Reversal Zones// This indicator identifies likely reversal zones above and below current price by aggregating multiple technical signals:
// • Prior Day High/Low
// • Opening Range (9:30–10:00)
// • VWAP ±2 standard deviations
// • 60‑minute Bollinger Bands
// It draws shaded boxes for each base level, then computes a single upper/lower reversal zone (closest level from combined signals),
// with configurable zone width based on the expected move (EM). Within those reversal zones, it highlights an inner “strike zone”
// (percentage of the box) to suggest optimal short-option strikes for credit spreads or iron condors.
// Additional features:
// • Optional Expected Move lines from the RTH open
// • 15‑minute RSI/Mean‑Reversion and Trend‑Day confluence flags displayed in a dashboard
// • Toggles to include/exclude each signal and adjust styling
// How to use:
// 1. Adjust inputs to select which levels to include and set the expected move parameters.
// 2. Reversal boxes (red above, green below) show zones where price is most likely to reverse.
// 3. Inner strike zones (darker shading) guide optimal short-strike placement.
// 4. Dashboard confirms whether mean-reversion or trend-day conditions are active.
// Customize colors and visibility in the settings panel. Enjoy disciplined, confluence-based trade entries!
Индикаторы и стратегии
ahr999 Index BITSTAMP
Credits to discountry for making the original script.
reference:
Updates:
- Updated the historical data to use BITSTAMP:BTCUSD since BLX:BNC api is not working anymore
- Implemented a tooltip label displaying the latest AHR index value.
TOPIX Relative Strength vs Symbol + Volume Quality (JP)Overview
Relative Strength vs Symbol + Volume Quality (JP) visualizes the relative performance (%) of a stock versus a chosen benchmark (e.g., TOPIX, Nikkei 225, or ETFs) while incorporating volume quality and momentum analysis.
It calculates percentage-point differences between the target and benchmark, smooths them (EMA/SMA), and evaluates whether the strength is supported by quality volume flow.
All data uses confirmed bars only (request.security() with confirmed values) to minimize repainting, and labels are drawn only on confirmed bars.
What It Shows
Relative Performance (%pt): Difference in rate of change between the stock and its benchmark.
Above 0 → outperforming
Below 0 → underperforming
Trend Direction: Short-/mid-term trend from smoothed EMA/SMA.
Volume Quality: Ratio of up-volume to down-volume, scaled from -1 to +1.
Volume Momentum (Z-Score): Measures unusual surges in trading activity.
Strength Detection: Combines price-based strength (relative or z-score) with volume quality and momentum filters.
How to Use
Set your comparison symbol (e.g., TSE:1306, TVC:NI225).
Adjust lookback length and smoothing period/type to fit your analysis window.
Enable “Confirm strength by volume quality” and/or “Use volume Z-score” to filter signals with supportive volume.
Optionally, configure background thresholds to highlight extreme relative strength/weakness.
Use Screener Mode to suppress visual outputs (table/labels) for performance in Pine Screener.
Main Input Groups
Comparison Settings: Benchmark symbol, calculation timeframe.
Period & Smoothing: lookback, smoothLen, and MA type (EMA or SMA).
Price Strength Detection: Enable Z-score mode and adjust zLen / zThresh.
Volume Quality & Momentum: vqThresh (volume quality) and vZth (Z-score threshold).
Display: Toggle histogram tint, background highlight, mini-table, and signal labels.
Background Thresholds: Independent thresholds for histogram/MA lines and colors.
Screener Output: Suppress visuals for screening use.
Output & Coloring
Histogram: Relative performance in %pt. Red = outperforming, Green = underperforming (intensity by magnitude).
White Line (EMA/SMA):
Rising with good volume quality → Red
Rising but poor quality → Yellow
Falling → White
Background: Optional highlight when histogram/MA exceeds user thresholds.
Counters: Hidden plots track how many bars have consecutively exceeded thresholds (usable in screeners).
Alerts
Strength Detection (Price + Volume):
Triggered when price condition (MA > 0 or Z-score > threshold) and volume conditions are met.
Weakness / Loss of Strength:
Triggered on cross-under or when volume conditions fail.
Labels: Optional, shown only on confirmed bars.
Repaint Prevention
All calculations use confirmed bar data only.
Labels appear only when bars close.
On lower timeframes, benchmark update delays may cause minor lag.
Volume quality is derived from up/down bar classification, which can be distorted by gaps or illiquid markets.
Avoid overfitting thresholds — values differ by asset and timeframe.
Practical Applications
Identify outperformance with supportive volume across sectors or themes.
Use streak counters to find consistent relative winners or laggards.
Compare stocks vs sector indices or ETFs to track rotation and momentum shifts.
Disclaimer
This script and its description are provided for educational and informational purposes only.
They do not constitute financial advice or recommendations.
Use at your own discretion, considering market risk, liquidity, and data limitations.
This description follows TradingView’s House Rules (no promotion, plagiarism, or misleading claims).
Publication Guidelines
When publishing:
Do not include promotional links or invitations.
Do not copy text/code from other authors without permission.
Screenshots should illustrate the script’s function only, not serve as marketing material.
Maintain consistency of language (English only for this version).
概要
Relative Strength vs Symbol + Volume Quality (JP) は、対象銘柄と比較指標（例：TOPIX）との相対パフォーマンスを％ポイント差で算出し、平滑化線（EMA/SMA）とヒストグラムで可視化します。さらに、出来高を「質（上げ/下げボリュームのバランス）」と「勢い（Zスコア）」で評価し、価格×出来高の両面から“強さ/弱さ”を判定します。
リペイント抑制のため、request.security()は確定足を参照し、ラベル描画も確定時に限定しています。
何がわかるか
相対パフォーマンス（％pt）：対象と比較指標の騰落率差。0より上＝相対優位、下＝相対劣位。
平滑化トレンド：相対の短中期的な傾き（EMA/SMA）。
出来高の質：上昇バー出来高と下降バー出来高の比から -1〜+1 で評価。
出来高の勢い（Zスコア）：直近出来高の異常度。
強/弱シグナル：価格条件（基準越え・Z超え）に、出来高条件（質・勢い）を組み合わせて抽出。
使い方（基本手順）
比較対象を「比較シンボル」で指定（例：TSE:1306、TVC:NI225 等）。
「比較期間（バー数）」と「平滑化（期間/種類）」を調整し、相対の視点を合わせる。
出来高確認を使う場合は「出来高の質で“強さ”を確認」「出来高の勢い（Z）」をオンにし、閾値を調整。
背景ハイライトの**閾値（ヒスト/平均線別）**を設定すると、重要局面を一目で把握可能。
スクリーナー利用時は「スクリーナー用」をオンにして、テーブル/ラベルの描画を抑制。
主な入力項目
比較設定：比較シンボル、計算タイムフレーム。
期間・平滑化：比較期間lookback、平滑化長smoothLen、MA種別（EMA/SMA）。
強さ検出（価格）：Zスコア方式のオン/オフ、zLen、zThresh。
出来高の質・勢い：質の閾値vqThresh、勢いZの長さvZlenと閾値vZth。
表示：テーブル、背景、ヒスト濃淡、直近ラベルのON/OFF。
背景（閾値）：ヒスト/平均線の上下しきいと背景色。
スクリーナー出力：描画抑制トグル。
出力と色分け
ヒストグラム：相対パフォーマンス（％pt）。プラス域は赤系、マイナス域は緑系で濃淡表示。
白線（実体は平滑化相対）：上向きかつ出来高質が閾値以上なら赤、上向きでも質不足なら黄、下降時は白。
背景色（任意）：設定したヒスト/平均線の閾値を超過/割れで自動着色。
カウンタ：ヒスト/平均線が各閾値を連続超過/連続割れした本数を、スクリーナーが取得できるよう非表示プロットで出力。
シグナル・アラート
強さ検出（価格+出来高）：
価格条件 … 平滑化線の0越え、またはZスコアがzThresh越え。
出来高条件 … 「質 ≥ vqThresh」「勢いZ ≥ vZth」（任意）。
条件一致で「強」アラート／喪失・未達で「弱」アラート。
ラベル（任意）：確定足でのみ出力。
リペイントと制約
request.security()は確定足データを用い、確定時ラベルのみ描画する設計です。
比較シンボルの更新周期・分足集計差により、短期足ではタイムラグが生じる場合があります。
出来高の「質」は上昇/下降バーの単純仕分けに依存するため、ギャップや出来高の歪みが強い市場では解釈に注意。
閾値は銘柄・期間で最適値が異なります。**過度な最適化（カーブフィット）**は避けてください。
（公開ガイドライン上も、明確で誤解を生む表現の回避が推奨されます。
TradingView
）
活用アイデア（例）
相対優位×出来高質の改善が同時に起きた局面を抽出。
連続超過カウントで、相対の“粘り”や“伸び”をスクリーニング。
指数だけでなく、業種ETFやセクター指数を比較軸にしてローテーション把握。
免責
本スクリプトおよび説明は情報提供・教育目的です。投資助言・勧誘ではありません。市場リスク、流動性、スリッページ、データ仕様に起因する差異等は利用者の自己責任でご確認ください。TradingViewのハウスルール（広告禁止・独自性・言語一致・わかりやすさ）および公開ルールに準拠する形で記述しています。
Liquidity Stress Index SOFR - IORBLiquidity Stress Index (SOFR - IORB)
This indicator tracks the spread between the Secured Overnight Financing Rate (SOFR) and the Interest on Reserve Balances (IORB) set by the Federal Reserve.
A persistently positive spread may indicate funding stress or liquidity shortages in the repo market, as it suggests overnight lending rates exceed the risk-free rate banks earn at the Fed.
Useful for monitoring monetary policy transmission or market/liquidity stress.
Trend Following Reflectometry🧭 Trend Following Reflectometry (TFR)
Author: Stef Jonker
Version: Pine Script® v6
The Trend Following Reflectometry (TFR) indicator translates market behavior into the language of impedance and signal reflection theory, providing a unique way to measure trend strength, stability, and purity.
🧩 Summary
Trend Following Reflectometry acts as a trend-quality meter, helping traders identify when a trend is strong, efficient, and worth following — or when the market is too noisy to trust.
It blends physics-inspired logic with practical trading insight, offering both a directional oscillator and a trend stability filter in one tool.
⚙️ Concept
Inspired by electrical impedance matching, this tool compares the market’s characteristic impedance (Z₀) — its natural volatility-to-price behavior — with the load impedance (Zₗ), representing current trend momentum.
The interaction between these two produces a reflection coefficient (Gamma) and a VSWR ratio, which reveal how efficiently market trends are transmitting energy (moving smoothly) versus reflecting noise (becoming unstable).
📊 Core Components
Z₀ (Characteristic Impedance): Market baseline, derived from ATR and SMA.
Zₗ (Load Impedance): Trend momentum based on fast and slow EMAs.
Γ (Gamma – Reflection Coefficient): Measures the mismatch between Z₀ and Zₗ.
VSWR (Voltage Standing Wave Ratio): Quantifies trend purity — lower = cleaner trend.
Impedance Oscillator: Combines momentum and reflection to produce directional bias.
⚡ Gamma & VSWR Interpretation
Gamma (Γ) represents the reflection coefficient — how much of the market’s trend energy is being reflected instead of transmitted.
When Gamma is low, the market trend is smooth and efficient, moving with little resistance.
When Gamma is high, the market becomes unstable or overextended, signaling potential turbulence, exhaustion, or reversal pressure.
VSWR (Voltage Standing Wave Ratio) measures trend purity — how clean or distorted the current trend is.
A low VSWR indicates a well-aligned, steady trend that’s likely to continue smoothly.
A high VSWR suggests an unbalanced or noisy market, where trends may struggle to sustain or could soon reverse.
Together, Gamma and VSWR help identify how well the market’s current momentum aligns with its natural behavior — whether the trend is stable and efficient or reflecting instability beneath the surface.
Golden Cross & Death Cross DetectorThis script will:
Plot both moving averages on your chart
Show triangle markers when crossovers occur
Allow you to set up alerts
Let you choose between SMA and EMA
Customize the periods for both moving averages
6am Candle High/Low Indicator with Highlight6am Candle High/Low Indicator with Highlight
6am Candle High/Low Indicator with Highlight
6am Candle High/Low Indicator with Highlight
6am Candle High/Low Indicator with Highlight 6am Candle High/Low Indicator with Highlight
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.
Alerts Killzones + PD/WL/ML Levels (No Labels)This indicator automatically highlights the London and New York killzones and triggers alerts at key price levels — without adding any labels or text clutter to the chart.
Features:
Highlights London (10:00–13:00) and New York (15:00–17:00) sessions (GMT+3, Romania).
Draws and updates key levels automatically:
PDH / PDL – Previous Day High & Low
WH / WL – Previous Week High & Low
MH / ML – Previous Month High & Low
Alerts when price touches any of these levels.
Alerts at session opens and closes for both London and New York.
Clean interface – no labels or extra markers on chart.
Ideal for:
Traders who follow ICT concepts, session-based setups, or liquidity sweeps and want precise alerts without chart noise.
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.
Hello Crypto! Modern Combo Snapshot
Unified long/short analyzer blending EMA structure, SuperTrend, WaveTrend, QQE, and volume pressure.
Background shading flags “watch” and “ready” states; optional long/short modules let you focus on one side.
Alerts fire when every checklist item aligns, while the side-panel table summarizes trend, momentum, liquidity, and overall score in real time.
Indicator → Trend Analysis
Indicator → Momentum Oscillators
Indicator → Volume Indicators
Tags:
cryptocurrency, bitcoin, altcoins, trend-following, momentum, volume, ema, supertrend, intraday, swing-trading, alerts, checklist, trading-strategy, risk-management
Asia & London Session High/Low – EOD Segments (v4.5)What it does
Plots the Asia and London session high & low each day.
When a session ends, its high/low are locked (non-repainting) and drawn as horizontal segments that auto-extend to the end of that same day (no infinite rays).
Optional labels show the exact level at session close.
Toggle whether to keep prior days on the chart or auto-clear them on the first bar of a new day.
Why traders use it
Quickly see overnight liquidity levels that often act as magnets or barriers during the U.S. session.
Map session range extremes for breakout/reversal planning, partials, and invalidation.
Works great alongside VWAP, 8/20/200 MAs, or your NY session tools to build confluence.
How it works
You define the session windows (defaults: Asia 00:00–06:00, London 07:00–11:00).
While a session is active, the script tracks running high/low.
On the bar after the session ends, the level is finalized and drawn; the segment’s right edge updates each bar until EOD, then stops automatically.
Inputs
Session Timezone: “Exchange”, UTC, or a specific region (set this to match your venue).
Asia / London Session: editable HHMM-HHMM windows.
Show Asia / Show London: enable either/both sessions.
Keep history: keep or auto-delete previous days.
Show labels: price labels at session close.
Colors & width: customize high/low colors and line width.
Best practices
Use on intraday timeframes (1–60m).
For equities/futures, set timezone to your exchange (e.g., America/New_York). For FX/crypto, pick what matches your workflow.
Common tweak: London 08:00–12:00 local; Asia 00:00–05:00 or your broker’s definition.
Notes
Non-repainting: levels only print once the session is complete.
Designed to be light and reliable—no boxes, just clean lines and labels.
If you want NY session levels, midlines (50%), anchored stop-time, or alerts on touches, this script can be extended.
For educational use only. Not financial advice.
RVI Divergence Detector with Custom SMA Filter (v6)This script enhances the classic Relative Vigor Index (RVI) by integrating divergence detection with a user-configurable SMA filter applied directly to the RVI oscillator. The goal is to help traders identify high-probability reversal and continuation signals by combining momentum analysis with dynamic baseline filtering.
How it works:
- The RVI measures the conviction behind price moves by comparing closing vs. opening prices relative to the high-low range over a 10-period window.
- Divergences are detected when price makes a new high/low but the RVI does not:
- Regular Bullish: Price makes a lower low, RVI makes a higher low → potential reversal up.
- Hidden Bullish: Price makes a higher low, RVI makes a lower low → trend continuation.
- Inverse logic applies for bearish cases.
- A customizable SMA (default: 14 periods) is plotted on the RVI line. This acts as a dynamic reference to assess whether divergences occur in strong momentum zones (far from SMA) or neutral zones (near SMA), helping filter out weaker signals.
- Users can adjust:
- Pivot lookback range (min/max bars)
- SMA period (1–200)
- Visibility of bullish/bearish and hidden/regular divergences
Why this version adds value:
Unlike basic RVI scripts, this adaptation introduces a configurable trend filter (SMA) and clear visual labeling ("D" for regular, "H" for hidden) with colored lines (green/red) connecting oscillator and price pivots—making divergences instantly recognizable. The logic is optimized for both scalping (short SMA) and swing trading (longer SMA).
Credits:
Based on the original RVI divergence concept by madoqa. This is an open-source adaptation under the Mozilla Public License 2.0. No financial advice. Use at your own risk.
The Vishnu Zone Ver 2 by Dr. Sudhir Khollam## 📜 **The Vishnu Zone — Trade When the Brahma Zone Ends**
**Author:** Dr. Sudhir Khollam (SALSA© Method of Astrology & Market Psychology)
**Category:** Volatility Phase Detection / Bollinger Band Expansion Analysis
---
### 🔶 **Concept Overview**
In the **SALSA© Market Philosophy**, every market phase follows a cosmic rhythm —
* **Brahma Phase** represents *creation and expansion* (high volatility and strong directional movement).
* **Vishnu Phase** represents *maintenance and stability* (where expansion cools down and balanced opportunities appear).
**“The Vishnu Zone”** indicator identifies the exact moments when the **Brahma Phase ends** — signaling that the expansion has completed and the market is likely to enter a more stable, tradable state.
This is a **precision-timing indicator** that helps traders avoid entering at the end of impulsive phases and instead prepare for equilibrium-based trades (mean reversion, range setups, or steady trends).
---
### ⚙️ **How It Works**
The indicator measures **Bollinger Band Width (BBW)** to quantify expansion and contraction in volatility.
1. It calculates the **adaptive expansion threshold** using the average BBW over a rolling lookback period.
2. When the current BBW **drops below** this adaptive threshold **after being above it**, the script marks it as the **end of the Brahma Phase**.
3. This moment is shown visually as:
* 🕉 **“Vishnu” label** above the candle
* A **horizontal dotted line** extending for several bars
Together, these mark a **Vishnu Zone**, where the market transitions from expansion to consolidation — an ideal time for stabilization or entry planning.
---
### 📊 **Inputs & Settings**
| Parameter | Description |
| ---------------------------------- | ------------------------------------------------------------------------------ |
| **Bollinger Band Length** | The number of bars used for SMA and standard deviation (default 20). |
| **Bollinger Multiplier** | Determines the width of Bollinger Bands (default 2.0). |
| **Adaptive Lookback Period** | Rolling window to calculate the mean BBW for dynamic adjustment (default 150). |
| **Expansion Multiplier** | Multiplies the mean BBW to define the expansion threshold (default 1.35). |
| **Horizontal Line Extension Bars** | Number of bars to extend the Vishnu Zone line into the future (default 40). |
| **Show End-of-Brahma Labels?** | Toggle 🕉 labels on/off. |
| **Show Horizontal Lines?** | Toggle Vishnu Zone lines on/off. |
---
### 🔔 **Alerts**
When the **Brahma Phase ends**, the indicator triggers an alert:
> *“Brahma Phase Ends, Vishnu has taken over.”*
This helps traders receive real-time notification of volatility contraction and possible entry zones.
---
### 🧠 **Best Practices**
* Works effectively on **5-minute to 1-hour timeframes** for intraday trading.
* Best paired with **momentum or volume filters** to confirm trend exhaustion.
* Avoid entering during rapid expansion (Brahma phase). Wait for a Vishnu signal to ensure market stabilization.
---
### 🌌 **Philosophical Interpretation (SALSA© Principle)**
Just as Vishnu sustains the universe after Brahma’s creation, the market too enters a **maintenance phase** after every burst of expansion.
Recognizing this shift allows traders to align with **cosmic rhythm and price psychology**, not just technical metrics.
---
### 🧩 **Summary**
✅ Detects when expansion volatility ends
✅ Marks transition zones between impulsive and stable phases
✅ Sends real-time alerts
✅ Adaptive and self-adjusting across markets and assets
✅ Simple, clean visualization — ideal for disciplined trading
---
### ⚡ **Use Case**
Perfect for traders who:
* Prefer **low-risk entries** after volatility spikes
* Trade **mean reversion**, **range breakouts**, or **volatility collapses**
* Believe in the **cyclic nature of market energy**
---
Modern Combo Crypto SuiteBlends long and short playbooks in one overlay with quick toggles.
Tracks EMA stacks, SuperTrend, WaveTrend, QQE, and volume to score bias.
Colors the chart background when watch/ready conditions align.
Fires alerts for imminent or fully aligned long/short setups.
Displays a live checklist table summarizing trend, momentum, and volume confidence.
ADR + MOVE BoxADR + Move 20 day average Box for any ticker. Calculates the average daily range as well as the absolute delta from open to close. For Full day as well as NY session only
Previous day high lowThis script Identifies and draw Previous day High low on 15 min Intra day chart
Multi-Timeframe Support & ResistanceThis indicator automatically plots dynamic support and resistance levels across multiple timeframes — including 1H, 4H, 1D, 1W, 1M, and the current chart timeframe. Each level is color-coded for clarity and extends across the chart to highlight key price zones.
**Key Features:**
- ⏱ Multi-timeframe analysis: 6 configurable timeframes
- 🎨 Custom color and style settings for each timeframe
- 📏 Adjustable number of levels per timeframe
- 🧼 Clean chart layout with no duplicate lines
- 🔄 Auto-refresh every 10 bars for up-to-date levels
Support and resistance levels are calculated using historical high/low ranges and evenly distributed across the selected lookback period. This helps traders identify confluence zones, breakout targets, and reversal areas with precision.
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.
RSI to Price Projection PanelThis indicator calculates the current RSI based on the closing price and projects estimated prices for user-defined RSI target levels. Results are displayed in a table at the top-right corner of the chart.
Advanced HMM - 3 States CompleteHidden Markov Model
Aconsistent challenge for quantitative traders is the frequent behaviour modification of financial
markets, often abruptly, due to changing periods of government policy, regulatory environment
and other macroeconomic effects. Such periods are known as market regimes. Detecting such
changes is a common, albeit difficult, process undertaken by quantitative market participants.
These various regimes lead to adjustments of asset returns via shifts in their means, variances,
autocorrelation and covariances. This impacts the effectiveness of time series methods that rely
on stationarity. In particular it can lead to dynamically-varying correlation, excess kurtosis ("fat
tails"), heteroskedasticity (volatility clustering) and skewed returns.
There is a clear need to effectively detect these regimes. This aids optimal deployment of
quantitative trading strategies and tuning the parameters within them. The modeling task then
becomes an attempt to identify when a new regime has occurred adjusting strategy deployment,
risk management and position sizing criteria accordingly.
A principal method for carrying out regime detection is to use a statistical time series tech
nique known as a Hidden Markov Model . These models are well-suited to the task since they
involve inference on "hidden" generative processes via "noisy" indirect observations correlated
to these processes. In this instance the hidden, or latent, process is the underlying regime state,
while the asset returns are the indirect noisy observations that are influenced by these states.
MAIN FEATURES OF THE INDICATOR
The "Advanced HMM - 3 States Complete" indicator is an advanced technical analysis tool that uses Hidden Markov Model (HMM) to identify three main market regimes: BULL, BEAR, and SIDEWAYS.
🎯 KEY FEATURES:
1. HMM-based Trend Detection
3 market states: Bull (0), Bear (1), Sideways (2)
Dynamic probabilities: Calculates probability for each state based on price data
Transition matrix: Models state transitions between regimes
2. Analytical Features
Price volatility: Log returns and standard deviation
Momentum: Rate of Change (ROC)
Volume: Volume ratio vs moving average
Data normalization: Standardizes features to common scale
3. Visual Trading Signals
text
📍 BUY Signals:
- Green upward triangle below bars
- "LONG" label in green
📍 SELL Signals:
- Red downward triangle above bars
- "SHORT" label in red
📍 EXIT Signals:
- Orange X marks when transitioning to sideways
4. Information Display
Probability table (top-right): Shows percentage for each state
State label: Current regime with probability percentages
Chart background color: Reflects dominant market state
5. Automated Alerts
Alerts when new Bull/Bear market detected
Alerts when market transitions to sideways
Configurable TradingView notifications
6. Customizable Parameters
pinescript
length: 100 // Lookback period
smoothing_period: 20 // Probability smoothing
volatility_threshold: 0.5 // Volatility threshold
💡 PRACTICAL APPLICATIONS:
Identify primary trends with quantified probabilities
Entry/exit signals based on state transitions
Risk management during sideways markets
Trend confirmation when combined with other indicators
This indicator is particularly useful for market regime analysis and identifying trend transition points using advanced statistical probability methods.
🔧 TECHNICAL IMPLEMENTATION:
Composite observation: Weighted combination of returns (40%), momentum (30%), and volatility (30%)
Gaussian emission probabilities: Different distributions for each state
Manual HMM updates: Avoids matrix computation limitations in Pine Script
Real-time smoothing: EMA applied to state probabilities
The indicator provides institutional-grade regime detection in a visually intuitive package suitable for both discretionary and systematic traders.
