cycles using advanced signal processing
MAMA (MESA Adaptive Moving Average) adapts from fast to slow based on cycle phase
FAMA (Following Adaptive Moving Average) provides confirmation signals
Dynamic volatility bands that expand and contract with cycle detection
Zero manual optimization required - the indicator tunes itself
📊 Core Components
1. MESA Adaptive Moving Average (MAMA)
The MAMA is the crown jewel of adaptive indicators. It uses the Hilbert Transform to measure the market's dominant cycle and adjusts its smoothing factor in real-time:
During trending phases: Responds quickly to capture moves
During choppy phases: Smooths heavily to filter noise
Transition is automatic and seamless based on price action
Parameters:
Fast Limit: Maximum responsiveness (default: 0.5) - how fast the indicator can adapt
Slow Limit: Minimum responsiveness (default: 0.05) - maximum smoothing during consolidation
2. Following Adaptive Moving Average (FAMA)
The FAMA is a slower version of MAMA that follows the primary signal. The relationship between MAMA and FAMA provides powerful trend confirmation:
MAMA > FAMA: Bullish trend in progress
MAMA < FAMA: Bearish trend in progress
Crossovers signal potential trend changes
3. Hilbert Transform Cycle Detection
The indicator employs sophisticated DSP (Digital Signal Processing) techniques:
Detects the dominant cycle period (1.5 to 50 bars)
Measures phase relationships in the price data
Calculates adaptive alpha values based on cycle dynamics
Continuously updates as market character changes
⚡ Key Features
Adaptive Alpha Calculation
The indicator's "intelligence" comes from its adaptive alpha:
Alpha dynamically adjusts between Fast Limit and Slow Limit based on the rate of phase change in the market cycle. Rapid phase changes trigger faster adaptation, while stable cycles maintain smoother response.
Dynamic Volatility Bands
Unlike static bands, these adapt to both ATR volatility AND the current cycle state:
Bands widen when the indicator detects fast adaptation (trending)
Bands narrow during slow adaptation (consolidation)
Band Multiplier controls overall width (default: 1.5)
Provides context-aware support and resistance
Intelligent Color Coding
Cyan: Bullish regime (MAMA > FAMA and price > MAMA)
Magenta: Bearish regime (MAMA < FAMA and price < MAMA)
Gray: Neutral/transitional state
📈 Trading Strategies
Trend Following Strategy
The MESA indicator excels at identifying and riding strong trends while automatically reducing sensitivity during choppy periods.
Entry Signals:
Long: MAMA crosses above FAMA with price closing above MAMA
Short: MAMA crosses below FAMA with price closing below MAMA
Exit/Management:
Exit longs when MAMA crosses below FAMA
Exit shorts when MAMA crosses above FAMA
Use dynamic bands as trailing stop references
Mean Reversion Strategy
When price extends beyond the dynamic bands during established trends, look for bounces back toward the MAMA line.
Setup Conditions:
Strong trend confirmed by MAMA/FAMA alignment
Price touches or exceeds outer band
Enter on first sign of reversal toward MAMA
Target: Return to MAMA line or opposite band
Cycle-Based Swing Trading
The indicator's cycle detection makes it ideal for swing trading:
Enter on MAMA/FAMA crossovers
Hold through the detected cycle period
Exit on counter-crossover or band extremes
Works exceptionally well on 4H to Daily timeframes
🔬 Technical Background
The Hilbert Transform
The Hilbert Transform is a mathematical operation used in signal processing to extract instantaneous phase and frequency information from a signal. In trading applications:
Separates trend from cycle components
Identifies the dominant market cycle without curve-fitting
Provides leading indicators of trend changes
MESA Algorithm Components
Smoothing: 4-bar weighted moving average for noise reduction
Detrending: Removes linear price trend to isolate cycles
InPhase & Quadrature: Orthogonal components for phase measurement
Homodyne Discriminator: Calculates instantaneous period
Adaptive Alpha: Converts period to smoothing factor
MAMA/FAMA: Final adaptive moving averages
⚙️ Optimization Guide
Fast Limit (0.1 - 0.9)
Higher values (0.5-0.9): More responsive, better for volatile markets and lower timeframes
Lower values (0.1-0.3): Smoother response, better for stable markets and higher timeframes
Default 0.5: Balanced for most applications
Slow Limit (0.01 - 0.1)
Higher values (0.05-0.1): Less smoothing during consolidation, more signals
Lower values (0.01-0.03): Heavy smoothing during chop, fewer but cleaner signals
Default 0.05: Good noise filtering while maintaining responsiveness
Band Multiplier (0.5 - 3.0)
Adjust based on instrument volatility
Backtest to find optimal value for your specific market
1.5 works well for most forex and equity indices
Consider higher values (2.0-2.5) for cryptocurrencies
🎨 Visual Interpretation
The gradient visualization shows probability zones around the MESA line:
MESA line: The adaptive trend center
Band expansion: Indicates strong cycle detection and trending
Band contraction: Indicates consolidation or ranging market
Color intensity: Shows confidence in trend direction
💡 Best Practices
Let it adapt: Give the indicator 50+ bars to properly calibrate to the market
Combine timeframes: Use higher timeframe MESA for trend bias, lower for entries
Respect the bands: Price rarely stays outside bands for extended periods
Watch for compression: Narrow bands often precede explosive moves
Volume confirmation: Combine with volume for higher probability setups
📊 Optimal Timeframes
15m - 1H: Day trading with Fast Limit 0.6-0.8
4H - Daily: Swing trading with Fast Limit 0.4-0.6 (recommended)
Weekly: Position trading with Fast Limit 0.2-0.4
⚠️ Important Considerations
The indicator needs time to "learn" the market - avoid trading the first 50 bars after applying
Extreme gap events can temporarily disrupt cycle calculations
Works best in markets with detectable cyclical behavior
Less effective during news events or extreme volatility spikes
Consider the detected cycle period for position holding times
🔍 What Makes MESA Superior?
Compared to traditional indicators:
vs. Fixed MAs: Automatically adjusts to market conditions instead of using one-size-fits-all parameters
vs. Other Adaptive MAs: Uses true DSP mathematics rather than simple volatility adjustments
vs. Manual Optimization: Continuously re-optimizes itself in real-time
vs. Lagging Indicators: Hilbert Transform provides earlier trend change detection
🎓 Understanding Adaptation
The magic of MESA is that it solves the eternal dilemma of technical analysis: be fast and get whipsawed in chop, or be smooth and miss the early move. MESA does both by detecting when to be fast and when to be smooth.
Adaptation in Action:
Strong trend starts → MESA quickly detects phase change → Fast Limit kicks in → Early entry
Trend continues → Phase stabilizes → MESA maintains moderate speed → Smooth ride
Consolidation begins → Phase changes slow → Slow Limit engages → Whipsaw avoidance
🚀 Advanced Applications
Multi-timeframe confluence: Use MESA on 3 timeframes for high-probability setups
Divergence detection: Watch for MAMA/price divergences at band extremes
Cycle period analysis: The internal period calculation can guide position duration
Band squeeze trading: Narrow bands + MAMA/FAMA cross = high-probability breakout
Created by AlphaNatt - Based on John Ehlers' MESA research. For educational purposes. Always practice proper risk management. Not financial advice. Always DYOR.
Arnaud Legoux Gaussian Flow | AlphaNattArnaud Legoux Gaussian Flow | AlphaNatt
A sophisticated trend-following and mean-reversion indicator that combines the power of the Arnaud Legoux Moving Average (ALMA) with advanced Gaussian distribution analysis to identify high-probability trading opportunities.
🎯 What Makes This Indicator Unique?
This indicator goes beyond traditional moving averages by incorporating Gaussian mathematics at multiple levels:
ALMA uses Gaussian distribution for superior price smoothing with minimal lag
Dynamic envelopes based on Gaussian probability zones
Multi-layer gradient visualization showing probability density
Adaptive envelope modes that respond to market conditions
📊 Core Components
1. Arnaud Legoux Moving Average (ALMA)
The ALMA is a highly responsive moving average that uses Gaussian distribution to weight price data. Unlike simple moving averages, ALMA can be fine-tuned to balance responsiveness and smoothness through three key parameters:
ALMA Period: Controls the lookback window (default: 21)
Gaussian Offset: Shifts the Gaussian curve to adjust lag vs. responsiveness (default: 0.85)
Gaussian Sigma: Controls the width of the Gaussian distribution (default: 6.0)
2. Gaussian Envelope System
The indicator features three envelope calculation modes:
Fixed Mode: Uses ATR-based fixed width for consistent envelope sizing
Adaptive Mode: Dynamically adjusts based on price acceleration and volatility
Hybrid Mode: Combines ATR and standard deviation for balanced adaptation
The envelopes represent statistical probability zones. Price moving beyond these zones suggests potential mean reversion opportunities.
3. Momentum-Adjusted Envelopes
The envelope width automatically expands during strong trends and contracts during consolidation, providing context-aware support and resistance levels.
⚡ Key Features
Multi-Layer Gradient Visualization
The indicator displays 10 gradient layers between the ALMA and envelope boundaries, creating a visual "heat map" of probability density. This helps traders quickly assess:
Distance from the mean
Potential support/resistance strength
Overbought/oversold conditions in context
Dynamic Color Coding
Cyan gradient: Price below ALMA (bullish zone)
Magenta gradient: Price above ALMA (bearish zone)
The ALMA line itself changes color based on price position
Trend Regime Detection
The indicator automatically identifies market regimes:
Strong Uptrend: Trend strength > 0.5% with price above ALMA
Strong Downtrend: Trend strength < -0.5% with price below ALMA
Weak trends and ranging conditions
📈 Trading Strategies
Mean Reversion Strategy
Look for price entering the extreme Gaussian zones (beyond 95% of envelope width) when trend strength is moderate. These represent statistical extremes where mean reversion is probable.
Signals:
Long: Price in lower Gaussian zone with trend strength > -0.5%
Short: Price in upper Gaussian zone with trend strength < 0.5%
Trend Continuation Strategy
Enter when price crosses the ALMA during confirmed strong trend conditions, riding momentum while using the envelope as a trailing stop reference.
Signals:
Long: Price crosses above ALMA during strong uptrend
Short: Price crosses below ALMA during strong downtrend
🎨 Visualization Guide
The gradient layers create a "probability cloud" around the ALMA:
Darker shades (near ALMA): High probability zone - price tends to stay here
Lighter shades (near envelope edges): Lower probability - potential reversal zones
Price at envelope extremes: Statistical outliers - strongest mean reversion setups
⚙️ Customization Options
ALMA Parameters
Adjust period for different timeframes (lower for day trading, higher for swing trading)
Modify offset to tune responsiveness vs. smoothness
Change sigma to control distribution width
Envelope Configuration
Choose envelope mode based on market characteristics
Adjust multiplier to match instrument volatility
Modify gradient depth for visual preference (5-15 layers)
Signal Enhancement
Momentum Length: Lookback for trend strength calculation
Signal Smoothing: Additional EMA smoothing to reduce noise
🔔 Built-in Alerts
The indicator includes six pre-configured alert conditions:
ALMA Trend Long - Price crosses above ALMA in strong uptrend
ALMA Trend Short - Price crosses below ALMA in strong downtrend
Mean Reversion Long - Price enters lower Gaussian zone
Mean Reversion Short - Price enters upper Gaussian zone
Strong Uptrend Detected - Momentum confirms strong bullish regime
Strong Downtrend Detected - Momentum confirms strong bearish regime
💡 Best Practices
Use on clean, liquid markets with consistent volatility
Combine with volume analysis for confirmation
Adjust envelope multiplier based on backtesting for your specific instrument
Higher timeframes (4H+) generally provide more reliable signals
Use adaptive mode for trending markets, hybrid for mixed conditions
⚠️ Important Notes
This indicator works best in markets with normal price distribution
Extreme news events can invalidate Gaussian assumptions temporarily
Always use proper risk management - no indicator is perfect
Backtest parameters on your specific instrument and timeframe
🔬 Technical Background
The Arnaud Legoux Moving Average was developed to solve the classic dilemma of moving averages: the trade-off between lag and noise. By applying Gaussian distribution weighting, ALMA achieves superior smoothing while maintaining responsiveness to price changes.
The envelope system extends this concept by creating probability zones based on volatility and momentum, effectively mapping where price is "likely" vs "unlikely" to be found based on statistical principles.
Created by AlphaNatt - For educational purposes. Always practice proper risk management. Not financial advice. Always DYOR.
多指标量化交易DIY- The indicator includes a very large menu of leading tools, each with its own logic to determine uptrend or downtrend impulses. Highlights include:
- Range Filter: Uses a dynamic centerline and bands computed via conditional EMA/SMA and range sizing to define directional movement. It can operate in a default mode or an alternative “DW” mode.
- Rational Quadratic Kernel (RQK): Applies a kernel smoothing model (Nadaraya Watson) to detect uptrends and downtrends with a focus on noise reduction.
- Supertrend, Half Trend, SSL Channel: Classic trend-following tools that derive direction from ATR-based bands or moving average channels.
- Ichimoku Cloud and SuperIchi: Multi-component systems validating trend via cloud position, conversion/base line relationships, projected cloud, and lagging span.
- TSI (True Strength Index), DPO (Detrended Price Oscillator), AO (Awesome Oscillator), MACD, STC (Schaff Trend Cycle), QQE Mod: Momentum and cycle tools that parse direction from crossovers, zero-line behavior, and momentum shifts.
- Donchian Trend Ribbon, Chandelier Exit: Trend and exit tools that can validate breakouts or sustained trend strength.
- ADX/DMI: Measures trend strength and directional movement via +DI/-DI relationships and minimum ADX thresholds.
- RSI and Stochastic: Use crossovers, level exits, or threshold filters to gate entries based on overbought/oversold dynamics or relative strength trends.
- Vortex, Chaikin Money Flow, VWAP, Bull Bear Power, ROC, Wolfpack Id, Hull Suite: A diverse set of directional, momentum, and volume-based indicators to suit different markets and styles.
- Trendline Breakout and Range Detector: Price-behavior filters that confirm signals during breakouts or within defined ranges.
Confirmation Filters
- Each filter is optional. When enabled, it must validate the leading condition for a signal to pass. Examples:
- EMA Filter: Requires price to be above a specified EMA for longs and below for shorts, filtering signals that contradict broader trend or baseline levels.
- 2 EMA Cross and 3 EMA Cross: Enforce moving average cross conditions (fast above slow for long, the reverse for short) or a three-line stacking logic for more stringent trend alignment.
- RQK, Supertrend, Half Trend, Donchian, QQE, Hull, MACD (crossover vs. zero-line), AO (zero line or AC momentum variants), SSL: Each adds its characteristic validation pattern.
- RSI family (MA cross, exits OB/OS zones, threshold levels) plus RSI MA direction and RSI/RSI MA limits: Multiple ways to constrain signals via relative strength behavior and trajectories.
- Choppiness Index and Damiani Volatility: Prevent entries during ranging conditions or insufficient volatility; choppiness thresholds and volatility states gate the trade.
- VWAP, Volume modes (above MA, simple up/down, delta), Chaikin Money Flow: Volume and flow conditions that ensure signals happen in supportive liquidity or accumulation/distribution contexts.
- ADX/DMI thresholds: Demand a minimum trend strength and directional DI alignment to reduce whipsaw trades.
- Trendline Breakout and Range Detector: Confirm that the price is breaking structure or remains within active range consistent with the leading setup.
- By combining several filters you can create strict, conservative entries or looser setups depending on your goals.
Range Filter Engine
- A core building block, the Range Filter uses conditional EMA and SMA functions to compute adaptive bands around a dynamic centerline. It supports two types:
- Type 1: The centerline updates when price exceeds the band thresholds; bands define acceptable drift ranges.
- Type 2: Uses quantized steps (via floor operations) relative to the previous centerline to handle larger moves in discrete increments.
- The engine offers smoothing for range values using a secondary EMA and can switch between raw and averaged outputs. Its hi/lo bands and centerline compose a corridor that defines directional movement and potential breakout confirmation.
Signal Construction
- The script computes:
- leadinglongcond and leadingshortcond : The primary directional signals from the chosen leading indicator.
- longCond and shortCond : Final signals formed by combining the leading conditions with all enabled confirmations. Each confirmation contributes a boolean gate. If a filter is disabled, it contributes a neutral pass-through, keeping the logic intact without enforcing that condition.
- Expiry Logic: The code counts consecutive bars where the leading condition remains true. If confirmations do not line up within the user-defined “Signal Expiry Candle Count,” the setup is abandoned and the signal does not trigger.
- Alternation: An optional state ensures that long and short signals alternate. This can reduce repeated entries in the same direction without a clear reset.
- Finally, longCondition and shortCondition represent the actionable signals after expiry and alternation logic. These drive the label plotting and alert conditions.
Visualization
- Buy and Sell Labels: When longCondition or shortCondition confirm, the script plots annotated labels directly on the chart, making entries easy to see at a glance. The labels use color coding and clear text tags (“long” vs. “short”).
- Dashboard: A table summarizes the status of the leading indicator and all confirmations. Each row shows the indicator label and whether it passed (✔️) or failed (❌) on the current bar. This intensely practical UI helps you diagnose why a signal did or did not trigger, empowering faster strategy iteration and parameter tuning.
- Failed Confirmation Markers: If a setup expires (count exceeds the limit) and confirmations failed to align, the script can mark the chart with a small label and provide a tooltip listing which confirmations did not pass. It’s a helpful audit trail to understand missed trades or prevent “chasing” invalid signals.
- Data Window Values: The script outputs signal states to the data window, which can be useful for debugging or building composite conditions in multi-indicator templates.
Inputs and Parameters
- You control the indicator from a comprehensive input panel:
- Setup: Signal expiry count, whether to enforce alternating signals, and whether to display labels and the dashboard (including position and size).
- Leading Indicator: Choose the primary signal generator from the large list.
- Per-Filter Toggles: For each confirmation, a respect... toggle enables or disables it. Many include sub-options (like MACD type, Stochastic mode, RSI mode, ADX variants, thresholds for choppiness/volatility, etc.) to fine-tune behavior.
- Range Filter Settings: Choose type and behavior; select default vs. DW mode and smoothing. The underlying functions adjust band sizes using ATR, average change, standard deviation, or user-defined scales.
- Because everything is customizable, you can adapt the indicator to different assets, volatility regimes, and timeframes.
Alerts and Automation
- The script defines alert conditions tied to longCondition and shortCondition . You can set these alerts in your chart to trigger notifications or webhook calls for automated execution in external bots. The alert text is simple, and you can configure your own message template when creating alerts in the chart, including JSON payloads for algorithmic integration.
Typical Workflow
- Select a Leading Indicator aligned with your style. For trend following, Supertrend or SSL may be appropriate; for momentum, MACD or TSI; for range/trend-change detection, Range Filter, RQK, or Donchian.
- Add a few key Confirmation Filters that complement the leading signal. For example:
- Pair Supertrend with EMA Filter and RSI MA Direction to ensure trend alignment and positive momentum.
- Combine MACD Crossover with ADX/DMI and Volume Above MA to avoid signals in low-trend or low-liquidity conditions.
- Use RQK with Choppiness Index and Damiani Volatility to only act when the market is trending and volatile enough.
- Set a sensible Signal Expiry Candle Count. Shorter expiry keeps entries timely and reduces lag; longer expiry captures setups that mature slowly.
- Observe the Dashboard during live markets to see which filters pass or fail, then iterate. Tighten or loosen thresholds and filter combinations as needed.
- For automation, turn on alerts for the final conditions and use webhook payloads to notify your trading robot.
Strengths and Practical Notes
- Flexibility: The indicator is a toolkit rather than a single rigid model. It lets you test different combinations rapidly and visualize outcomes immediately.
- Clarity: Labels, dashboard, and failed-confirmation markers make it easy to audit behavior and refine settings without digging into code.
- Robustness: The expiry and alternation options add discipline, avoiding the temptation to enter late or repeatedly in one direction without a reset.
- Modular Design: The logical gates (“respect…”) make the behavior transparent: if a filter is on, it must pass; if it’s off, the signal ignores it. This keeps reasoning clean.
- Avoiding Overfitting: Because you can stack many filters, it’s tempting to over-constrain signals. Start simple (one leading indicator and one or two confirmations). Add complexity only if it demonstrably improves your edge across varied market regimes.
Limitations and Recommendations
- No single configuration is universally optimal. Markets change; tune filters for the instrument and timeframe you trade and revisit settings periodically.
- Trend filters can underperform in choppy markets; likewise, momentum filters can false-trigger in quiet periods. Consider using Choppiness Index or Damiani to gate signals by regime.
- Use expiry wisely. Too short may miss good setups that need a few bars to confirm; too long may cause late entries. Balance responsiveness and accuracy.
- Always consider risk management externally (position sizing, stops, profit targets). The indicator focuses on signal quality; combining it with robust trade management methods will improve results.
Example Configurations
- Trend-Following Setup:
- Leading: Supertrend uptrend for longs and downtrend for shorts.
- Confirmations: EMA Filter (price above 200 EMA for long, below for short), ADX/DMI (trend strength above threshold with +DI/-DI alignment), Volume Above MA.
- Expiry: 3–4 bars to keep entries timely.
- Result: Strong bias toward sustained moves while avoiding weak trends and thin liquidity.
- Mean-Reversion to Momentum Crossover:
- Leading: RSI exits from OB/OS zones (e.g., RSI leaves oversold for long and leaves overbought for short).
- Confirmations: 2 EMA Cross (fast crossing slow in the same direction), MACD zero-line behavior for added momentum validation.
- Expiry: 2–3 bars for responsive re-entry.
- Result: Captures momentum transitions after short-term extremes, with extra confirmation to reduce head-fakes.
- Range Breakout Focus:
- Leading: Range Filter Type 2 or Donchian Trend Ribbon to detect breakouts.
- Confirmations: Damiani Volatility (avoid low-volatility false breaks), Choppiness Index (prefer trend-ready states), ROC positive/negative threshold.
- Expiry: 1–3 bars to act on breakout windows.
- Result: Better alignment to breakout dynamics, gating trades by volatility and regime.
Conclusion
- This indicator is a comprehensive, configurable framework that merges a chosen leading signal with an array of corroborating filters, disciplined expiry handling, and intuitive visualization. It’s designed to help you build high-quality entry signals tailored to your approach, whether that’s trend-following, breakout trading, momentum capturing, or a hybrid. By surfacing pass/fail states in a dashboard and allowing alert-based automation, it bridges the gap between discretionary analysis and systematic execution. With sensible parameter tuning and thoughtful filter selection, it can serve as a robust backbone for signal generation across diverse instruments and timeframes.
Earnings Day - Price Predictor [DunesIsland]It's designed to analyze and visualize historical stock price movements on earnings report days, focusing on percentage changes.
Here's a breakdown of what it does, step by step:
Key Inputs and Setup
User Input: There's a single input for "Lookback Years" (default: 10), which determines how far back in time (approximately) the indicator analyzes earnings data. It uses a rough calculation of milliseconds in that period to filter historical data.
Data Fetching: It uses TradingView's request.earnings function to pull actual earnings per share (EPS) data for the current ticker. Earnings days are identified where EPS data exists on a bar but not on the previous one (to avoid duplicates).
Price Change Calculation: For each detected earnings day, it computes the percentage price movement as (close - close ) / close * 100, representing the change from the previous close to the current close on that day.
Processing and Calculations (on the Last Bar)
Lookback Filter: It calculates a cutoff timestamp for the lookback period and processes only earnings events within that window.
Overall Averages:
Separates positive (≥0%) and negative (<0%) percentage changes.
Seasonality (Next Quarter Prediction):
Identifies the most recent earnings quarter (latest_q).
Predicts the "next" quarter (e.g., if latest is Q4, next is Q1;
Again, separates positive and negative changes, computing their respective averages.
Visual Outputs
Lookback: How far to fetch the data in years.
Average Change (Green): Showing the average of all positive changes.
Average Change (Red): Showing the average of all negative changes.
Seasonality Change (Green): Showing the average of positive changes for the predicted next quarter.
Seasonality Change (Red): Showing the average of negative changes for the predicted next quarter.
Purpose and Usage
This indicator helps traders assess a stock's historical reaction to earnings announcements. The overall averages give a broad sense of typical gains/losses, while the seasonality focuses on quarter-specific trends to "predict" potential movement for the upcoming earnings (based on past same-quarter performance). It's best used on daily charts for stocks with reliable earnings data. Note that quarter inference is calendar-based and may not perfectly match fiscal calendars for all companies—it's an approximation.
Gunzo Trend Sniper For Loop🧠 Gunzo Trend Sniper For Loop — Adaptive Trend Momentum Framework
The Gunzo Trend Sniper For Loop is a precision-built, adaptive trend analysis system designed to expose hidden trend strength, exhaustion points, and directional momentum within any market — from cryptocurrencies to equities and forex.
At its core, this indicator integrates a loop-based comparative engine with a multi-type adaptive moving average filter, producing a highly responsive yet smooth measure of directional sentiment.
⚙️ Core Concept
Gunzo Trend Sniper quantifies market bias by comparing the current smoothed weighted average of price to its historical values across a dynamic lookback window.
Through this iterative “for loop” scoring process, the indicator tallies how many of the recent bars exhibit higher or lower values than the present one — forming a trend strength score that oscillates between bullish and bearish dominance.
In essence:
Positive score values indicate sustained upward bias — more candles recently closed below the current value.
Negative or low score values signal downward pressure — suggesting that recent candles are outperforming the current value.
📊 Interpreting the Chart
The indicator plots two complementary visuals:
Gunzo Trend Score (Oscillator Panel)
Green Zones (Above Upper Threshold) → Confirmed uptrend momentum and accumulation.
Red Zones (Below Lower Threshold) → Confirmed downtrend pressure and potential distribution.
Neutral Region (Between Thresholds) → Consolidation or transitional phases.
Gunzo Trend Line (Overlay on Price Chart)
The plotted line dynamically changes color:
🟩 Green: Confirmed bullish trend bias
🟥 Red: Confirmed bearish momentum
⚪ Gray: Neutral or indecisive period
This color transition acts as a visual confirmation layer, aligning the oscillator’s internal score with price structure.
🔍 How to Use It
1. Trend Identification:
When the oscillator consistently remains above the upper threshold, and the overlay line turns green, the market exhibits strong bullish continuation.
Sustained readings below the lower threshold with a red overlay signal dominant bearish control.
2. Entry Confirmation:
Combine this indicator with breakout or pullback setups. For example, enter long positions when:
The oscillator crosses above the upper threshold from below,
The overlay line flips from red to green, confirming new momentum.
Short entries follow the inverse logic.
3. Divergence Detection:
Price forming higher highs while the Gunzo Trend Score forms lower highs may hint at momentum exhaustion — signaling potential reversals.
4. Adaptive Thresholding:
Adjust ThresholdL and ThresholdS to fit volatility.
Tighter thresholds increase sensitivity (useful in lower timeframes).
Wider thresholds filter out noise (ideal for daily or higher intervals).
🧭 Strategic Insights
The Gunzo Trend Sniper is more than an oscillator — it’s a multi-dimensional market bias model.
Its comparative logic captures how consistent recent directional strength has been, effectively quantifying trend persistence. This makes it especially valuable for:
Momentum confirmation before breakouts.
Avoiding false reversals during volatile consolidation phases.
Detecting early trend slowdowns before major reversals.
| Parameter | Description |
| ------------------------------- | ------------------------------------------------------------------- |
| `MA Type` | Selects the smoothing algorithm (SMA, EMA, SMMA, or WMA).
| `MA Source` | Price input (default: OHLC4). |
| `Gunzo Length` | Lookback for the moving average engine. |
| `Smoothing Length` | Additional smoothing layer for refined signals. |
| `From / To` | Defines the historical range for the scoring loop. |
| `Threshold Uptrend / Downtrend` | Determines when a market is considered strongly bullish or bearish. |
💡 Pro Tips
Combine with volume-based indicators or ATR filters for volatility-adjusted entries.
Use in conjunction with higher timeframe confirmation — e.g., align the Gunzo Trend on 4H and 1D for stronger bias.
Works exceptionally well with trend-following strategies, especially when paired with trailing stop systems.
MTF 200 SMAMulti-Timeframe (MTF) 200 SMA: Your Universal Trend Guide
Tired of switching timeframes just to check the major moving averages?
The MTF 200 SMA indicator is a powerful, customizable tool designed to give you a clear, comprehensive view of the trend across multiple timeframes, all on a single chart. It's built on Pine Script v6 for stability and performance.
Key Features:
9 MTF Lines: Simultaneously plot the 200 Simple Moving Average (SMA) for 30m, 1h, 2h, 3h, 4h, 6h, 8h, Daily, and Weekly charts. Understand the overall market structure at a glance.
Single-Click Toggle: Use the 'Current Chart TF Only' checkbox to instantly switch from the crowded MTF view to showing only the standard 200 SMA for your current chart resolution. Perfect for focusing on immediate price action.
Dynamic Highlighting: The 'Highlight Current Chart TF' option (default ON) emphasizes the SMA corresponding to your current chart, making it stand out with a bright Aqua color and a thicker line when in MTF mode.
Full Customization: Easily adjust the SMA Length and the MTF SMA Line Color directly in the indicator settings.
How to Use It:
Trend Confirmation: When all MTF lines (especially the Daily and Weekly) are aligned and moving in the same direction, it provides high-confidence trend confirmation.
Dynamic S/R: The MTF SMAs often act as strong dynamic Support and Resistance levels, even when viewing a lower timeframe like the 5-minute chart.
Clean Analysis: Use the 'Current Chart TF Only' option when you need to declutter your chart and focus on the primary trend of your active trading session.
Elevate your trend analysis today with the MTF 200 SMA!
Puell Multiple Variants [OperationHeadLessChicken]Overview
This script contains three different, but related indicators to visualise Bitcoin miner revenue.
The classical Puell Multiple : historically, it has been good at signaling Bitcoin cycle tops and bottoms, but due to the diminishing rewards miners get after each halving, it is not clear how you determine overvalued and undervalued territories on it. Here is how the other two modified versions come into play:
Halving-Corrected Puell Multiple : The idea is to multiply the miner revenue after each halving with a correction factor, so overvalued levels are made comparable by a horizontal line across cycles. After experimentation, this correction factor turned out to be around 1.63. This brings cycle tops close to each other, but we lose the ability to see undervalued territories as a horizontal region. The third variant aims to fix this:
Miner Revenue Relative Strength Index (Miner Revenue RSI) : It uses RSI to map miner revenue into the 0-100 range, making it easy to visualise over/undervalued territories. With correct parameter settings, it eliminates the diminishing nature of the original Puell Multiple, and shows both over- and undervalued revenues correctly.
Example usage
The goal is to determine cycle tops and bottoms. I recommend using it on high timeframes, like monthly or weekly . Lower than that, you will see a lot of noise, but it could still be used. Here I use monthly as the example.
The classical Puell Multiple is included for reference. It is calculated as Miner Revenue divided by the 365-day Moving Average of the Miner Revenue . As you can see in the picture below, it has been good at signaling tops at 1,3,5,7.
The problems:
- I have to switch the Puell Multiple to a logarithmic scale
- Still, I cannot use a horizontal oversold territory
- 5 didn't touch the trendline, despite being a cycle top
- 9 touched the trendline despite not being a cycle top
Halving-Corrected Puell Multiple (yellow): Multiplies the Puell Multiple by 1.63 (a number determined via experimentation) after each halving. In the picture below, you can see how the Classical (white) and Corrected (yellow) Puell Multiples compare:
Advantages:
- Now you can set a constant overvalued level (12.49 in my case)
- 1,3,7 are signaled correctly as cycle tops
- 9 is correctly not signaled as a cycle top
Caveats:
- Now you don't have bottom signals anymore
- 5 is still not signaled as cycle top
Let's see if we can further improve this:
Miner Revenue RSI (blue):
On the monthly, you can see that an RSI period of 6, an overvalued threshold of 90, and an undervalued threshold of 35 have given historically pretty good signals.
Advantages:
- Uses two simple and clear horizontal levels for undervalued and overvalued levels
- Signaling 1,3,5,7 correctly as cycle tops
- Correctly does not signal 9 as a cycle top
- Signaling 4,6,8 correctly as cycle bottoms
Caveats:
- Misses two as a cycle bottom, although it was a long time ago when the Bitcoin market was much less mature
- In the past, gave some early overvalued signals
Usage
Using the example above, you can apply these indicators to any timeframe you like and tweak their parameters to obtain signals for overvalued/undervalued BTC prices
You can show or hide any of the three indicators individually
Set overvalued/undervalued thresholds for each => the background will highlight in green (undervalued) or red (overvalued)
Set special parameters for the given indicators: correction factor for the Corrected Puell and RSI period for Revenue RSI
Show or hide halving events on the indicator panel
All parameters and colours are adjustable
Golden Cross 50/200Simplicity characterizes each of my trading systems and methods. On this occasion, I present a trend-following strategy with simple rules and high profitability.
System Rules:
-Long entries when the 50 EMA crosses above the 200 EMA.
-Stop Loss (SL) placed at the low of 15 candles prior to the entry candle.
-Take Profit (TP) triggered when the 50 EMA crosses below the 200 EMA.
As with any trend-following system, we sacrifice win rate for profitability, and of course, we will focus on traditional markets with a consistent trend-following nature over time.
Recommended Markets and Timeframes:
BTCUSDT H6
August 17, 2017 - October 20, 2025 Total trades: 30
Profitability: +1,682.99%
Win rate: 40%
Outperforms Buy & Hold
BTCUSDT H4
August 17, 2017 - October 20, 2025 Total trades: 42
Profitability: +12,213.49% (high and stable performance curve)
Win rate: 40%
Outperforms Buy & Hold
BTCUSDT H2
August 17, 2017 - October 20, 2025 Total trades: 95
Profitability: +2,363.80%
Win rate: 24.21%
Matches Buy & Hold
BTCUSDT H1
August 17, 2017 - October 20, 2025 Total trades: 203
Profitability: +1,045% (stable performance curve)
Win rate: 25.62%
BTCUSDT 30M
August 17, 2017 - October 20, 2025 Total trades: 393
Profitability: +4,205.51% (high and stable performance curve)
Win rate: 27.74%
Outperforms Buy & Hold
BTCUSDT 15M
August 17, 2017 - October 20, 2025 Total trades: 821
Profitability: +1,311.97%
Win rate: 23.14%
Timeframes such as Daily, 12-hour, 8-hour, and even 5-minute charts are profitable with this system, so feel free to experiment.
Other markets and timeframes to observe include:
-XAUUSD (H1, H4, H6, H8, Daily)
-SPX (Daily: +21,302% profitability since 1871 in 40 trades)
-Tesla (H1, H2, H4, H6, especially M30 and M15)
-Apple (M5, M15, M30, H1, H2, H4…)
-Warner Bros (M5, M15, M30…)
-GOOGL (M5, M15, M30, H1, H2, H4, H6…)
-AMZN (M5, M15, M30, H2, H4, H6…)
-META (M5, M15, M30, H1, H2, H4…)
-NVDA (M5, M15, M30, H1, H2, H4…)
This system not only generates significant profitability but also performs very well in traditional markets, even on lower timeframes like 5-minute charts. In many cases, the returns far exceed Buy & Hold.
I hope this strategy is useful to you. Follow my Spanish-speaking profile if you want to see my market analyses, and send me your good vibes!
ORBs, EMAs, SMAs, AVWAPThis is an update to a previously published script. In short the difference is the added capability to adjust the length of EMAs. Also added 3 customizable SMAs. Enjoy! Let me know what you think of the script please. This is only second one I have ever done. Through practice and people like @LuxAlgo and other Pinescripters this isn't possible. Tedious hrs with ChatGPT to correct nuances, who doesnt seem to learn from (insert pronoun) mistakes
This all-in-one indicator combines key institutional tools into a unified framework for intraday and swing trading. Designed for traders who use multi-session analysis and dynamic levels, it automatically maps out global session breakouts, moving averages, and volume-weighted anchors with high clarity.
Features include:
🕓 Tokyo, London, and New York ORBs (Opening Range Breakouts) — 30-minute configurable range boxes that persist until the next New York open.
📈 Anchored VWAP with Standard Deviation Bands — dynamically anchorable to session, week, or month for institutional-grade price tracking.
📊 Exponential Moving Averages (9, 20, 113, 200) — for short-, mid-, and long-term momentum structure.
📉 Simple Moving Averages (20, 50, 100) — fully customizable lengths, colors, and visibility toggles for trend confirmation.
🏁 Prior High/Low Levels (PDH/PDL, PWH/PWL, PMH/PML) — automatically plotted from previous day, week, and month, with labels placed at each session’s midpoint.
🎛️ Session-Aligned Time Logic — all time calculations use New York session anchors with DST awareness.
💡 Clean Visualization Options — every component can be toggled on/off, recolored, or customized for your workflow.
Best used for:
ORB break-and-retest setups
VWAP and EMA rejections
Confluence-based trading around key session levels
Multi-session momentum tracking
Key Levels (PA, MAs, VWAPs, Volume Profile, rVWAPs)This indicator marks all kinds of key levels so that users can keep an overview of their specified levels in a convenient non chart cluttering way. It can highlight levels of confluence or display each level seperately.
The indicator includes markers for the following levels:
Price Action: Opens, Previous High/Low, Monday Range
Moving Averages: H4, D1 and W1 with customisable lengths
VWAPs: Developing and Previous VWAPs with their respective VAL/VAH (1 Standard Deviation)
Rolling VWAPs
Volume Profile: Developing and Previous VAL/VAH/POC
What makes this indicator different is its vast customisation options and big library of levels…
… users can choose to merge all levels that are aligned in a specified % threshold and additionally they can choose to color them the same color to highlight confluence levels.
… users have the choice between Full Label Markers or Abbreviations of those Labels.
… users have the choice of a few presets making level switching fast and convenient (Price Action, Volume Profile, VWAP, Volume or Custom).
… users can specify if they prefer to highlight Simple Moving Averages or Exponential Moving Averages. They have calculations available on three different timeframes and can change the lengths of each.
… users can color all levels the same with one click instead of having to manually change all of them.
… when users choose Volume Profile Levels they can either let the script auto calculate the row size making asset switching simple or they can manually input row size.
With the custom preset users can show and hide whichever levels they want.
(To have them the same every time you freshly load the indicator save your settings as default in the lower left corner of the settings tab).
Purpose
This indicator is designed to serve as a level visualisation tool that has the ability to highlight levels of confluence. It may assist in keeping an overview of where all levels are currently located but does not produce signals or trade recommendations.
🐼 Panda EMA-OBV Dual SignalPanda EMA-OBV Dual Signal
Description:
The Panda EMA-OBV Dual Signal combines exponential moving averages (EMAs) with On-Balance Volume (OBV) to identify both trend direction and momentum strength.
This script is designed for professional traders who want clear visual confirmations for reversals and trend continuations.
Main Features:
• Multi-layer EMA system (14 / 20 / 50 / 100 periods) for trend alignment
• OBV divergence detection (Bullish / Bearish)
• RSI confirmation filter for extra accuracy
• Auto signal arrows for buy/sell opportunities
• Works on all timeframes (H1 / H4 / D / W / MN)
How to use:
1️⃣ Look for Buy signal when OBV shows Bullish divergence and price closes above EMA 20.
2️⃣ Look for Sell signal when OBV shows Bearish divergence and price closes below EMA 20.
3️⃣ Use EMA crossovers as confirmation for trend continuation.
Tip:
The script is optimized for XAUUSD and BTCUSD but can also be applied to other assets for swing or intraday analysis.
Created by Millionbears | For educational and analytical purposes only.
Robust Scaled HMA | OquantOverview
The Robust Scaled HMA is an indicator designed to provide a more resilient trend-following signal by combining the Hull Moving Average (HMA) with a robust scaling mechanism based on interquartile range (IQR). Unlike traditional scaled indicators that rely on standard deviation, which can be skewed by outliers in volatile markets, this approach uses quartiles to normalize the HMA values, offering better resistance to extreme price movements. It generates long and short signals based on user-defined thresholds and includes built-in performance metrics to evaluate the indicator's historical behavior, alongside buy-and-hold comparisons(Remember past performance doesn’t guarantee future results). This allows traders to assess potential effectiveness without needing external backtesting tools(Remember past performance doesn’t guarantee future results). The indicator is particularly useful for those seeking a balance between responsiveness and robustness in trend detection, and it visualizes allocation states (LONG, SHORT, or CASH) through color-coded plots and optional tables.
Key Factors/Components
Robust Scaling: Employs IQR for normalization instead of standard deviation, reducing sensitivity to outliers and providing a more stable measure of deviation from the median HMA.
Signal Generation: Threshold-based triggers for long (above upper threshold) and short (below lower threshold) positions, with options to enable/disable longs or shorts to suit directional biases.
Performance Metrics: Calculates key risk-adjusted metrics such as Maximum Drawdown (Max DD), Intra-Trade Max DD, Sharpe Ratio, Sortino Ratio, Omega Ratio, Percent Profitable, Profit Factor, Total Trades, and Net Profit for the indicator's signals.
Buy-and-Hold Comparison: Displays equivalent metrics for a simple buy-and-hold approach on the same asset and timeframe for benchmarking.
Visualization Tools: Color-coded plot of the scaled HMA, threshold lines, optional equity curve, bar coloring, and customizable tables for metrics and allocation status.
Alert Conditions: Built-in alerts for bullish (crossover to long) and bearish (crossunder to short) signals.
How It Works
The indicator starts by computing a standard HMA on the selected source. It then applies robust scaling over a lookback period by subtracting the median HMA and dividing by the IQR (difference between the 75th and 25th percentiles), resulting in a normalized value that highlights deviations in a outlier-resistant manner. Signals are derived simply: values exceeding the upper threshold suggest upward momentum (long), while those below the lower threshold indicate downward momentum (short). The script simulates a basic equity curve by applying these signals to daily returns, holding long/short only when enabled, otherwise defaulting to cash (0% return). Metrics are computed on this equity curve using standard formulas—e.g., Sharpe as average return over standard deviation of returns (annualized), Sortino focusing on downside deviation, and Omega as the ratio of positive to negative returns. All calculations begin from the user-specified start date to ensure relevance to the tested period(Remember past performance doesn’t guarantee future results). This logic emphasizes robustness for real-world application.
For Who It Is Best/Recommended Use Cases
This indicator is best suited for traders focused on trend-following strategies in markets prone to volatility or outliers. Recommended use cases include:
Trend Identification: As a filter for entering/exiting positions.
Strategy Evaluation: Quickly assessing signal quality through integrated metrics without complex backtesting setups(Remember past performance doesn’t guarantee future results).
Customization: Adjusting for bullish biases by disabling shorts, or vice versa, in one-sided markets.
Settings and Default Settings
Start Date: Timestamp for when calculations begin (default: 1 Jan 2018).
Source: Price series for HMA calculation (default: close).
HMA Length: Period for the Hull Moving Average (default: 25).
Robust Scaling Length: Lookback for robust scaling calculations (default: 40).
Upper Threshold: Level above which long signals trigger (default: 0.6).
Lower Threshold: Level below which short signals trigger (default: -0.2).
Allow Long Trades: Enables long positions; if disabled, defaults to cash (default: true).
Allow Shorts: Enables short positions; if disabled, defaults to cash (default: false).
Show Indicator Metrics Table: Displays table with strategy metrics (default: true).
Show Buy&Hold Table: Displays table with asset benchmarks (default: true).
Plot Equity Curve: Shows the simulated equity line (default: false).
Defaults are tuned for general use.
Conclusion
The Robust Scaled HMA offers a fresh take on trend detection by prioritizing robustness through IQR scaling, making it a valuable addition for traders aiming to navigate noisy markets with metrics-backed insights(Remember past performance doesn’t guarantee future results).
⚠️ Disclaimer: This indicator is intended for educational and informational purposes only. Trading/investing involves risk, and past performance does not guarantee future results. Always test and evaluate indicators/strategies before applying them in live markets. Use at your own risk.
Portfolio Strategy TesterThe Portfolio Strategy Tester is an institutional-grade backtesting framework that evaluates the performance of trend-following strategies on multi-asset portfolios. It enables users to construct custom portfolios of up to 30 assets and apply moving average crossover strategies across individual holdings. The model features a clear, color-coded table that provides a side-by-side comparison between the buy-and-hold portfolio and the portfolio using the risk management strategy, offering a comprehensive assessment of both approaches relative to the benchmark.
Portfolios are constructed by entering each ticker symbol in the menu, assigning its respective weight, and reviewing the total sum of individual weights displayed at the top left of the table. For strategy selection, users can choose between Exponential Moving Average (EMA), Simple Moving Average (SMA), Wilder’s Moving Average (RMA), Weighted Moving Average (WMA), Moving Average Convergence Divergence (MACD), and Volume-Weighted Moving Average (VWMA). Moving average lengths are defined in the menu and apply only to strategy-enabled assets.
To accurately replicate real-world portfolio conditions, users can choose between daily, weekly, monthly, or quarterly rebalancing frequencies and decide whether cash is held or redistributed. Daily rebalancing maintains constant portfolio weights, while longer intervals allow natural drift. When cash positions are not allowed, capital from bearish assets is automatically redistributed proportionally among bullish assets, ensuring the portfolio remains fully invested at all times. The table displays a comprehensive set of widely used institutional-grade performance metrics:
CAGR = Compounded annual growth rate of returns.
Volatility = Annualized standard deviation of returns.
Sharpe = CAGR per unit of annualized standard deviation.
Sortino = CAGR per unit of annualized downside deviation.
Calmar = CAGR relative to maximum drawdown.
Max DD = Largest peak-to-trough decline in value.
Beta (β) = Sensitivity of returns relative to benchmark returns.
Alpha (α) = Excess annualized risk-adjusted returns relative to benchmark.
Upside = Ratio of average return to benchmark return on up days.
Downside = Ratio of average return to benchmark return on down days.
Tracking = Annualized standard deviation of returns versus benchmark.
Turnover = Average sum of absolute changes in weights per year.
Cumulative returns are displayed on each label as the total percentage gain from the selected start date, with green indicating positive returns and red indicating negative returns. In the table, baseline metrics serve as the benchmark reference and are always gray. For portfolio metrics, green indicates outperformance relative to the baseline, while red indicates underperformance relative to the baseline. For strategy metrics, green indicates outperformance relative to both the baseline and the portfolio, red indicates underperformance relative to both, and gray indicates underperformance relative to either the baseline or portfolio. Metrics such as Volatility, Tracking Error, and Turnover ratio are always displayed in gray as they serve as descriptive measures.
In summary, the Portfolio Strategy Tester is a comprehensive backtesting tool designed to help investors evaluate different trend-following strategies on custom portfolios. It enables real-world simulation of both active and passive investment approaches and provides a full set of standard institutional-grade performance metrics to support data-driven comparisons. While results are based on historical performance, the model serves as a powerful portfolio management and research framework for developing, validating, and refining systematic investment strategies.
Dual ATR with OffsetGives you a cross when ATR moves unusually, perhaps like would happen at the beginning of a trade.
MA Oscillator Map [ChartPrime]⯁ OVERVIEW
The MA Oscillator Map transforms moving average deviations into an oscillator framework that highlights overextended price conditions. By normalizing the difference between price and a chosen moving average, the tool maps oscillations between -100 and +100 , with gradient coloring to emphasize bullish and bearish momentum. When the oscillator cools from extreme levels (-100/100), the indicator marks potential reversal points and extends short-term levels from those extremes. A compact side table and dynamic bar coloring make momentum context visible at a glance.
⯁ KEY FEATURES
Oscillator Mapping (±100 Scale):
Price deviation from the selected MA is normalized into a percentage scale, allowing consistent overbought/oversold readings across assets and timeframes.
// MA
MA = ma(close, maLengthInput, maTypeInput)
diff = src - MA
maxVal = ta.highest(math.abs(diff), 50)
osc = diff / maxVal * 100
Customizable MA Types:
Choose SMA, EMA, SMMA, WMA, or VWMA to fine-tune the smoothing method that powers the oscillator.
Extreme Signal Diamonds:
When the oscillator retreats from +100 or -100, the script plots diamonds to flag potential exhaustion and reversal zones.
Dynamic Levels from Extremes:
Upper and lower dotted lines extend from recent overextension points, projecting temporary barriers until broken by price.
Gradient Bar Coloring:
Candles and oscillator values adopt a bullish-to-bearish gradient, making shifts in momentum instantly visible on the chart.
Compact Momentum Map:
A table at the chart’s edge plots the oscillator position with a gradient scale and live percentage label for precise momentum tracking.
⯁ USAGE
Watch for diamonds after the oscillator exits ±100 — these mark potential exhaustion zones.
Use extended dotted levels as short-term reference lines; if broken, trend continuation is favored.
Combine gradient bar coloring with oscillator shifts for confirmation of momentum reversals.
Experiment with different MA types to adapt sensitivity for trending vs. ranging markets.
Use the side momentum table as a quick-read gauge of trend strength in percent terms.
⯁ CONCLUSION
The MA Oscillator Map reframes moving average deviations into a visual momentum tracker with extremes, reversal signals, and dynamic levels. By blending oscillator math with intuitive visuals like gradient candles, diamonds, and a live gauge, it helps traders spot overextension, exhaustion, and momentum shifts across any market.
SuperTrend MAAfter building SuperBands, I kept thinking about what happens at the midpoint between those two volatility-adaptive envelopes. The upper and lower bands are both trailing price based on ATR and EMA smoothing, but they're operating independently in opposite directions. Taking their average seemed like it might produce an interesting centerline that adapts to volatility in a way that regular moving averages don't. Turns out it does, and that's what this indicator is.
The core concept is straightforward. Instead of plotting the upper and lower SuperBands separately, this calculates both of them internally, averages their values, and then applies an additional smoothing pass with EMA to create a single centerline. That centerline sits roughly in the middle of where the bands would be, but because it's derived from ATR-offset trailing stops rather than direct price smoothing, it behaves differently than a standard moving average of the same length. During trending periods, the centerline tracks closer to price because one of the underlying bands is actively trailing while the other is dormant. During consolidation, both bands compress toward price and the centerline tends to oscillate more with shorter-term movements.
What's interesting is that this acts like a supertrend all by itself with directional behavior baked in. When one of the underlying supertrend waves dominates, meaning price is strongly trending in one direction and only one band is active, you get what feels like a "true" supertrend, whatever that means exactly. The centerline locks into trend-following mode and the color gradient reflects that commitment. You get bright bullish colors during sustained uptrends when the upper band is doing all the work, and strong bearish colors during downtrends when the lower band dominates. But when both bands are active and fighting for control, which happens during consolidation or choppy conditions, the centerline settles into more neutral tones that clearly signal you're in a ranging environment. The colors really do emphasize this behavior and make it visually obvious which regime you're in.
The smoothing parameter controls how aggressively the underlying SuperBand trails adapt to price, which indirectly affects how responsive the centerline is. Lower values make the bands tighter and more reactive, so the centerline follows price action more closely. Higher values create wider bands that only respond to sustained moves, which produces a smoother centerline that filters out more noise. The center smoothing parameter applies a second EMA pass specifically to the averaged midpoint, giving you independent control over how much additional lag you want on the final output versus the raw band average.
What makes this different from just slapping an EMA on price is that the underlying bands are already volatility-aware through their ATR calculations. When volatility spikes, the bands widen and the centerline adjusts its position relative to price based on where those bands settle. A traditional moving average would just smooth over the volatility spike without adjusting its distance from price. This approach incorporates volatility information into the centerline's positioning, which can help it stay relevant during regime changes where fixed-period moving averages tend to lag badly or whipsaw.
The color gradient adds a momentum overlay using the same angle-based calculation from SuperBands. The centerline's rate of change gets normalized by an RMS estimate of its historical movement range, converted to an angle through arctangent scaling, and then mapped to a color gradient. When the centerline is rising, it gradients from neutral toward your chosen bullish color, with brightness increasing as the rate of ascent steepens. When falling, it shifts toward the bearish color with intensity tied to the descent rate. This gives you an immediate visual sense of whether the centerline is accelerating, decelerating, or moving at a stable pace.
Configuration is simpler than SuperBands since you're only dealing with a single output line instead of separate bull and bear envelopes. The length parameter controls the underlying band behavior. ATR period and multiplier determine how much space the bands allocate around price before they trail. Center smoothing adds the extra EMA pass on the averaged midpoint. You can tune these independently to get different characteristics. A tight ATR multiplier with heavy center smoothing creates a smooth line that stays close to price. A wide multiplier with light center smoothing produces a line that swings more freely and adapts faster to directional changes.
From a practical standpoint, this works well as a trend filter or dynamic support and resistance reference. Price above the centerline with bullish coloring suggests a favorable environment for long positions. Price below with bearish coloring indicates the opposite. Crossovers can signal trend changes, though like any moving average system, you'll get whipsaws in choppy conditions. The advantage over traditional MAs is that the volatility adaptation tends to reduce false signals during transitional periods where volatility is expanding but direction hasn't fully committed.
The implementation reuses the entire SuperBands logic, which means all the smoothing and state management for the trailing stops is identical. The only addition is averaging the two band outputs and applying the final EMA pass. The color calculation follows the same RMS-normalized angle approach but applies it to the centerline's delta rather than the individual band deltas. This keeps the coloring consistent with how SuperBands handles momentum visualization while adapting it to a single line instead of dual envelopes.
What this really highlights is that you can derive moving averages from mechanisms other than direct price smoothing. By building the centerline from volatility-adjusted trailing stops, you get adaptive behavior that responds to both price movement and volatility regime without needing separate inputs or complex multi-stage calculations. Whether that adaptation provides a meaningful edge depends on your strategy and market, but it's a fundamentally different approach than the typical fixed-period or adaptive MAs that adjust length based on volatility or momentum indicators.
Phoenix Smart ZoneThe Golden Trend Cloud Indicator is a professional trend-identification tool that combines Ichimoku Cloud with a 20-period Moving Average (MA20) to clearly define the market’s dominant direction.
It visually highlights bullish and bearish momentum using dynamic support and resistance zones derived from the Kumo cloud structure.
Teckmann Ribbon ScalperA scalping indicator is a technical tool designed to provide quick, high-probability trade signals in short timeframes, typically 1–5 minutes. It identifies immediate market opportunities by detecting rapid price movements, trend direction, and potential reversals. Common features include moving average crossovers, momentum oscillators, and price action patterns, often enhanced with visual cues like arrows or alerts for instant buy or sell entries. The goal is to maximize small, frequent profits while minimizing exposure to market noise.Follow the signal at the close of 2nd or 3rd candle after the ribbon changes.
ADX MA Filter for Choppy MarketsA clear way to see expanding markets and identify contracting markets or chop
