Mutanabby_AI | Ultimate Algo | Remastered+Overview
The Mutanabby_AI Ultimate Algo Remastered+ represents a sophisticated trend-following system that combines Supertrend analysis with multiple moving average confirmations. This comprehensive indicator is designed specifically for identifying high-probability trend continuation and reversal opportunities across various market conditions.
Core Algorithm Components
**Supertrend Foundation**: The primary signal generation relies on a customizable Supertrend indicator with adjustable sensitivity (1-20 range). This adaptive trend-following tool uses Average True Range calculations to establish dynamic support and resistance levels that respond to market volatility.
**SMA Confirmation Matrix**: Multiple Simple Moving Averages (SMA 4, 5, 9, 13) provide layered confirmation for signal strength. The algorithm distinguishes between regular signals and "Strong" signals based on SMA 4 vs SMA 5 relationship, offering traders different conviction levels for position sizing.
**Trend Ribbon Visualization**: SMA 21 and SMA 34 create a visual trend ribbon that changes color based on their relationship. Green ribbon indicates bullish momentum while red signals bearish conditions, providing immediate visual trend context.
**RSI-Based Candle Coloring**: Advanced 61-tier RSI system colors candles with gradient precision from deep red (RSI ≤20) through purple transitions to bright green (RSI ≥79). This visual enhancement helps traders instantly assess momentum strength and overbought/oversold conditions.
Signal Generation Logic
**Buy Signal Criteria**:
- Price crosses above Supertrend line
- Close price must be above SMA 9 (trend confirmation)
- Signal strength determined by SMA 4 vs SMA 5 relationship
- "Strong Buy" when SMA 4 ≥ SMA 5
- Regular "Buy" when SMA 4 < SMA 5
**Sell Signal Criteria**:
- Price crosses below Supertrend line
- Close price must be below SMA 9 (trend confirmation)
- Signal strength based on SMA relationship
- "Strong Sell" when SMA 4 ≤ SMA 5
- Regular "Sell" when SMA 4 > SMA 5
Advanced Risk Management System
**Automated TP/SL Calculation**: The indicator automatically calculates stop loss and take profit levels using ATR-based measurements. Risk percentage and ATR length are fully customizable, allowing traders to adapt to different market conditions and personal risk tolerance.
**Multiple Take Profit Targets**:
- 1:1 Risk-Reward ratio for conservative profit taking
- 2:1 Risk-Reward for balanced trade management
- 3:1 Risk-Reward for maximum profit potential
**Visual Risk Display**: All risk management levels appear as both labels and optional trend lines on the chart. Customizable line styles (solid, dashed, dotted) and positioning ensure clear visualization without chart clutter.
**Dynamic Level Updates**: Risk levels automatically recalculate with each new signal, maintaining current market relevance throughout position lifecycles.
Visual Enhancement Features
**Customizable Display Options**: Toggle trend ribbon, TP/SL levels, and risk lines independently. Decimal precision adjustments (1-8 decimal places) accommodate different instrument price formats and personal preferences.
**Professional Label System**: Clean, informative labels show entry points, stop losses, and take profit targets with precise price levels. Labels automatically position themselves for optimal chart readability.
**Color-Coded Momentum**: The gradient RSI candle coloring system provides instant visual feedback on momentum strength, helping traders assess market energy and potential reversal zones.
Implementation Strategy
**Timeframe Optimization**: The algorithm performs effectively across multiple timeframes, with higher timeframes (4H, Daily) providing more reliable signals for swing trading. Lower timeframes work well for day trading with appropriate risk adjustments.
**Sensitivity Adjustment**: Lower sensitivity values (1-5) generate fewer but higher-quality signals, ideal for conservative approaches. Higher sensitivity (15-20) increases signal frequency for active trading styles.
**Risk Management Integration**: Use the automated risk calculations as baseline parameters, adjusting risk percentage based on account size and market conditions. The 1:1, 2:1, 3:1 targets enable systematic profit-taking strategies.
Market Application
**Trend Following Excellence**: Primary strength lies in capturing significant trend movements through the Supertrend foundation with SMA confirmation. The dual-layer approach reduces false signals common in single-indicator systems.
**Momentum Assessment**: RSI-based candle coloring provides immediate momentum context, helping traders assess signal strength and potential continuation probability.
**Range Detection**: The trend ribbon helps identify ranging conditions when SMA 21 and SMA 34 converge, alerting traders to potential breakout opportunities.
Performance Optimization
**Signal Quality**: The requirement for both Supertrend crossover AND SMA 9 confirmation significantly improves signal reliability compared to basic trend-following approaches.
**Visual Clarity**: The comprehensive visual system enables rapid market assessment without complex calculations, ideal for traders managing multiple instruments.
**Adaptability**: Extensive customization options allow fine-tuning for specific markets, trading styles, and risk preferences while maintaining the core algorithm integrity.
## Non-Repainting Design
**Educational Note**: This indicator uses standard TradingView functions (Supertrend, SMA, RSI) with normal behavior patterns. Real-time updates on current candles are expected and standard across all technical indicators. Historical signals on closed candles remain fixed and unchanged, ensuring reliable backtesting and analysis.
**Signal Confirmation**: Final signals are confirmed only when candles close, following standard technical analysis principles. The algorithm provides clear distinction between developing signals and confirmed entries.
Technical Specifications
**Supertrend Parameters**: Default sensitivity of 4 with ATR length of 11 provides balanced signal generation. Sensitivity range from 1-20 allows adaptation to different market volatilities and trading preferences.
**Moving Average Configuration**: SMA periods of 8, 9, and 13 create multi-layered trend confirmation, while SMA 21 and 34 form the visual trend ribbon for broader market context.
**Risk Management**: ATR-based calculations with customizable risk percentage ensure dynamic adaptation to market volatility while maintaining consistent risk exposure principles.
Recommended Settings
**Conservative Approach**: Sensitivity 4-5, RSI length 14, higher timeframes (4H, Daily) for swing trading with maximum signal reliability.
**Active Trading**: Sensitivity 6-8, RSI length 8-10, intermediate timeframes (1H) for balanced signal frequency and quality.
**Scalping Setup**: Sensitivity 10-15, RSI length 5-8, lower timeframes (15-30min) with enhanced risk management protocols.
## Conclusion
The Mutanabby_AI Ultimate Algo Remastered+ combines proven trend-following principles with modern visual enhancements and comprehensive risk management. The algorithm's strength lies in its multi-layered confirmation approach and automated risk calculations, providing both novice and experienced traders with clear signals and systematic trade management.
Success with this system requires understanding the relationship between signal strength indicators and adapting sensitivity settings to match current market conditions. The comprehensive visual feedback system enables rapid decision-making while the automated risk management ensures consistent trade parameters.
Practice with different sensitivity settings and timeframes to optimize performance for your specific trading style and risk tolerance. The algorithm's systematic approach provides an excellent framework for disciplined trend-following strategies across various market environments.
Cerca negli script per "美国财长：10年期美债收益率"
ai quant oculusAI QUANT OCULUS
Version 1.0 | Pine Script v6
Purpose & Innovation
AI QUANT OCULUS integrates four distinct technical concepts—exponential trend filtering, adaptive smoothing, momentum oscillation, and Gaussian smoothing—into a single, cohesive system that delivers clear, objective buy and sell signals along with automatically plotted stop-loss and three profit-target levels. This mash-up goes beyond a simple EMA crossover or standalone TRIX oscillator by requiring confluence across trend, adaptive moving averages, momentum direction, and smoothed price action, reducing false triggers and focusing on high‐probability turning points.
How It Works & Why Its Components Matter
Trend Filter: EMA vs. Adaptive MA
EMA (20) measures the prevailing trend with fixed sensitivity.
Adaptive MA (also EMA-based, length 10) approximates a faster-responding moving average, standing in for a KAMA-style filter.
Bullish bias requires AMA > EMA; bearish bias requires AMA < EMA. This ensures signals align with both the underlying trend and a more nimble view of recent price action.
Momentum Confirmation: TRIX
Calculates a triple-smoothed EMA of price over TRIX Length (15), then converts it to a percentage rate-of-change oscillator.
Positive TRIX reinforces bullish entries; negative TRIX reinforces bearish entries. Using TRIX helps filter whipsaws by focusing on sustained momentum shifts.
Gaussian Price Smoother
Applies two back-to-back 5-period EMAs to the price (“gaussian” smoothing) to remove short-term noise.
Price above the smoothed line confirms strength for longs; below confirms weakness for shorts. This layer avoids entries on erratic spikes.
Confluence Signals
Buy Signal (isBull) fires only when:
AMA > EMA (trend alignment)
TRIX > 0 (momentum support)
Close > Gaussian (price strength)
Sell Signal (isBear) fires under the inverse conditions.
Requiring all three conditions simultaneously sharply reduces false triggers common to single-indicator systems.
Automatic Risk & Reward Plotting
On each new buy or sell signal (edge detection via not isBull or not isBear ), the script:
Stores entryPrice at the signal bar’s close.
Draws a stop-loss line at entry minus ATR(14) × Stop Multiplier (1.5) by default.
Plots three profit-target lines at entry plus ATR × Target Multiplier (1×, 1.5×, and 2×).
All previous labels and lines are deleted on each new signal, keeping the chart uncluttered and focusing only on the current trade.
Inputs & Customization
Input Description Default
EMA Length Period for the main trend EMA 20
Adaptive MA Length Period for the faster adaptive EM A substitute 10
TRIX Length Period for the triple-smoothed momentum oscillator 15
Dominant Cycle Length (Reserved) 40
Stop Multiplier ATR multiple for stop-loss distance 1.5
Target Multiplier ATR multiple for first profit target 1.5
Show Buy/Sell Signals Toggle on-chart labels for entry signals On
How to Use
Apply to Chart: Best on 15 m–1 h timeframes for swing entries or 5 m for agile scalps.
Wait for Full Confluence:
Look for the AMA to cross above/below the EMA and verify TRIX and Gaussian conditions on the same bar.
A bright “LONG” or “SHORT” label marks your entry.
Manage the Trade:
Place your stop where the red or green SL line appears.
Scale or exit at the three yellow TP1/TP2/TP3 lines, automatically drawn by volatility.
Repeat Cleanly: Each new signal clears prior annotations, ensuring you only track the active setup.
Why This Script Stands Out
Multi-Layer Confluence: Trend, momentum, and noise-reduction must all align, addressing the weaknesses of single-indicator strategies.
Automated Trade Management: No manual plotting—stop and target lines appear seamlessly with each signal.
Transparent & Customizable: All logic is open, adjustable, and clearly documented, allowing traders to tweak lengths and multipliers to suit different instruments.
Disclaimer
No indicator guarantees profit. Always backtest AI QUANT OCULUS extensively, combine its signals with your own analysis and risk controls, and practice sound money management before trading live.
Smooth Cloud + RSI Liquidity Spectrum + Zig Zag Volume ProfileSmooth Cloud + RSI Liquidity Spectrum + Zig Zag++ Volume Profile" Indicator
| Advanced Trend & Liquidity Analysis.
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📌 Key Features & Enhancements (Zig Zag++)
This advanced indicator combines **trend-following moving averages, RSI momentum with liquidity factors, and an improved Zig Zag++ algorithm with volume profiling** for precise swing detection.
🔹 Zig Zag++ Upgrades:
✅ **Dynamic Reversal Detection** – Adapts to volatility using percentage-based pivots.
✅ **Volume-Weighted Swing Points** – Highlights high-liquidity turning points.
✅ **Multi-Timeframe Confirmation** – Uses historical pivots for stronger signals.
✅ **Volume Profile Clustering** – Reveals key support/resistance zones based on traded volume.
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📊 Indicator Components Breakdown
1️⃣ Smooth Cloud (Trend Filter)
- **Fast MA (20-period) & Slow MA (50-period)** – Configurable as EMA, SMA, or WMA.
- **Cloud Coloring** – Green when fast MA > slow MA (bullish), red otherwise (bearish).
- **Purpose**: Acts as a trend filter—only take trades in the direction of the cloud.
2️⃣ RSI Liquidity Spectrum (Momentum + Volume)
- **RSI (14-period default)** – Standard momentum oscillator.
- **Liquidity-Adjusted Momentum** = `(RSI + ROC(RSI,3)) * (Volume / SMA(Volume, RSI Length))`
- **Purpose**: Identifies overbought/oversold conditions with volume confirmation (high volume = stronger signal).
3️⃣ Zig Zag++ (Swing Detection & Volume Profiling)
📈 Zig Zag Logic:**
- **Percentage-Based Reversals** (default: 5%) – Only plots swings exceeding this threshold.
- **Pivot Tracking** – Stores price & bar index of each swing point in arrays.
- **Dynamic Line Drawing** – Connects swing points with yellow trendlines.
📊 Volume Profile at Swings:
- **Lookback Period** (200 bars default) – Analyzes volume distribution between Zig Zag turns.
- **10-Price Bin Clustering** – Splits the price range into 10 levels and calculates traded volume at each.
- **Transparency Scaling** – Higher volume zones appear darker (stronger support/resistance).
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🎯 Step-by-Step Trading Strategies
📈 Strategy 1: Trend-Following with RSI Liquidity Confirmation**
1. **Enter Long** when:
- Smooth Cloud is **green** (fast MA > slow MA).
- RSI Liquidity Momentum crosses above **30** (bullish momentum + volume).
- Price pulls back to the **Volume Profile high-volume zone** (demand area).
2. **Enter Short** when:
- Smooth Cloud is **red** (fast MA < slow MA).
- RSI Liquidity Momentum crosses below **70** (bearish momentum + volume).
- Price rallies into the **Volume Profile high-volume zone** (supply area).
3. **Exit** when:
- Zig Zag++ detects a new reversal (5% move against position).
- RSI Liquidity Momentum crosses back mid-level (50).
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📉 Strategy 2: Swing Trading with Zig Zag++ Pivots**
1. **Buy at Swing Lows** when:
- Zig Zag++ prints a **higher low** (bullish structure).
- Volume Profile shows **strong absorption** (high volume at the low).
- RSI Liquidity Momentum is rising from oversold (<30).
2. **Sell at Swing Highs** when:
- Zig Zag++ prints a **lower high** (bearish structure).
- Volume Profile shows **distribution** (high volume at the top).
- RSI Liquidity Momentum is falling from overbought (>70).
3. **Stop Loss**:
- Below the recent Zig Zag low (for longs).
- Above the recent Zig Zag high (for shorts).
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📌 Additional Enhancements (Pro Tips)**
- **Combine with Higher Timeframe (HTF) Cloud** – Use a 4H/1D cloud to filter trades.
- **Divergence Detection** – Hidden bullish/bearish divergences between Zig Zag & RSI Liquidity.
- **Volume Spike Confirmation** – Only trade if volume exceeds SMA(volume, 20) at reversal points.
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🚀 Conclusion
This **all-in-one indicator** provides:
✔ **Trend direction** (Smooth Cloud)
✔ **Momentum + Liquidity strength** (RSI Spectrum)
✔ **Precise swing points** (Zig Zag++)
✔ **Volume-based S/R zones** (Profile Clustering)
Best used on **15M-4H timeframes** for swing/day trading. Adjust parameters based on asset volatility.
MSTY-WNTR Rebalancing SignalMSTY-WNTR Rebalancing Signal
## Overview
The **MSTY-WNTR Rebalancing Signal** is a custom TradingView indicator designed to help investors dynamically allocate between two YieldMax ETFs: **MSTY** (YieldMax MSTR Option Income Strategy ETF) and **WNTR** (YieldMax Short MSTR Option Income Strategy ETF). These ETFs are tied to MicroStrategy (MSTR) stock, which is heavily influenced by Bitcoin's price due to MSTR's significant Bitcoin holdings.
MSTY benefits from upward movements in MSTR (and thus Bitcoin) through a covered call strategy that generates income but caps upside potential. WNTR, on the other hand, provides inverse exposure, profiting from MSTR declines but losing in rallies. This indicator uses Bitcoin's momentum and MSTR's relative strength to signal when to hold MSTY (bullish phases), WNTR (bearish phases), or stay neutral, aiming to optimize returns by switching allocations at key turning points.
Inspired by strategies discussed in crypto communities (e.g., X posts analyzing MSTR-linked ETFs), this indicator promotes an active rebalancing approach over a "set and forget" buy-and-hold strategy. In simulated backtests over the past 12 months (as of August 4, 2025), the optimized version has shown potential to outperform holding 100% MSTY or 100% WNTR alone, with an illustrative APY of ~125% vs. ~6% for MSTY and ~-15% for WNTR in one scenario.
**Important Disclaimer**: This is not financial advice. Past performance does not guarantee future results. Always consult a financial advisor. Trading involves risk, and you could lose money. The indicator is for educational and informational purposes only.
## Key Features
- **Momentum-Based Signals**: Uses a Simple Moving Average (SMA) on Bitcoin's price to detect bullish (price > SMA) or bearish (price < SMA) trends.
- **RSI Confirmation**: Incorporates MSTR's Relative Strength Index (RSI) to filter signals, avoiding overbought conditions for MSTY and oversold for WNTR.
- **Visual Cues**:
- Green upward triangle for "Hold MSTY".
- Red downward triangle for "Hold WNTR".
- Yellow cross for "Switch" signals.
- Background color: Green for MSTY, red for WNTR.
- **Information Panel**: A table in the top-right corner displays real-time data: BTC Price, SMA value, MSTR RSI, and current Allocation (MSTY, WNTR, or Neutral).
- **Alerts**: Configurable alerts for holding MSTY, holding WNTR, or switching.
- **Optimized Parameters**: Defaults are tuned (SMA: 10 days, RSI: 15 periods, Overbought: 80, Oversold: 20) based on simulations to reduce whipsaws and capture trends effectively.
## How It Works
The indicator's logic is straightforward yet effective for volatile assets like Bitcoin and MSTR:
1. **Primary Trigger (Bitcoin Momentum)**:
- Calculate the SMA of Bitcoin's closing price (default: 10-day).
- Bullish: Current BTC price > SMA → Potential MSTY hold.
- Bearish: Current BTC price < SMA → Potential WNTR hold.
2. **Secondary Filter (MSTR RSI Confirmation)**:
- Compute RSI on MSTR stock (default: 15-period).
- For bullish signals: If RSI > Overbought (80), signal Neutral (avoid overextended rallies).
- For bearish signals: If RSI < Oversold (20), signal Neutral (avoid capitulation bottoms).
3. **Allocation Rules**:
- Hold 100% MSTY if bullish and not overbought.
- Hold 100% WNTR if bearish and not oversold.
- Neutral otherwise (e.g., during choppy or extreme markets) – consider holding cash or avoiding trades.
4. **Rebalancing**:
- Switch signals trigger when the hold changes (e.g., from MSTY to WNTR).
- Recommended frequency: Weekly reviews or on 5% BTC moves to minimize trading costs (aim for 4-6 trades/year).
This approach leverages Bitcoin's influence on MSTR while mitigating the risks of MSTY's covered call drag during downtrends and WNTR's losses in uptrends.
## Setup and Usage
1. **Chart Requirements**:
- Apply this indicator to a Bitcoin chart (e.g., BTCUSD on Binance or Coinbase, daily timeframe recommended).
- Ensure MSTR stock data is accessible (TradingView supports it natively).
2. **Adding to TradingView**:
- Open the Pine Editor.
- Paste the script code.
- Save and add to your chart.
- Customize inputs if needed (e.g., adjust SMA/RSI lengths for different timeframes).
3. **Interpretation**:
- **Green Background/Triangle**: Allocate 100% to MSTY – Bitcoin is in an uptrend, MSTR not overbought.
- **Red Background/Triangle**: Allocate 100% to WNTR – Bitcoin in downtrend, MSTR not oversold.
- **Yellow Switch Cross**: Rebalance your portfolio immediately.
- **Neutral (No Signal)**: Panel shows "Neutral" – Hold cash or previous position; reassess weekly.
- Monitor the panel for key metrics to validate signals manually.
4. **Backtesting and Strategy Integration**:
- Convert to a strategy script by changing `indicator()` to `strategy()` and adding entry/exit logic for automated testing.
- In simulations (e.g., using Python or TradingView's backtester), it has outperformed buy-and-hold in volatile markets by ~100-200% relative APY, but results vary.
- Factor in fees: ETF expense ratios (~0.99%), trading commissions (~$0.40/trade), and slippage.
5. **Risk Management**:
- Use with a diversified portfolio; never allocate more than you can afford to lose.
- Add stop-losses (e.g., 10% trailing) to protect against extreme moves.
- Rebalance sparingly to avoid over-trading in sideways markets.
- Dividends: Reinvest MSTY/WNTR payouts into the current hold for compounding.
## Performance Insights (Simulated as of August 4, 2025)
Based on synthetic backtests modeling the last 12 months:
- **Optimized Strategy APY**: ~125% (by timing switches effectively).
- **Hold 100% MSTY APY**: ~6% (gains from BTC rallies offset by downtrends).
- **Hold 100% WNTR APY**: ~-15% (losses in bull phases outweigh bear gains).
In one scenario with stronger volatility, the strategy achieved ~4533% APY vs. 10% for MSTY and -34% for WNTR, highlighting its potential in dynamic markets. However, these are illustrative; real results depend on actual BTC/MSTR movements. Test thoroughly on historical data.
## Limitations and Considerations
- **Data Dependency**: Relies on accurate BTC and MSTR data; delays or gaps can affect signals.
- **Market Risks**: Bitcoin's volatility can lead to false signals (whipsaws); the RSI filter helps but isn't perfect.
- **No Guarantees**: This indicator doesn't predict the future. MSTR's correlation to BTC may change (e.g., due to regulatory events).
- **Not for All Users**: Best for intermediate/advanced traders familiar with ETFs and crypto. Beginners should paper trade first.
- **Updates**: As of August 4, 2025, this is version 1.0. Future updates may include volume filters or EMA options.
If you find this indicator useful, consider leaving a like or comment on TradingView. Feedback welcome for improvements!
5 SMA/EMA and Zigzag- Chỉ báo gộp của 2 chỉ báo 5 đường MA/EMA/WMA và đường zigzag
- Các thông số đường EMA và zigzag mặc định đã được đặt theo thông số khoá học Fibo
- 5 đường MA có thể lựa chọn loại đường SMA, EMA, WMA, VWM và được bật mặc định 3 đường EMA 8, 13, 21 và có thể thay đổi màu đường định dạng đường. Và giao cắt của đường EMA 10 và 21 được đánh dấu bằng các dấu chấm tròn.
- Đường zigzag được đặt thông số mặc định là 3.
Màu đường và độ dày đường zigzag có thể thay đổi từ bảng lựa chọn, kiểu đường thì phải thay đổi trong code.
- Bảng giá trị RSI, MA RSI thì đang để 7 khung thời gian. Muốn tắt bớt thì phải tắt trong code
Và giá trị của RSI và MA RSI sẽ không đúng với các Tf 5, 15, 30 nếu Tf của chart lớn hơn TF này (do tradingview) . Vd TF chart là 15m thì giá trị RSI trong bảng của khung 5m không đúng, Tf chart là 60m thì giá trị RSI của 30m, 15m , 5m trong bảng là không đúng. TF chart là 4H thì giá trị trong bảng của khung 5m, 15m 30m không đúng, còn giá trị của 1H, 2H, 3H vẫn đúng.
This is a combined indicator of two separate indicators: a 5-line MA/EMA/WMA indicator and a ZigZag indicator.
The default parameters for the EMA and ZigZag lines are set according to the Fibo course settings.
For the 5 moving averages, you can choose between SMA, EMA, WMA, and VWM. By default, 3 EMA lines (8, 13, 21) are enabled, and their colors and styles can be customized. The crossover between EMA 10 and EMA 21 is marked with circular dots.
The default setting for the ZigZag line is 3.
The color and thickness of the ZigZag line can be changed via the input panel, but the line style must be modified in the code.
The RSI and MA RSI value table is currently set to display across 7 timeframes. To reduce the number of timeframes shown, you will need to edit the code manually.
Note: The RSI and MA RSI values will not be accurate for timeframes 5m, 15m, and 30m if the chart's timeframe is higher than these (due to limitations in TradingView).
For example:
If the chart is on 15m, the RSI value for the 5m frame in the table will be incorrect.
If the chart is on 60m, then RSI values for 30m, 15m, and 5m will be incorrect.
If the chart is on 4H, the RSI values for 5m, 15m, and 30m will be incorrect, but the values for 1H, 2H, and 3H will still be correct.
Bollinger Bands + LWMA + EMA ComboThe BBMA strategy from Omaly Ally, this contains all the MA 5/ 10 high and MA 5/ 10 low, it also has EMA 50, 100 and 200
Hunting Bollinger Bands for scalping📌 Bollinger Band Reversal BUY/SELL Indicator
Name: Hunting Bollinger Bands for scalping
Purpose: Displays reversal signals for short-term scalping in range-bound markets.
Target Users: Scalpers and day traders, especially for trading Gold (XAU/USD).
Recommended Target: Works well for scalping approximately $3 price movements on Gold.
Core Logic:
Detects excessive price deviation using Bollinger Bands (±2σ).
Filters out excessive signals with a bar interval limiter.
Displays clear and simple BUY/SELL labels for entry timing.
📌 Signal Conditions
BUY
Price closes below the Lower Bollinger Band.
At least the specified number of bars has passed since the previous signal.
Displays a “BUY” label below the bar.
SELL
Price closes above the Upper Bollinger Band.
At least the specified number of bars has passed since the previous signal.
Displays a “SELL” label above the bar.
📌 Parameters
Parameter Description Default
Bollinger Band Length (bbLength) Period for Bollinger Band calculation 20
Standard Deviation (bbStdDev) Standard deviation multiplier for band width 2.0
Signal Interval (barLimit) Minimum bar interval to avoid repeated signals 10
📌 How to Use
Add the indicator to your chart; Bollinger Bands and BUY/SELL labels will appear.
When a signal appears, confirm price reaction and enter a scalp trade (around $3 for Gold is recommended).
Adjust the “Signal Interval (barLimit)” to control signal frequency.
Avoid using it during high-impact news events or strong trending markets.
📌 Best Market Conditions
Range-bound markets
Scalping small price movements (~$3)
Low-volatility sessions (e.g. Asian session for Gold)
📌 Notes
May generate frequent signals during strong trends, leading to potential losses.
Can be combined with other indicators (e.g. 200 MA, RSI, VWAP) for higher accuracy.
Signals are for reference only and should not be used as the sole trading decision factor.
📌 ボリンジャーバンド逆張りBUY/SELL インジケーター解説
名前：Hunting Bollinger Bands for scalping
目的：レンジ相場での短期的な反発を狙った逆張りシグナルを表示
対象ユーザー：スキャルピングやデイトレードで、特にゴールド(XAU/USD)での小幅な値動きを狙うトレーダー
推奨利幅：ゴールドでおよそ 3ドル前後 を目安にスキャルピングを行うと有効
メインロジック：
ボリンジャーバンド（±2σ）で過剰な価格乖離を検出
バー間隔フィルターで過剰シグナルを制御
BUY/SELLラベルで視覚的にシンプルなエントリーポイントを表示
📌 シグナル条件
BUY（買いシグナル）
現在価格が ボリンジャーバンド下限（Lower Band）を下回った時
前回シグナルから指定したバー数以上経過
この条件を満たした場合、ローソク足下に「BUY」ラベルを表示します。
SELL（売りシグナル）
現在価格が ボリンジャーバンド上限（Upper Band）を上回った時
前回シグナルから指定したバー数以上経過
この条件を満たした場合、ローソク足上に「SELL」ラベルを表示します。
📌 パラメータ
項目 説明 初期値
ボリンジャーバンド期間 (bbLength) ボリンジャーバンド計算の期間 20
標準偏差 (bbStdDev) バンド幅を決める標準偏差 2.0
シグナル間隔 (barLimit) シグナルの連続表示を防止する最小バー間隔 10
📌 使い方
インジケーターをチャートに追加すると、ボリンジャーバンドとBUY/SELLラベルが表示されます
シグナルが出たら、反発確認後にスキャルピングエントリー（ゴールドなら約3ドルを目安に）
「シグナル間隔（barLimit）」を調整して、シグナルの過剰表示を防ぐ
経済指標発表や強いトレンド発生時は使用を控える
📌 このインジケーターが向いている相場
レンジ相場
小さな値幅（約3ドル前後）を狙うスキャルピング
トレンドが弱い横ばいの時間帯（例：アジア時間のゴールドなど）
📌 注意点
強いトレンド相場では、逆張りシグナルが連続的に発生し、損切りが増える可能性あり
200MAやRSI、VWAPなど他の指標と組み合わせることで精度を高められる
シグナルは参考用であり、単独での売買判断は推奨されない
Contrarian Investor📌 Indicator Overview
Name:Contrarian investor
Purpose: Identify oversold or overbought conditions for simple reversal trades.
Key Features:
Uses the 200-period moving average (200MA) to determine the market trend.
Uses RSI to detect oversold and overbought levels.
Includes a signal interval filter to prevent excessive signals.
📌 Signal Conditions
BUY (Reversal Buy)
Price is below the 200MA
RSI is below the oversold threshold (default: 30)
When both conditions are met, a "BUY" label is plotted below the bar.
SELL (Reversal Sell)
Price is above the 200MA
RSI is above the overbought threshold (default: 70)
When both conditions are met, a "SELL" label is plotted above the bar.
📌 Parameters
MA Length: Default 200 (used for trend detection)
RSI Length: Default 14
RSI Oversold: Default 30 (trigger for BUY signals)
RSI Overbought: Default 70 (trigger for SELL signals)
Signal Interval (bars): Default 10 (prevents duplicate signals)
📌 How to Use
Use the 200MA to confirm the trend direction.
Wait for RSI to reach extreme levels (oversold or overbought).
When a "BUY" or "SELL" label appears, consider a potential entry.
For better accuracy, combine with support/resistance or price action confirmation.
📌 Notes
This indicator is designed as a supplementary tool, not a standalone entry system.
Adjust the signal interval based on your trading style (e.g., shorter for scalping, longer for swing trading).
In strong trending markets, reversal signals may fail frequently, so additional confluence is recommended.
You need to adjust the settings depending on the market conditions.
This indicator is not intended for use during strong trending markets, such as after major economic news releases.
It is best suited for range-bound markets and scalping within a few-dollar price range.
📌 インジケーターの概要
名前：Contrarian investor
目的：過剰に売られた/買われたタイミングでの逆張りシグナルを簡単に確認
特徴：
200MAを基準にトレンド方向を判定
RSIで売られすぎ・買われすぎを検出
過剰なシグナルを防ぐための「シグナル間隔制限」付き
📌 シグナルの条件
BUY（逆張り買い）
現在の価格が 200MAより下
RSIが 設定値（初期値30）以下
この条件で「BUY」ラベルがチャート下に表示されます。
SELL（逆張り売り）
現在の価格が 200MAより上
RSIが 設定値（初期値70）以上
この条件で「SELL」ラベルがチャート上に表示されます。
📌 パラメータ設定
MA期間：デフォルト200（200MAで長期トレンドを判定）
RSI期間：デフォルト14
RSI売られすぎ：デフォルト30（BUYの発生条件）
RSI買われすぎ：デフォルト70（SELLの発生条件）
シグナル間隔（バー）：デフォルト10（重複シグナル防止）
📌 使い方
200MAでトレンド方向を確認
RSIが極端な水準に達したら逆張りシグナル発生
「BUY」または「SELL」のラベルが出たら検討
他のテクニカル（サポレジ・プライスアクション）と組み合わせると精度向上
📌 注意点
単独でのエントリー判断には使わず、補助的に活用するのが推奨
シグナル間隔は調整可能（例：スキャルピングなら短め、スイングなら長め）
トレンドが強い相場では逆張りシグナルが連続して外れる可能性あり
相場環境によって設定を変える必要がある
指標発表後など強いトレンドが出る時ではなくレンジ相場で数ドル幅のスキャルピングをするのに向いている。
Recession Warning Model [BackQuant]Recession Warning Model
Overview
The Recession Warning Model (RWM) is a Pine Script® indicator designed to estimate the probability of an economic recession by integrating multiple macroeconomic, market sentiment, and labor market indicators. It combines over a dozen data series into a transparent, adaptive, and actionable tool for traders, portfolio managers, and researchers. The model provides customizable complexity levels, display modes, and data processing options to accommodate various analytical requirements while ensuring robustness through dynamic weighting and regime-aware adjustments.
Purpose
The RWM fulfills the need for a concise yet comprehensive tool to monitor recession risk. Unlike approaches relying on a single metric, such as yield-curve inversion, or extensive economic reports, it consolidates multiple data sources into a single probability output. The model identifies active indicators, their confidence levels, and the current economic regime, enabling users to anticipate downturns and adjust strategies accordingly.
Core Features
- Indicator Families : Incorporates 13 indicators across five categories: Yield, Labor, Sentiment, Production, and Financial Stress.
- Dynamic Weighting : Adjusts indicator weights based on recent predictive accuracy, constrained within user-defined boundaries.
- Leading and Coincident Split : Separates early-warning (leading) and confirmatory (coincident) signals, with adjustable weighting (default 60/40 mix).
- Economic Regime Sensitivity : Modulates output sensitivity based on market conditions (Expansion, Late-Cycle, Stress, Crisis), using a composite of VIX, yield-curve, financial conditions, and credit spreads.
- Display Options : Supports four modes—Probability (0-100%), Binary (four risk bins), Lead/Coincident, and Ensemble (blended probability).
- Confidence Intervals : Reflects model stability, widening during high volatility or conflicting signals.
- Alerts : Configurable thresholds (Watch, Caution, Warning, Alert) with persistence filters to minimize false signals.
- Data Export : Enables CSV output for probabilities, signals, and regimes, facilitating external analysis in Python or R.
Model Complexity Levels
Users can select from four tiers to balance simplicity and depth:
1. Essential : Focuses on three core indicators—yield-curve spread, jobless claims, and unemployment change—for minimalistic monitoring.
2. Standard : Expands to nine indicators, adding consumer confidence, PMI, VIX, S&P 500 trend, money supply vs. GDP, and the Sahm Rule.
3. Professional : Includes all 13 indicators, incorporating financial conditions, credit spreads, JOLTS vacancies, and wage growth.
4. Research : Unlocks all indicators plus experimental settings for advanced users.
Key Indicators
Below is a summary of the 13 indicators, their data sources, and economic significance:
- Yield-Curve Spread : Difference between 10-year and 3-month Treasury yields. Negative spreads signal banking sector stress.
- Jobless Claims : Four-week moving average of unemployment claims. Sustained increases indicate rising layoffs.
- Unemployment Change : Three-month change in unemployment rate. Sharp rises often precede recessions.
- Sahm Rule : Triggers when unemployment rises 0.5% above its 12-month low, a reliable recession indicator.
- Consumer Confidence : University of Michigan survey. Declines reflect household pessimism, impacting spending.
- PMI : Purchasing Managers’ Index. Values below 50 indicate manufacturing contraction.
- VIX : CBOE Volatility Index. Elevated levels suggest market anticipation of economic distress.
- S&P 500 Growth : Weekly moving average trend. Declines reduce wealth effects, curbing consumption.
- M2 + GDP Trend : Monitors money supply and real GDP. Simultaneous declines signal credit contraction.
- NFCI : Chicago Fed’s National Financial Conditions Index. Positive values indicate tighter conditions.
- Credit Spreads : Proxy for corporate bond spreads using 10-year vs. 2-year Treasury yields. Widening spreads reflect stress.
- JOLTS Vacancies : Job openings data. Significant drops precede hiring slowdowns.
- Wage Growth : Year-over-year change in average hourly earnings. Late-cycle spikes often signal economic overheating.
Data Processing
- Rate of Change (ROC) : Optionally applied to capture momentum in data series (default: 21-bar period).
- Z-Score Normalization : Standardizes indicators to a common scale (default: 252-bar lookback).
- Smoothing : Applies a short moving average to final signals (default: 5-bar period) to reduce noise.
- Binary Signals : Generated for each indicator (e.g., yield-curve inverted or PMI below 50) based on thresholds or Z-score deviations.
Probability Calculation
1. Each indicator’s binary signal is weighted according to user settings or dynamic performance.
2. Weights are normalized to sum to 100% across active indicators.
3. Leading and coincident signals are aggregated separately (if split mode is enabled) and combined using the specified mix.
4. The probability is adjusted by a regime multiplier, amplifying risk during Stress or Crisis regimes.
5. Optional smoothing ensures stable outputs.
Display and Visualization
- Probability Mode : Plots a continuous 0-100% recession probability with color gradients and confidence bands.
- Binary Mode : Categorizes risk into four levels (Minimal, Watch, Caution, Alert) for simplified dashboards.
- Lead/Coincident Mode : Displays leading and coincident probabilities separately to track signal divergence.
- Ensemble Mode : Averages traditional and split probabilities for a balanced view.
- Regime Background : Color-coded overlays (green for Expansion, orange for Late-Cycle, amber for Stress, red for Crisis).
- Analytics Table : Optional dashboard showing probability, confidence, regime, and top indicator statuses.
Practical Applications
- Asset Allocation : Adjust equity or bond exposures based on sustained probability increases.
- Risk Management : Hedge portfolios with VIX futures or options during regime shifts to Stress or Crisis.
- Sector Rotation : Shift toward defensive sectors when coincident signals rise above 50%.
- Trading Filters : Disable short-term strategies during high-risk regimes.
- Event Timing : Scale positions ahead of high-impact data releases when probability and VIX are elevated.
Configuration Guidelines
- Enable ROC and Z-score for consistent indicator comparison unless raw data is preferred.
- Use dynamic weighting with at least one economic cycle of data for optimal performance.
- Monitor stress composite scores above 80 alongside probabilities above 70 for critical risk signals.
- Adjust adaptation speed (default: 0.1) to 0.2 during Crisis regimes for faster indicator prioritization.
- Combine RWM with complementary tools (e.g., liquidity metrics) for intraday or short-term trading.
Limitations
- Macro indicators lag intraday market moves, making RWM better suited for strategic rather than tactical trading.
- Historical data availability may constrain dynamic weighting on shorter timeframes.
- Model accuracy depends on the quality and timeliness of economic data feeds.
Final Note
The Recession Warning Model provides a disciplined framework for monitoring economic downturn risks. By integrating diverse indicators with transparent weighting and regime-aware adjustments, it empowers users to make informed decisions in portfolio management, risk hedging, or macroeconomic research. Regular review of model outputs alongside market-specific tools ensures its effective application across varying market conditions.
Drawdown Distribution Analysis (DDA) ACADEMIC FOUNDATION AND RESEARCH BACKGROUND
The Drawdown Distribution Analysis indicator implements quantitative risk management principles, drawing upon decades of academic research in portfolio theory, behavioral finance, and statistical risk modeling. This tool provides risk assessment capabilities for traders and portfolio managers seeking to understand their current position within historical drawdown patterns.
The theoretical foundation of this indicator rests on modern portfolio theory as established by Markowitz (1952), who introduced the fundamental concepts of risk-return optimization that continue to underpin contemporary portfolio management. Sharpe (1966) later expanded this framework by developing risk-adjusted performance measures, most notably the Sharpe ratio, which remains a cornerstone of performance evaluation in financial markets.
The specific focus on drawdown analysis builds upon the work of Chekhlov, Uryasev and Zabarankin (2005), who provided the mathematical framework for incorporating drawdown measures into portfolio optimization. Their research demonstrated that traditional mean-variance optimization often fails to capture the full risk profile of investment strategies, particularly regarding sequential losses. More recent work by Goldberg and Mahmoud (2017) has brought these theoretical concepts into practical application within institutional risk management frameworks.
Value at Risk methodology, as comprehensively outlined by Jorion (2007), provides the statistical foundation for the risk measurement components of this indicator. The coherent risk measures framework developed by Artzner et al. (1999) ensures that the risk metrics employed satisfy the mathematical properties required for sound risk management decisions. Additionally, the focus on downside risk follows the framework established by Sortino and Price (1994), while the drawdown-adjusted performance measures implement concepts introduced by Young (1991).
MATHEMATICAL METHODOLOGY
The core calculation methodology centers on a peak-tracking algorithm that continuously monitors the maximum price level achieved and calculates the percentage decline from this peak. The drawdown at any time t is defined as DD(t) = (P(t) - Peak(t)) / Peak(t) × 100, where P(t) represents the asset price at time t and Peak(t) represents the running maximum price observed up to time t.
Statistical distribution analysis forms the analytical backbone of the indicator. The system calculates key percentiles using the ta.percentile_nearest_rank() function to establish the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of the historical drawdown distribution. This approach provides a complete picture of how the current drawdown compares to historical patterns.
Statistical significance assessment employs standard deviation bands at one, two, and three standard deviations from the mean, following the conventional approach where the upper band equals μ + nσ and the lower band equals μ - nσ. The Z-score calculation, defined as Z = (DD - μ) / σ, enables the identification of statistically extreme events, with thresholds set at |Z| > 2.5 for extreme drawdowns and |Z| > 3.0 for severe drawdowns, corresponding to confidence levels exceeding 99.4% and 99.7% respectively.
ADVANCED RISK METRICS
The indicator incorporates several risk-adjusted performance measures that extend beyond basic drawdown analysis. The Sharpe ratio calculation follows the standard formula Sharpe = (R - Rf) / σ, where R represents the annualized return, Rf represents the risk-free rate, and σ represents the annualized volatility. The system supports dynamic sourcing of the risk-free rate from the US 10-year Treasury yield or allows for manual specification.
The Sortino ratio addresses the limitation of the Sharpe ratio by focusing exclusively on downside risk, calculated as Sortino = (R - Rf) / σd, where σd represents the downside deviation computed using only negative returns. This measure provides a more accurate assessment of risk-adjusted performance for strategies that exhibit asymmetric return distributions.
The Calmar ratio, defined as Annual Return divided by the absolute value of Maximum Drawdown, offers a direct measure of return per unit of drawdown risk. This metric proves particularly valuable for comparing strategies or assets with different risk profiles, as it directly relates performance to the maximum historical loss experienced.
Value at Risk calculations provide quantitative estimates of potential losses at specified confidence levels. The 95% VaR corresponds to the 5th percentile of the drawdown distribution, while the 99% VaR corresponds to the 1st percentile. Conditional VaR, also known as Expected Shortfall, estimates the average loss in the worst 5% of scenarios, providing insight into tail risk that standard VaR measures may not capture.
To enable fair comparison across assets with different volatility characteristics, the indicator calculates volatility-adjusted drawdowns using the formula Adjusted DD = Raw DD / (Volatility / 20%). This normalization allows for meaningful comparison between high-volatility assets like cryptocurrencies and lower-volatility instruments like government bonds.
The Risk Efficiency Score represents a composite measure ranging from 0 to 100 that combines the Sharpe ratio and current percentile rank to provide a single metric for quick asset assessment. Higher scores indicate superior risk-adjusted performance relative to historical patterns.
COLOR SCHEMES AND VISUALIZATION
The indicator implements eight distinct color themes designed to accommodate different analytical preferences and market contexts. The EdgeTools theme employs a corporate blue palette that matches the design system used throughout the edgetools.org platform, ensuring visual consistency across analytical tools.
The Gold theme specifically targets precious metals analysis with warm tones that complement gold chart analysis, while the Quant theme provides a grayscale scheme suitable for analytical environments that prioritize clarity over aesthetic appeal. The Behavioral theme incorporates psychology-based color coding, using green to represent greed-driven market conditions and red to indicate fear-driven environments.
Additional themes include Ocean, Fire, Matrix, and Arctic schemes, each designed for specific market conditions or user preferences. All themes function effectively with both dark and light mode trading platforms, ensuring accessibility across different user interface configurations.
PRACTICAL APPLICATIONS
Asset allocation and portfolio construction represent primary use cases for this analytical framework. When comparing multiple assets such as Bitcoin, gold, and the S&P 500, traders can examine Risk Efficiency Scores to identify instruments offering superior risk-adjusted performance. The 95% VaR provides worst-case scenario comparisons, while volatility-adjusted drawdowns enable fair comparison despite varying volatility profiles.
The practical decision framework suggests that assets with Risk Efficiency Scores above 70 may be suitable for aggressive portfolio allocations, scores between 40 and 70 indicate moderate allocation potential, and scores below 40 suggest defensive positioning or avoidance. These thresholds should be adjusted based on individual risk tolerance and market conditions.
Risk management and position sizing applications utilize the current percentile rank to guide allocation decisions. When the current drawdown ranks above the 75th percentile of historical data, indicating that current conditions are better than 75% of historical periods, position increases may be warranted. Conversely, when percentile rankings fall below the 25th percentile, indicating elevated risk conditions, position reductions become advisable.
Institutional portfolio monitoring applications include hedge fund risk dashboard implementations where multiple strategies can be monitored simultaneously. Sharpe ratio tracking identifies deteriorating risk-adjusted performance across strategies, VaR monitoring ensures portfolios remain within established risk limits, and drawdown duration tracking provides valuable information for investor reporting requirements.
Market timing applications combine the statistical analysis with trend identification techniques. Strong buy signals may emerge when risk levels register as "Low" in conjunction with established uptrends, while extreme risk levels combined with downtrends may indicate exit or hedging opportunities. Z-scores exceeding 3.0 often signal statistically oversold conditions that may precede trend reversals.
STATISTICAL SIGNIFICANCE AND VALIDATION
The indicator provides 95% confidence intervals around current drawdown levels using the standard formula CI = μ ± 1.96σ. This statistical framework enables users to assess whether current conditions fall within normal market variation or represent statistically significant departures from historical patterns.
Risk level classification employs a dynamic assessment system based on percentile ranking within the historical distribution. Low risk designation applies when current drawdowns perform better than 50% of historical data, moderate risk encompasses the 25th to 50th percentile range, high risk covers the 10th to 25th percentile range, and extreme risk applies to the worst 10% of historical drawdowns.
Sample size considerations play a crucial role in statistical reliability. For daily data, the system requires a minimum of 252 trading days (approximately one year) but performs better with 500 or more observations. Weekly data analysis benefits from at least 104 weeks (two years) of history, while monthly data requires a minimum of 60 months (five years) for reliable statistical inference.
IMPLEMENTATION BEST PRACTICES
Parameter optimization should consider the specific characteristics of different asset classes. Equity analysis typically benefits from 500-day lookback periods with 21-day smoothing, while cryptocurrency analysis may employ 365-day lookback periods with 14-day smoothing to account for higher volatility patterns. Fixed income analysis often requires longer lookback periods of 756 days with 34-day smoothing to capture the lower volatility environment.
Multi-timeframe analysis provides hierarchical risk assessment capabilities. Daily timeframe analysis supports tactical risk management decisions, weekly analysis informs strategic positioning choices, and monthly analysis guides long-term allocation decisions. This hierarchical approach ensures that risk assessment occurs at appropriate temporal scales for different investment objectives.
Integration with complementary indicators enhances the analytical framework. Trend indicators such as RSI and moving averages provide directional bias context, volume analysis helps confirm the severity of drawdown conditions, and volatility measures like VIX or ATR assist in market regime identification.
ALERT SYSTEM AND AUTOMATION
The automated alert system monitors five distinct categories of risk events. Risk level changes trigger notifications when drawdowns move between risk categories, enabling proactive risk management responses. Statistical significance alerts activate when Z-scores exceed established threshold levels of 2.5 or 3.0 standard deviations.
New maximum drawdown alerts notify users when historical maximum levels are exceeded, indicating entry into uncharted risk territory. Poor risk efficiency alerts trigger when the composite risk efficiency score falls below 30, suggesting deteriorating risk-adjusted performance. Sharpe ratio decline alerts activate when risk-adjusted performance turns negative, indicating that returns no longer compensate for the risk undertaken.
TRADING STRATEGIES
Conservative risk parity strategies can be implemented by monitoring Risk Efficiency Scores across a diversified asset portfolio. Monthly rebalancing maintains equal risk contribution from each asset, with allocation reductions triggered when risk levels reach "High" status and complete exits executed when "Extreme" risk levels emerge. This approach typically results in lower overall portfolio volatility, improved risk-adjusted returns, and reduced maximum drawdown periods.
Tactical asset rotation strategies compare Risk Efficiency Scores across different asset classes to guide allocation decisions. Assets with scores exceeding 60 receive overweight allocations, while assets scoring below 40 receive underweight positions. Percentile rankings provide timing guidance for allocation adjustments, creating a systematic approach to asset allocation that responds to changing risk-return profiles.
Market timing strategies with statistical edges can be constructed by entering positions when Z-scores fall below -2.5, indicating statistically oversold conditions, and scaling out when Z-scores exceed 2.5, suggesting overbought conditions. The 95% VaR serves as a stop-loss reference point, while trend confirmation indicators provide additional validation for position entry and exit decisions.
LIMITATIONS AND CONSIDERATIONS
Several statistical limitations affect the interpretation and application of these risk measures. Historical bias represents a fundamental challenge, as past drawdown patterns may not accurately predict future risk characteristics, particularly during structural market changes or regime shifts. Sample dependence means that results can be sensitive to the selected lookback period, with shorter periods providing more responsive but potentially less stable estimates.
Market regime changes can significantly alter the statistical parameters underlying the analysis. During periods of structural market evolution, historical distributions may provide poor guidance for future expectations. Additionally, many financial assets exhibit return distributions with fat tails that deviate from normal distribution assumptions, potentially leading to underestimation of extreme event probabilities.
Practical limitations include execution risk, where theoretical signals may not translate directly into actual trading results due to factors such as slippage, timing delays, and market impact. Liquidity constraints mean that risk metrics assume perfect liquidity, which may not hold during stressed market conditions when risk management becomes most critical.
Transaction costs are not incorporated into risk-adjusted return calculations, potentially overstating the attractiveness of strategies that require frequent trading. Behavioral factors represent another limitation, as human psychology may override statistical signals, particularly during periods of extreme market stress when disciplined risk management becomes most challenging.
TECHNICAL IMPLEMENTATION
Performance optimization ensures reliable operation across different market conditions and timeframes. All technical analysis functions are extracted from conditional statements to maintain Pine Script compliance and ensure consistent execution. Memory efficiency is achieved through optimized variable scoping and array usage, while computational speed benefits from vectorized calculations where possible.
Data quality requirements include clean price data without gaps or errors that could distort distribution analysis. Sufficient historical data is essential, with a minimum of 100 bars required and 500 or more preferred for reliable statistical inference. Time alignment across related assets ensures meaningful comparison when conducting multi-asset analysis.
The configuration parameters are organized into logical groups to enhance usability. Core settings include the Distribution Analysis Period (100-2000 bars), Drawdown Smoothing Period (1-50 bars), and Price Source selection. Advanced metrics settings control risk-free rate sourcing, either from live market data or fixed rate specification, along with toggles for various risk-adjusted metric calculations.
Display options provide flexibility in visual presentation, including color theme selection from eight available schemes, automatic dark mode optimization, and control over table display, position lines, percentile bands, and standard deviation overlays. These options ensure that the indicator can be adapted to different analytical workflows and visual preferences.
CONCLUSION
The Drawdown Distribution Analysis indicator provides risk management tools for traders seeking to understand their current position within historical risk patterns. By combining established statistical methodology with practical usability features, the tool enables evidence-based risk assessment and portfolio optimization decisions.
The implementation draws upon established academic research while providing practical features that address real-world trading requirements. Dynamic risk-free rate integration ensures accurate risk-adjusted performance calculations, while multiple color schemes accommodate different analytical preferences and use cases.
Academic compliance is maintained through transparent methodology and acknowledgment of limitations. The tool implements peer-reviewed statistical techniques while clearly communicating the constraints and assumptions underlying the analysis. This approach ensures that users can make informed decisions about the appropriate application of the risk assessment framework within their broader trading and investment processes.
BIBLIOGRAPHY
Artzner, P., Delbaen, F., Eber, J.M. and Heath, D. (1999) 'Coherent Measures of Risk', Mathematical Finance, 9(3), pp. 203-228.
Chekhlov, A., Uryasev, S. and Zabarankin, M. (2005) 'Drawdown Measure in Portfolio Optimization', International Journal of Theoretical and Applied Finance, 8(1), pp. 13-58.
Goldberg, L.R. and Mahmoud, O. (2017) 'Drawdown: From Practice to Theory and Back Again', Journal of Risk Management in Financial Institutions, 10(2), pp. 140-152.
Jorion, P. (2007) Value at Risk: The New Benchmark for Managing Financial Risk. 3rd edn. New York: McGraw-Hill.
Markowitz, H. (1952) 'Portfolio Selection', Journal of Finance, 7(1), pp. 77-91.
Sharpe, W.F. (1966) 'Mutual Fund Performance', Journal of Business, 39(1), pp. 119-138.
Sortino, F.A. and Price, L.N. (1994) 'Performance Measurement in a Downside Risk Framework', Journal of Investing, 3(3), pp. 59-64.
Young, T.W. (1991) 'Calmar Ratio: A Smoother Tool', Futures, 20(1), pp. 40-42.
Momentum DivergenceOverview
The Momentum Divergence Oscillator is a valuable tool designed for traders who are familiar with basic charting but want to deepen their market insights. This indicator combines a momentum calculation with divergence detection, presenting the data in an intuitive way with a blue momentum line and colored divergence signals ("Bull" and "Bear"). It’s perfect for refining entry and exit points across various timeframes, especially for scalping or swing trading strategies.
Understanding the Concepts
What is Momentum?
Momentum measures the speed and strength of a price movement by comparing the current closing price to a previous close over a set period. In this indicator, it’s calculated as the difference between the current close and the close from a user-defined number of bars ago (default: 10). A rising momentum line indicates accelerating upward momentum, while a falling line suggests slowing momentum or a potential reversal. This helps you gauge whether a trend is gaining power or losing steam, making it a key indicator for spotting overbought or oversold conditions.
What is a Divergence?
A divergence occurs when the price action and the momentum indicator move in opposite directions, often signaling a potential trend reversal. The Momentum Divergence Oscillator highlights two types:
Bullish Divergence: When the price forms a lower low (indicating weakness), but the momentum shows a higher low (suggesting underlying strength). This can foreshadow an upward reversal.
Bearish Divergence: When the price reaches a higher high (showing strength), but the momentum records a lower high (indicating fading momentum). This may hint at an impending downward turn.
How the Indicator Works
The indicator plots a momentum line in a separate pane below your chart, giving you a clear view of price momentum over time. It also scans for divergences using adjustable lookback periods (default: 5 bars left and right) and a range window (default: 5-60 bars) to ensure relevance. When a divergence is detected, it’s visually highlighted, and you can customize the sensitivity through input settings like the momentum length and pivot lookback. Alerts are included to notify you of new divergence signals in real-time, saving you from constant monitoring.
How to Apply It
Identifying Opportunities: Use bullish divergences ("Bull") as a cue to consider long positions, especially when confirmed by support levels or a moving average crossover. Bearish divergences ("Bear") can signal short opportunities, particularly near resistance zones.
Combining with Other Tools: Pair this oscillator with indicators like the Relative Strength Index (RSI) or volume analysis to filter out false signals and increase confidence in your trades. For example, a bullish divergence with rising volume can be a stronger buy signal.
Timeframe Flexibility: Test it on shorter timeframes (e.g., 5-minute charts) for quick scalping trades or longer ones (e.g., 1-hour or 4-hour charts) for swing trading, adjusting the momentum length to suit the market’s pace.
Alert Setup: Enable the built-in alerts to get notified when a divergence forms, allowing you to react promptly without staring at the screen all day.
Strategy Example
Spot a bullish divergence on a 15-minute chart where the price hits a lower low, but the momentum rises.
Confirm with a break above a 20-period EMA and increasing volume.
Enter a long position with a stop-loss below the recent low and a take-profit near the next resistance level.
Customization Tips
Adjust the "Momentum Length" (default: 10) to make the oscillator more or less sensitive—shorter lengths react faster, while longer ones smooth out noise.
Tweak the "Pivot Lookback" settings to widen or narrow the divergence detection range based on your trading style.
Use the "Range Upper/Lower" inputs to focus on divergences within a specific timeframe that matches your strategy.
Important Considerations
b]This indicator is a technical analysis tool, not a guaranteed trading system. Always pair it with a solid strategy and strict risk management, such as setting stop-losses.
In strong trending markets, divergences can sometimes produce false signals. Consider adding a trend filter (e.g., ADX below 25) to avoid whipsaws.
Experiment with the settings on a demo account or backtest to find what works best for your preferred markets and timeframes.
MERV: Market Entropy & Rhythm Visualizer [BullByte]The MERV (Market Entropy & Rhythm Visualizer) indicator analyzes market conditions by measuring entropy (randomness vs. trend), tradeability (volatility/momentum), and cyclical rhythm. It provides traders with an easy-to-read dashboard and oscillator to understand when markets are structured or choppy, and when trading conditions are optimal.
Purpose of the Indicator
MERV’s goal is to help traders identify different market regimes. It quantifies how structured or random recent price action is (entropy), how strong and volatile the movement is (tradeability), and whether a repeating cycle exists. By visualizing these together, MERV highlights trending vs. choppy environments and flags when conditions are favorable for entering trades. For example, a low entropy value means prices are following a clear trend line, whereas high entropy indicates a lot of noise or sideways action. The indicator’s combination of measures is original: it fuses statistical trend-fit (entropy), volatility trends (ATR and slope), and cycle analysis to give a comprehensive view of market behavior.
Why a Trader Should Use It
Traders often need to know when a market trend is reliable vs. when it is just noise. MERV helps in several ways: it shows when the market has a strong direction (low entropy, high tradeability) and when it’s ranging (high entropy). This can prevent entering trend-following strategies during choppy periods, or help catch breakouts early. The “Optimal Regime” marker (a star) highlights moments when entropy is very low and tradeability is very high, typically the best conditions for trend trades. By using MERV, a trader gains an empirical “go/no-go” signal based on price history, rather than guessing from price alone. It’s also adaptable: you can apply it to stocks, forex, crypto, etc., on any timeframe. For example, during a bullish phase of a stock, MERV will turn green (Trending Mode) and often show a star, signaling good follow-through. If the market later grinds sideways, MERV will shift to magenta (Choppy Mode), warning you that trend-following is now risky.
Why These Components Were Chosen
Market Entropy (via R²) : This measures how well recent prices fit a straight line. We compute a linear regression on the last len_entropy bars and calculate R². Entropy = 1 - R², so entropy is low when prices follow a trend (R² near 1) and high when price action is erratic (R² near 0). This single number captures trend strength vs noise.
Tradeability (ATR + Slope) : We combine two familiar measures: the Average True Range (ATR) (normalized by price) and the absolute slope of the regression line (scaled by ATR). Together they reflect how active and directional the market is. A high ATR or strong slope means big moves, making a trend more “tradeable.” We take a simple average of the normalized ATR and slope to get tradeability_raw. Then we convert it to a percentile rank over the lookback window so it’s stable between 0 and 1.
Percentile Ranks : To make entropy and tradeability values easy to interpret, we convert each to a 0–100 rank based on the past len_entropy periods. This turns raw metrics into a consistent scale. (For example, an entropy rank of 90 means current entropy is higher than 90% of recent values.) We then divide by 100 to plot them on a 0–1 scale.
Market Mode (Regime) : Based on those ranks, MERV classifies the market:
Trending (Green) : Low entropy rank (<40%) and high tradeability rank (>60%). This means the market is structurally trending with high activity.
Choppy (Magenta) : High entropy rank (>60%) and low tradeability rank (<40%). This is a mostly random, low-momentum market.
Neutral (Cyan) : All other cases. This covers mixed regimes not strongly trending or choppy.
The mode is shown as a colored bar at the bottom: green for trending, magenta for choppy, cyan for neutral.
Optimal Regime Signal : Separately, we mark an “optimal” condition when entropy_norm < 0.3 and tradeability > 0.7 (both normalized 0–1). When this is true, a ★ star appears on the bottom line. This star is colored white when truly optimal, gold when only tradeability is high (but entropy not quite low enough), and black when neither condition holds. This gives a quick visual cue for very favorable conditions.
What Makes MERV Stand Out
Holistic View : Unlike a single-oscillator, MERV combines trend, volatility, and cycle analysis in one tool. This multi-faceted approach is unique.
Visual Dashboard : The fixed on-chart dashboard (shown at your chosen corner) summarizes all metrics in bar/gauge form. Even a non-technical user can glance at it: more “█” blocks = a higher value, colors match the plots. This is more intuitive than raw numbers.
Adaptive Thresholds : Using percentile ranks means MERV auto-adjusts to each market’s character, rather than requiring fixed thresholds.
Cycle Insight : The rhythm plot adds information rarely found in indicators – it shows if there’s a repeating cycle (and its period in bars) and how strong it is. This can hint at natural bounce or reversal intervals.
Modern Look : The neon color scheme and glow effects make the lines easy to distinguish (blue/pink for entropy, green/orange for tradeability, etc.) and the filled area between them highlights when one dominates the other.
Recommended Timeframes
MERV can be applied to any timeframe, but it will be more reliable on higher timeframes. The default len_entropy = 50 and len_rhythm = 30 mean we use 30–50 bars of history, so on a daily chart that’s ~2–3 months of data; on a 1-hour chart it’s about 2–3 days. In practice:
Swing/Position traders might prefer Daily or 4H charts, where the calculations smooth out small noise. Entropy and cycles are more meaningful on longer trends.
Day trader s could use 15m or 1H charts if they adjust the inputs (e.g. shorter windows). This provides more sensitivity to intraday cycles.
Scalpers might find MERV too “slow” unless input lengths are set very low.
In summary, the indicator works anywhere, but the defaults are tuned for capturing medium-term trends. Users can adjust len_entropy and len_rhythm to match their chart’s volatility. The dashboard position can also be moved (top-left, bottom-right, etc.) so it doesn’t cover important chart areas.
How the Scoring/Logic Works (Step-by-Step)
Compute Entropy : A linear regression line is fit to the last len_entropy closes. We compute R² (goodness of fit). Entropy = 1 – R². So a strong straight-line trend gives low entropy; a flat/noisy set of points gives high entropy.
Compute Tradeability : We get ATR over len_entropy bars, normalize it by price (so it’s a fraction of price). We also calculate the regression slope (difference between the predicted close and last close). We scale |slope| by ATR to get a dimensionless measure. We average these (ATR% and slope%) to get tradeability_raw. This represents how big and directional price moves are.
Convert to Percentiles : Each new entropy and tradeability value is inserted into a rolling array of the last 50 values. We then compute the percentile rank of the current value in that array (0–100%) using a simple loop. This tells us where the current bar stands relative to history. We then divide by 100 to plot on .
Determine Modes and Signal : Based on these normalized metrics: if entropy < 0.4 and tradeability > 0.6 (40% and 60% thresholds), we set mode = Trending (1). If entropy > 0.6 and tradeability < 0.4, mode = Choppy (-1). Otherwise mode = Neutral (0). Separately, if entropy_norm < 0.3 and tradeability > 0.7, we set an optimal flag. These conditions trigger the colored mode bars and the star line.
Rhythm Detection : Every bar, if we have enough data, we take the last len_rhythm closes and compute the mean and standard deviation. Then for lags from 5 up to len_rhythm, we calculate a normalized autocorrelation coefficient. We track the lag that gives the maximum correlation (best match). This “best lag” divided by len_rhythm is plotted (a value between 0 and 1). Its color changes with the correlation strength. We also smooth the best correlation value over 5 bars to plot as “Cycle Strength” (also 0 to 1). This shows if there is a consistent cycle length in recent price action.
Heatmap (Optional) : The background color behind the oscillator panel can change with entropy. If “Neon Rainbow” style is on, low entropy is blue and high entropy is pink (via a custom color function), otherwise a classic green-to-red gradient can be used. This visually reinforces the entropy value.
Volume Regime (Dashboard Only) : We compute vol_norm = volume / sma(volume, len_entropy). If this is above 1.5, it’s considered high volume (neon orange); below 0.7 is low (blue); otherwise normal (green). The dashboard shows this as a bar gauge and percentage. This is for context only.
Oscillator Plot – How to Read It
The main panel (oscillator) has multiple colored lines on a 0–1 vertical scale, with horizontal markers at 0.2 (Low), 0.5 (Mid), and 0.8 (High). Here’s each element:
Entropy Line (Blue→Pink) : This line (and its glow) shows normalized entropy (0 = very low, 1 = very high). It is blue/green when entropy is low (strong trend) and pink/purple when entropy is high (choppy). A value near 0.0 (below 0.2 line) indicates a very well-defined trend. A value near 1.0 (above 0.8 line) means the market is very random. Watch for it dipping near 0: that suggests a strong trend has formed.
Tradeability Line (Green→Yellow) : This represents normalized tradeability. It is colored bright green when tradeability is low, transitioning to yellow as tradeability increases. Higher values (approaching 1) mean big moves and strong slopes. Typically in a market rally or crash, this line will rise. A crossing above ~0.7 often coincides with good trend strength.
Filled Area (Orange Shade) : The orange-ish fill between the entropy and tradeability lines highlights when one dominates the other. If the area is large, the two metrics diverge; if small, they are similar. This is mostly aesthetic but can catch the eye when the lines cross over or remain close.
Rhythm (Cycle) Line : This is plotted as (best_lag / len_rhythm). It indicates the relative period of the strongest cycle. For example, a value of 0.5 means the strongest cycle was about half the window length. The line’s color (green, orange, or pink) reflects how strong that cycle is (green = strong). If no clear cycle is found, this line may be flat or near zero.
Cycle Strength Line : Plotted on the same scale, this shows the autocorrelation strength (0–1). A high value (e.g. above 0.7, shown in green) means the cycle is very pronounced. Low values (pink) mean any cycle is weak and unreliable.
Mode Bars (Bottom) : Below the main oscillator, thick colored bars appear: a green bar means Trending Mode, magenta means Choppy Mode, and cyan means Neutral. These bars all have a fixed height (–0.1) and make it very easy to see the current regime.
Optimal Regime Line (Bottom) : Just below the mode bars is a thick horizontal line at –0.18. Its color indicates regime quality: White (★) means “Optimal Regime” (very low entropy and high tradeability). Gold (★) means not quite optimal (high tradeability but entropy not low enough). Black means neither condition. This star line quickly tells you when conditions are ideal (white star) or simply good (gold star).
Horizontal Guides : The dotted lines at 0.2 (Low), 0.5 (Mid), and 0.8 (High) serve as reference lines. For example, an entropy or tradeability reading above 0.8 is “High,” and below 0.2 is “Low,” as labeled on the chart. These help you gauge values at a glance.
Dashboard (Fixed Corner Panel)
MERV also includes a compact table (dashboard) that can be positioned in any corner. It summarizes key values each bar. Here is how to read its rows:
Entropy : Shows a bar of blocks (█ and ░). More █ blocks = higher entropy. It also gives a percentage (rounded). A full bar (10 blocks) with a high % means very chaotic market. The text is colored similarly (blue-green for low, pink for high).
Rhythm : Shows the best cycle period in bars (e.g. “15 bars”). If no calculation yet, it shows “n/a.” The text color matches the rhythm line.
Cycle Strength : Gives the cycle correlation as a percentage (smoothed, as shown on chart). Higher % (green) means a strong cycle.
Tradeability : Displays a 10-block gauge for tradeability. More blocks = more tradeable market. It also shows “gauge” text colored green→yellow accordingly.
Market Mode : Simply shows “Trending”, “Choppy”, or “Neutral” (cyan text) to match the mode bar color.
Volume Regime : Similar to tradeability, shows blocks for current volume vs. average. Above-average volume gives orange blocks, below-average gives blue blocks. A % value indicates current volume relative to average. This row helps see if volume is abnormally high or low.
Optimal Status (Large Row) : In bold, either “★ Optimal Regime” (white text) if the star condition is met, “★ High Tradeability” (gold text) if tradeability alone is high, or “— Not Optimal” (gray text) otherwise. This large row catches your eye when conditions are ripe.
In short, the dashboard turns the numeric state into an easy read: filled bars, colors, and text let you see current conditions without reading the plot. For instance, five blue blocks under Entropy and “25%” tells you entropy is low (good), and a row showing “Trending” in green confirms a trend state.
Real-Life Example
Example : Consider a daily chart of a trending stock (e.g. “AAPL, 1D”). During a strong uptrend, recent prices fit a clear upward line, so Entropy would be low (blue line near bottom, perhaps below the 0.2 line). Volatility and slope are high, so Tradeability is high (green-yellow line near top). In the dashboard, Entropy might show only 1–2 blocks (e.g. 10%) and Tradeability nearly full (e.g. 90%). The Market Mode bar turns green (Trending), and you might see a white ★ on the optimal line if conditions are very good. The Volume row might light orange if volume is above average during the rally. In contrast, imagine the same stock later in a tight range: Entropy will rise (pink line up, more blocks in dashboard), Tradeability falls (fewer blocks), and the Mode bar turns magenta (Choppy). No star appears in that case.
Consolidated Use Case : Suppose on XYZ stock the dashboard reads “Entropy: █░░░░░░░░ 20%”, “Tradeability: ██████████ 80%”, Mode = Trending (green), and “★ Optimal Regime.” This tells the trader that the market is in a strong, low-noise trend, and it might be a good time to follow the trend (with appropriate risk controls). If instead it reads “Entropy: ████████░░ 80%”, “Tradeability: ███▒▒▒▒▒▒ 30%”, Mode = Choppy (magenta), the trader knows the market is random and low-momentum—likely best to sit out until conditions improve.
Example: How It Looks in Action
Screenshot 1: Trending Market with High Tradeability (SOLUSD, 30m)
What it means:
The market is in a clear, strong trend with excellent conditions for trading. Both trend-following and active strategies are favored, supported by high tradeability and strong volume.
Screenshot 2: Optimal Regime, Strong Trend (ETHUSD, 1h)
What it means:
This is an ideal environment for trend trading. The market is highly organized, tradeability is excellent, and volume supports the move. This is when the indicator signals the highest probability for success.
Screenshot 3: Choppy Market with High Volume (BTC Perpetual, 5m)
What it means:
The market is highly random and choppy, despite a surge in volume. This is a high-risk, low-reward environment, avoid trend strategies, and be cautious even with mean-reversion or scalping.
Settings and Inputs
The script is fully open-source; here are key inputs the user can adjust:
Entropy Window (len_entropy) : Number of bars used for entropy and tradeability (default 50). Larger = smoother, more lag; smaller = more sensitivity.
Rhythm Window (len_rhythm ): Bars used for cycle detection (default 30). This limits the longest cycle we detect.
Dashboard Position : Choose any corner (Top Right default) so it doesn’t cover chart action.
Show Heatmap : Toggles the entropy background coloring on/off.
Heatmap Style : “Neon Rainbow” (colorful) or “Classic” (green→red).
Show Mode Bar : Turn the bottom mode bar on/off.
Show Dashboard : Turn the fixed table panel on/off.
Each setting has a tooltip explaining its effect. In the description we will mention typical settings (e.g. default window sizes) and that the user can move the dashboard corner as desired.
Oscillator Interpretation (Recap)
Lines : Blue/Pink = Entropy (low=trend, high=chop); Green/Yellow = Tradeability (low=quiet, high=volatile).
Fill : Orange tinted area between them (for visual emphasis).
Bars : Green=Trending, Magenta=Choppy, Cyan=Neutral (at bottom).
Star Line : White star = ideal conditions, Gold = good but not ideal.
Horizontal Guides : 0.2 and 0.8 lines mark low/high thresholds for each metric.
Using the chart, a coder or trader can see exactly what each output represents and make decisions accordingly.
Disclaimer
This indicator is provided as-is for educational and analytical purposes only. It does not guarantee any particular trading outcome. Past market patterns may not repeat in the future. Users should apply their own judgment and risk management; do not rely solely on this tool for trading decisions. Remember, TradingView scripts are tools for market analysis, not personalized financial advice. We encourage users to test and combine MERV with other analysis and to trade responsibly.
-BullByte
BUY in HASH RibbonsHash Ribbons Indicator (BUY Signal)
A TradingView Pine Script v6 implementation for identifying Bitcoin miner capitulation (“Springs”) and recovery phases based on hash rate data. It marks potential low-risk buying opportunities by tracking short- and long-term moving averages of the network hash rate.
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Key Features
• Hash Rate SMAs
• Short-term SMA (default: 30 days)
• Long-term SMA (default: 60 days)
• Phase Markers
• Gray circle: Short SMA crosses below long SMA (start of capitulation)
• White circles: Ongoing capitulation, with brighter white when the short SMA turns upward
• Yellow circle: Short SMA crosses back above long SMA (end of capitulation)
• Orange circle: Buy signal once hash rate recovery aligns with bullish price momentum (10-day price SMA crosses above 20-day price SMA)
• Display Modes
• Ribbons: Plots the two SMAs as colored bands—red for capitulation, green for recovery
• Oscillator: Shows the percentage difference between SMAs as a histogram (red for negative, blue for positive)
• Optional Overlays
• Bitcoin halving dates (2012, 2016, 2020, 2024) with dashed lines and labels
• Raw hash rate data in EH/s
• Alerts
• Configurable alerts for capitulation start, recovery, and buy signals
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How It Works
1. Data Source: Fetches daily hash rate values from a selected provider (e.g., IntoTheBlock, Quandl).
2. Capitulation Detection: When the 30-day SMA falls below the 60-day SMA, miners are likely capitulating.
3. Recovery Identification: A rising 30-day SMA during capitulation signals miner recovery.
4. Buy Signal: Confirmed when the hash rate recovery coincides with a bullish shift in price momentum (10-day price SMA > 20-day price SMA).
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Inputs
Hash Rate Short SMA: 30 days
Hash Rate Long SMA: 60 days
Plot Signals: On
Plot Halvings: Off
Plot Raw Hash Rate: Off
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Considerations
• Timeframe: Best applied on daily charts to capture meaningful miner behavior.
• Data Reliability: Ensure the chosen hash rate source provides consistent, gap-free data.
• Risk Management: Use alongside other technical indicators (e.g., RSI, MACD) and fundamental analysis.
• Backtesting: Evaluate performance over different market cycles before live deployment.
Vertical Time Marker Configurable (VTMC)# Vertical Time Marker Configurable (VTMC)
## Overview
The Vertical Time Marker Configurable (VTMC) is a powerful PineScript v6 indicator designed to help traders quickly identify key market times across their entire chart history. Instead of hovering over candles to check timestamps, VTMC draws clear vertical lines with customizable labels at your specified times, making it easy to spot important market sessions, news events, or personal trading windows at a glance.
## Key Features
### ⏰ Flexible Time Selection
- Set any time using an intuitive time picker (defaults to 8:30 AM Central Time)
- Automatically draws lines at your specified time across all historical data
- Perfect for marking market opens, closes, news releases, or personal trading times
### 🎨 Full Visual Customization
- **Line Color**: Choose any color (defaults to white for maximum visibility)
- **Line Style**: Solid, dashed, or dotted options
- **Line Width**: Adjustable from 1-10 pixels
- **Opacity Control**: Precise opacity slider (0-100%) for both line and text
### 🏷️ Smart Text Labels
- **Preset Options**: New York Open, New York Close, London Open, London Close, Asia Open, Asia Close
- **Custom Labels**: Enter any text for personalized marking (news events, trading windows, etc.)
- **Configurable Text**: Adjustable size (8-20px), color, and opacity
- **Smart Positioning**: Text appears just above the price action for clear visibility
### 📊 Professional Display
- Lines extend fully from top to bottom of chart
- Clean, non-intrusive design that doesn't clutter your analysis
- Works on any timeframe and market
- Historical lines persist across all chart data
## Perfect For
### Market Session Traders
- Mark key session opens and closes
- Identify overlap periods between major markets
- Track session-specific price behavior patterns
### News Traders
- Mark important economic releases (FOMC, NFP, etc.)
- Create visual reminders for scheduled events
- Track market reaction patterns around news times
### Institutional Flow Traders
- Identify key institutional activity times
- Mark order block formation periods
- Track smart money movement windows
### Personal Trading Systems
- Mark your optimal trading hours
- Create visual discipline for trading windows
- Track performance during specific time periods
## Why VTMC?
Unlike hardcoded session indicators that only work for specific markets, VTMC gives you complete flexibility to mark ANY time that matters to your trading strategy. Whether you're tracking "MY Trading Window" from 9:30-10:30 AM or marking custom news events, VTMC adapts to your specific needs.
The indicator eliminates the constant need to hover over candles to check times, instead providing instant visual reference points across your entire chart. This makes pattern recognition, backtesting, and trade timing significantly more efficient.
## Usage Tips
- Use multiple instances for different time zones or events
- Combine with other indicators for comprehensive market timing
- Customize colors to match your chart theme
- Use custom labels for personalized trading reminders
*Built with precision in PineScript v6 for reliable performance and modern TradingView compatibility.*
AVWAP 4HThe AVWAP 4H indicator is a multi-session Anchored Volume-Weighted Average Price (AVWAP) tool designed for intraday precision and institutional-grade insight. It plots session-specific AVWAP lines based on a series of key UTC-based time anchors, allowing traders to monitor value zones and dynamic support/resistance across global trading hours.
This script calculates and displays AVWAP lines anchored from five distinct UTC times:
8:00 PM (ETH Open)
10:00 PM
2:00 AM
6:00 AM
10:00 AM
Each line is calculated using ohlc4 as the price source and resets at its respective session start time. Traders can enable or disable any AVWAP anchor individually, as well as customize line color and width for better visual distinction.
The indicator is ideal for identifying volume-weighted equilibrium levels across overlapping global market sessions, particularly useful for short-term mean-reversion, breakout, and institutional order flow strategies.
Trigonometric StochasticTrigonometric Stochastic - Mathematical Smoothing Oscillator
Overview
A revolutionary approach to stochastic oscillation using sine wave mathematical smoothing. This indicator transforms traditional stochastic calculations through trigonometric functions, creating an ultra-smooth oscillator that reduces noise while maintaining sensitivity to price changes.
Mathematical Foundation
Unlike standard stochastic oscillators, this version applies sine wave smoothing:
• Raw Stochastic: (close - lowest_low) / (highest_high - lowest_low) × 100
• Trigonometric Smoothing: 50 + 50 × sin(2π × raw_stochastic / 100)
• Result: Naturally smooth oscillator with mathematical precision
Key Features
Advanced Smoothing Technology
• Sine Wave Filter: Eliminates choppy movements while preserving signal integrity
• Natural Boundaries: Mathematically constrained between 0-100
• Reduced False Signals: Trigonometric smoothing filters market noise effectively
Traditional Stochastic Levels
• Overbought Zone: 80 level (dashed line)
• Oversold Zone: 20 level (dashed line)
• Midline: 50 level (dotted line) - equilibrium point
• Visual Clarity: Clean oscillator panel with clear level markings
Smart Signal Generation
• Anti-Repaint Logic: Uses confirmed previous bar values
• Buy Signals: Generated when crossing above 30 from oversold territory
• Sell Signals: Generated when crossing below 70 from overbought territory
• Crossover Detection: Precise entry/exit timing
Professional Presentation
• Separate Panel: Dedicated oscillator window (overlay=false)
• Price Format: Formatted as price indicator with 2-decimal precision
• Theme Adaptive: Automatically matches your chart color scheme
Parameters
• Cycle Length (5-200): Period for highest/lowest calculations
- Shorter periods = more sensitive, more signals
- Longer periods = smoother, fewer but stronger signals
Trading Applications
Momentum Analysis
• Overbought/Oversold: Clear visual identification of extreme levels
• Momentum Shifts: Early detection of momentum changes
• Trend Strength: Monitor oscillator position relative to midline
Signal Trading
• Long Entries: Buy when crossing above 30 (oversold bounce)
• Short Entries: Sell when crossing below 70 (overbought rejection)
• Confirmation Tool: Use with trend indicators for higher probability trades
Divergence Detection
• Bullish Divergence: Price makes lower lows, oscillator makes higher lows
• Bearish Divergence: Price makes higher highs, oscillator makes lower highs
• Early Warning: Spot potential trend reversals before they occur
Trading Strategies
Scalping (5-15min timeframes)
• Use cycle length 10-14 for quick signals
• Focus on 20/80 level bounces
• Combine with price action confirmation
Swing Trading (1H-4H timeframes)
• Use cycle length 20-30 for reliable signals
• Wait for clear crossovers with momentum
• Monitor divergences for reversal setups
Position Trading (Daily+ timeframes)
• Use cycle length 50+ for major signals
• Focus on extreme readings (below 10, above 90)
• Combine with fundamental analysis
Advantages Over Standard Stochastic
1. Smoother Action: Sine wave smoothing reduces whipsaws
2. Mathematical Precision: Trigonometric functions provide consistent behavior
3. Maintained Sensitivity: Smoothing doesn't compromise signal quality
4. Reduced Noise: Cleaner signals in volatile markets
5. Visual Appeal: More aesthetically pleasing oscillator movement
Best Practices
• Market Context: Consider overall trend direction
• Multiple Timeframe: Confirm signals on higher timeframes
• Risk Management: Always use proper position sizing
• Backtesting: Test parameters on your preferred instruments
• Combination: Works excellently with trend-following indicators
Built-in Alerts
• Buy Alert: Trigonometric stochastic oversold crossover
• Sell Alert: Trigonometric stochastic overbought crossunder
Technical Specifications
• Pine Script Version: v6
• Panel: Separate oscillator window
• Format: Price indicator with 2-decimal precision
• Performance: Optimized for all timeframes
• Compatibility: Works with all instruments
Free and open-source indicator. Modify, improve, and share with the community!
Educational Value: Perfect for traders wanting to understand how mathematical smoothing improves oscillators and trigonometric applications in technical analysis.
MVO - MA Signal StrategyStrategy Description: MA Signal Strategy with Heikin Ashi, Break-even and Trailing Stop
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🔍 Core Concept
This strategy enters long or short trades based on Heikin Ashi candles crossing above or below a moving average (MA), with optional confirmation from the Money Flow Index (MFI). It includes:
• Dynamic stop loss and take profit levels based on ATR
• Optional break-even stop adjustment
• Optional trailing stop activation after breakeven
• Full visual feedback for trades and zones
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⚙️ Indicators Used
• Heikin Ashi Candles: Smooth price action to reduce noise.
• Simple Moving Average (MA): Determines trend direction.
• Average True Range (ATR): Sets volatility-based SL/TP.
• Money Flow Index (MFI): Optional momentum filter for entries.
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📈 Trade Entry Logic
✅ Long Entry:
Triggered if:
• Heikin Ashi close crosses above the MA
or
• MFI is below 20 and Heikin Ashi close is above the MA
❌ Short Entry:
Triggered if:
• Heikin Ashi close crosses below the MA
or
• MFI is above 90 and Heikin Ashi close is below the MA
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🛑 Stop Loss & Take Profit
• SL is set using riskMult * ATR
• TP is set using rewardMult * ATR
Example:
• If ATR = 10, riskMult = 1, rewardMult = 5
→ SL = 10 points, TP = 50 points from entry
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⚖️ Break-even Logic (Optional)
• If price moves in your favor by breakevenTicks * ATR, SL is moved to entry price.
• Enabled via checkbox Enable Break Even.
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📉 Trailing Stop Logic (Optional)
• Once break-even is hit, a trailing stop starts moving behind price by trailATRmult * ATR.
• Trailing stop only activates after break-even is reached.
• Enabled via checkbox Enable Trailing Stop.
📊 Visual Elements
• Heikin Ashi candles are drawn on the main chart.
• Trade zones are shaded between SL and TP during open trades.
• Lines mark Entry, SL, TP, Break-even trigger.
• Markers show entries and exits:
• Green/red triangles = long/short entries
• ✅ = Take profit hit
• ❌ = Stop loss hit
✅ Best Use Case
• Trending markets with strong pullbacks
• Works on multiple timeframes
• Better suited for assets with consistent volatility (ATR behavior)
Portfolio Tracker ARJO (V-01)Portfolio Tracker ARJO (V-01)
This indicator is a user-friendly portfolio tracking tool designed for TradingView charts. It overlays a customizable table on your chart to monitor up to 15 stocks or symbols in your portfolio. It calculates real-time metrics like current market price (CMP), gains/losses, and stoploss breaches, helping you stay on top of your investments without switching between multiple charts. The table uses color-coding for quick visual insights: green for profits, red for losses, and highlights breached stoplosses in red for alerts. It also shows portfolio-wide totals for overall performance.
Key Features
Supports up to 15 Symbols: Enter stock tickers (e.g., NSE:RELIANCE or BSE:TCS) with details like buy price, date, units, and stoploss.
Symbol: The stock ticker and description.
Buy Date: When you purchased it.
Units: Number of shares/units held.
Buy Price: Your entry price.
Stop Loss: Your set stoploss level (highlighted in red if breached by CMP).
CMP: Current market price (fetched from the chart's timeframe).
% Gain/Loss: Percentage change from buy price (color-coded: green for positive, red for negative).
Gain/Loss: Total monetary gain/loss based on units.
Optional Timeframe Columns: Toggle to show % change over 1 Week (1W), 1 Month (1M), 3 Months (3M), and 6 Months (6M) for historical performance.
Portfolio Summary: At the top of the table, see total % gain/loss and absolute gain/loss for your entire portfolio.
Visual Customizations: Adjust table position (e.g., Top Right), size, colors for positive/negative values, and intensity cutoff for gradients.
Benchmark Index-Based Header: The title row's background color reflects NIFTY's weekly trend (green if above 10-week SMA, red if below) for market context.
Benchmark Index-Based Header: The title row's background color reflects NIFTY's weekly trend (green if above 10-week SMA, red if below) for market context.
How to Use It: Step-by-Step Guide
Add the Indicator to Your Chart: Search for "Portfolio Tracker ARJO (V-01)" in TradingView's indicator library and add it to any chart (preferably Daily timeframe for accuracy).
Input Your Portfolio Symbols:
Open the indicator settings (gear icon).
In the "Symbol 1" to "Symbol 15" groups, fill in:
Symbol: Enter the ticker (e.g., NSE:INFY).
Year/Month/Day: Select your buy date (e.g., 2024-07-01).
Buy Price: Your purchase price per unit.
Stoploss: Your exit price if things go south.
Units: How many shares you own.
Only fill what you need—leave extras blank. The table auto-adjusts to show only entered symbols.
Customize the Table (Optional):
In "Table settings":
Choose position (e.g., Top Right) and size (% of chart).
Toggle "Show Timeframe Columns" to add 1W/1M/3M/6M performance.
In "Color settings":
Pick colors for positive (green) and negative (red) cells.
Set "Color intensity cutoff (%)" to control how strong the colors get (e.g., 10% means changes above 10% max out the color).
Interpret the Table on Your Chart:
The table appears overlaid—scan rows for each symbol's stats.
Look at colors: Greener = better gains; redder = bigger losses.
Check CMP cell: Red means stoploss breached—consider selling!
Portfolio Gain/Loss at the top gives a quick overall health check.
For Best Results:
Use on a Daily chart to avoid CMP errors (the script will warn if on Weekly/Monthly).
Refresh the chart or wait for a new bar if data doesn't update immediately.
For Indian stocks, prefix with NSE: or BSE: (e.g., BSE:RELIANCE).
This is for tracking only—not trading signals. Combine with your strategy.
If no symbols show, ensure inputs are valid (e.g., buy price > 0, valid date).
Finally, this tool makes it quite easy for beginners to track their portfolios, while also giving advanced traders powerful and customizable insights. I'd love to hear your feedback—happy trading!
Trend Buy/Sell Fibonacci Range - KLTThe Trend Buy/Sell Fibonacci Range – KLT indicator identifies bullish and bearish trends based on where the closing price is located within a Fibonacci range calculated from the last N candles (default is 10). Instead of analyzing individual candles, this tool takes a broader view of price action using Fibonacci retracement levels across a dynamic multi-candle range.
How It Works:
Range Calculation
The indicator calculates the highest high and lowest low over the last N candles to define the active price range (default: 10 bars).
Fibonacci Levels
Within this range, Fibonacci levels (0.236, 0.382, 0.5, 0.618, 0.786) are dynamically computed. These levels act as internal thresholds to evaluate bullish or bearish pressure.
Trend Identification (via Close Position):
If the closing price is above the 0.618 level, it indicates strong buy pressure → the candle turns green and an upward triangle appears.
If the closing price is below the 0.382 level, it suggests strong sell pressure → the candle turns red and a downward triangle is displayed.
If the close lies between 0.382 and 0.618, the market is considered neutral, and the candle is gray.
Visual Elements:
Colored candles to immediately spot trend conditions.
Triangle signals (optional) for clear Buy/Sell markers.
Fibonacci level lines plotted on the chart for full context (can be toggled on/off).
Customization Options:
Lookback period (number of candles to calculate the range)
Fibonacci threshold levels (upper/lower)
Show/hide arrows and Fibonacci lines
Why Use This Indicator?
This tool is perfect for traders who want a simple visual method to assess trend strength based on price structure, not indicators derived from lagging moving averages. It offers:
Cleaner market structure analysis
Objective trend zones
Customizable sensitivity
Recommended Use:
Works well in conjunction with support/resistance zones, volume, or momentum indicators.
Applicable to any asset class or timeframe.
Credits:
Developed by KLT, combining structure-based logic with Fibonacci precision.
SPY, QQQ, VIX Status TableBased on Ripster EMA and 1 hour MTF Clouds, this custom TradingView indicator displays a visual trend status table for SPY, QQQ, and VIX using multiple timeframes and EMA-based logic to be used on any stock ticker.
🔍 Key Features:
✅ Tracks 3 symbols: SPY, QQQ, and VIX
✅ Multiple trend conditions:
10-min (5/12 EMA) Ripster cloud trend
10-min (34/50 EMA) Ripster cloud trend
1-Hour Multi-Timeframe Ripster EMA trend
Daily open/close trend
✅ Color-coded trend strength:
🟩 Green = Bullish
🟥 Red = Bearish
🟨 Yellow = Sideways
✅ TO save screen space, customizations available:
Show/hide individual rows (SPY, QQQ, VIX)
Show/hide any trend column (10m, 1H MTF, Daily)
Change header/background colors and font color
Bold white top row for readability
✅ Auto-updating table appears on your chart, top-right
This tool is great for active traders looking to quickly scan short-term and longer-term momentum in key market instruments without having to go back and forth market charts.
MA Table [RanaAlgo]The "MA Table " indicator is a comprehensive and visually appealing tool for tracking moving average signals in TradingView. Here's a short summary of its usefulness:
Key Features:
Dual MA Support:
Tracks both EMA (Exponential Moving Average) and SMA (Simple Moving Average) signals (10, 20, 30, 50, 100 periods).
Users can toggle visibility for EMA/SMA separately.
Clear Signal Visualization:
Displays Buy (▲) or Sell (▼) signals based on price position relative to each MA.
Color-coded (green for buy, red for sell) for quick interpretation.
Customizable Table Design:
Adjustable position (9 placement options), colors, text size, and border styling.
Alternating row colors improve readability.
Optional MA Plots:
Can display the actual MA lines on the chart for visual confirmation (with distinct colors/styles).
Usefulness:
Quick Overview: The table consolidates multiple MA signals in one place, saving time compared to checking each MA individually.
Trend Confirmation: Helps confirm trend strength when multiple MAs align (e.g., price above all MAs → strong uptrend).
Flexible: Suitable for both short-term (10-20 period) and long-term (50-100 period) traders.
Aesthetic: Professional design enhances chart clarity without clutter.
Ideal For:
Traders who rely on moving average crossovers or price-MA relationships.
Multi-timeframe analysis when combined with other tools.
Beginners learning MA strategies (clear visual feedback).
Advanced Range Theory - ART📊 Advanced Range Theory (ART): The Institutional Blueprint
Stop drawing lines. Start reading the blueprint of the market. Advanced Range Theory (ART) is not another support and resistance indicator; it is a military-grade market structure engine designed to decode the language of institutional capital. It operates on a single, powerful premise: markets move in phases of consolidation and expansion, and the key to anticipation lies in understanding the complete lifecycle of these phases.
ART provides a living, breathing map of the battlefield, identifying institutional accumulation zones and tracking them with unparalleled precision from their inception as "Pending" ranges to their ultimate classification after a breakout. This is your X-ray into the market's skeletal structure.
🔬 THEORETICAL FRAMEWORK: THE ARCHITECTURE OF PRICE ACTION
ART is built on a multi-layered system of logic that moves beyond static levels. It treats ranges as dynamic entities with a narrative—a beginning, a middle, and an end. The core of the system is the dynamic classification engine, which analyzes not just the range, but the character of the price action that resolves it.
1. The Range Lifecycle: From Accumulation to Classification
This is the revolutionary heart of ART. A range's true identity is only revealed by how it is broken.
Phase 1: PENDING (Yellow): A new range is identified based on a period of price consolidation (a "parent" candle followed by a minimum number of "inside" candles). At this stage, it is a neutral zone of potential energy—an area where institutions are likely building positions. It is a question the market has not yet answered.
Phase 2: MITIGATION & CLASSIFICATION: When price breaks out and reaches a calculated extension level, the range is considered "mitigated." At this exact moment, ART analyzes the breakout's DNA to classify the range's true intent:
TYPE 1 - BREAKOUT (Blue): Characterized by a strong, impulsive move with confirming volume. This is a high-conviction breakout, signaling aggressive institutional participation and the likely start of a new trend. It is a statement of intent.
TYPE 2 - REVERSAL (Orange): Occurs when price attempts to break one way but is aggressively rejected, reversing and breaking out the other side. This signals absorption and a "failed auction," often marking significant market turning points.
TYPE 3 - PIVOT (Green): A more balanced breakout, lacking the explosive momentum of a Type 1. This often represents a resolution after a period of indecision or a pivot within a larger trading range.
2. The Hierarchical Map: Source & S/R Levels
ART doesn't just draw boxes; it builds a genealogical map of market structure.
SOURCE LEVEL (Thick Gold Line): This is the "genesis" point—the most recently mitigated range. It acts as the primary point of origin for the current market swing and serves as a critical level for determining overall bias. Price action above the Source is generally bullish; below is bearish.
S/R LEVELS (Cyan Lines): When a range is mitigated, the price level where it broke becomes a key Support/Resistance zone for the future. ART tracks the two most recent S/R levels, as these often act as powerful magnets or rejection points for price.
3. The Multi-Factor Validation Engine
To eliminate noise and focus only on institutionally significant ranges, every potential range must pass a rigorous quality control check:
Time-Based Consolidation: Requires a minimum number of consecutive inside candles (minInsideCandles), ensuring a true period of balance.
Volatility-Based Significance: The range's size must be greater than a multiple of the Average True Range (minRangeSize), filtering out insignificant micro-consolidations.
Participation Confirmation: The parent candle of the range is checked against average volume to ensure there was meaningful activity during its formation.
⚙️ THE COMMAND CONSOLE: CONFIGURING YOUR ART ENGINE
Every input is designed to give you granular control over the detection engine, allowing you to tune ART to any market or timeframe with precision. Each tooltip in the script provides a deep dive, but here is a summary of the core controls.
🎯 ART Detection Engine
Minimum Inside Candles: The soul of the detection algorithm. It defines the minimum number of bars that must be contained within a single "parent" candle to qualify as a range. Higher values (3-4) find major, significant consolidation zones. Lower values (1-2) are more sensitive and will identify shorter-term accumulation patterns.
Extension Multiplier & Fibonacci Extension: These control the profit target projections. The Extension Multiplier uses a simple measured move (e.g., 1.0 = a 1:1 projection of the range's height). The Fibonacci Extension uses the golden ratio (1.618) for harmonically-derived targets.
Mitigation Method (Cross vs. Close): Determines how a breakout is confirmed. Cross is more responsive, triggering as soon as price touches the extension. Close is more conservative, requiring a full candle to close beyond the level, which helps filter out fake-outs from wicks.
Min Range Size (ATR): A crucial noise filter. It ensures that ART ignores tiny, insignificant ranges by requiring a range's height to be a certain multiple of the current market volatility (ATR).
📊 Display & Visual Configuration
These settings give you full control over the visual interface. You can toggle every single element—from the Webb Scanner to the S/R Levels—to create a clean or a comprehensive view. Choose a color theme that suits your charting environment or define a fully custom palette.
🕸️ Webb Analysis Scanner
This is a unique real-time flow analysis tool. It draws dynamic, animated lines from the current price to recent historical points. This visualization helps reveal hidden "tendrils" of momentum and short-term support/resistance that are not immediately obvious, acting as a "sonar" for immediate price flow.
📊 THE ANALYTICS HUB: YOUR DASHBOARD DECODED
The dashboard provides a real-time, at-a-glance intelligence briefing on the current state of market structure as seen by the ART engine.
RANGE METRICS: This section is a "census" of the market's structure. It tells you the total number of ranges identified, how many are still Pending (awaiting a breakout), how many are Unmitigated (active but not yet broken), and how many have been Mitigated (classified and complete).
TYPE BREAKDOWN: This is a powerful gauge of market character. A high count of Type 1 (Breakout) ranges suggests a strong, trending environment. A rising number of Type 2 (Reversal) ranges can signal market exhaustion and potential trend changes. A dominant Type 3 (Pivot) count indicates a balanced, rotational market.
KEY GUIDE: The Large dashboard includes a full legend, so you never have to guess what a line or color represents. It's your built-in user manual.
🎨 DECODING THE BLUEPRINT: A VISUAL INTERPRETATION GUIDE
Every line and color in ART is designed for instant, intuitive understanding.
The Range Lines:
Yellow Lines: A Pending range. This is an active zone of accumulation. Pay close attention.
Colored Lines (Blue/Orange/Green): An unmitigated, classified range. The color tells you its breakout character.
Dotted Lines: A Mitigated range. Its story has been told. These historical levels can still act as support or resistance.
The Identification Zones: These colored boxes appear at a range's origin point after it has been classified. They are the "birth certificate" of the range, permanently marking its type (Breakout, Reversal, or Pivot) and providing an immediate visual history of market behavior.
The Hierarchical Lines:
Thick Gold Line (Source): The most important line on your chart. It is the anchor for your bias.
Cyan Lines (S/R): High-probability decision points. Expect reactions here.
Purple Dotted Lines (Extensions): Logical, calculated profit targets for breaking ranges.
🔧 THE ARCHITECT'S VISION: THE DEVELOPMENT JOURNEY
ART was born from a deep frustration with the static and subjective nature of traditional market structure analysis. Drawing lines by hand is inconsistent, and most indicators are reactive, only confirming what has already happened. The goal was to create a proactive, objective, and dynamic framework that could think about the market in terms of phases and lifecycles.
The breakthrough came from a simple shift in perspective: a range's true character isn't defined when it forms, but by how it resolves. This led to the development of the "post-breakout classification engine," which waits for the market to show its hand before assigning a definitive type. The Webb Scanner was inspired by the desire to visualize the unseen, to create a tool that could feel the immediate "pull" and "push" of price flow. The result is not just an indicator; it is a new language for interpreting price action, built on a foundation of logic, clarity, and precision.
⚠️ RISK DISCLAIMER & BEST PRACTICES
Advanced Range Theory is a professional-grade analytical tool designed to enhance a trader's decision-making process. It does not provide direct buy or sell signals. The levels and classifications it generates are based on historical price action and mathematical probabilities. All trading involves substantial risk, and past performance is not indicative of future results. Always use this tool in conjunction with a robust risk management plan.
"I fear not the man who has practiced 10,000 kicks once, but I fear the man who has practiced one kick 10,000 times."
— Dskyz, Trade with insight. Trade with anticipation.
— Bruce Lee
Info TableOverview
The Info Table V1 is a versatile TradingView indicator tailored for intraday futures traders, particularly those focusing on MESM2 (Micro E-mini S&P 500 futures) on 1-minute charts. It presents essential market insights through two customizable tables: the Main Table for predictive and macro metrics, and the New Metrics Table for momentum and volatility indicators. Designed for high-activity sessions like 9:30 AM–11:00 AM CDT, this tool helps traders assess price alignment, sentiment, and risk in real-time. Metrics update dynamically (except weekly COT data), with optional alerts for key conditions like volatility spikes or momentum shifts.
This indicator builds on foundational concepts like linear regression for predictions and adapts open-source elements for enhanced functionality. Gradient code is adapted from TradingView's Color Library. QQE logic is adapted from LuxAlgo's QQE Weighted Oscillator, licensed under CC BY-NC-SA 4.0. The script is released under the Mozilla Public License 2.0.
Key Features
Two Customizable Tables: Positioned independently (e.g., top-right for Main, bottom-right for New Metrics) with toggle options to show/hide for a clutter-free chart.
Gradient Coloring: User-defined high/low colors (default green/red) for quick visual interpretation of extremes, such as overbought/oversold or high volatility.
Arrows for Directional Bias: In the New Metrics Table, up (↑) or down (↓) arrows appear in value cells based on metric thresholds (top/bottom 25% of range), indicating bullish/high or bearish/low conditions.
Consensus Highlighting: The New Metrics Table's title cells ("Metric" and "Value") turn green if all arrows are ↑ (strong bullish consensus), red if all are ↓ (strong bearish consensus), or gray otherwise.
Predicted Price Plot: Optional line (default blue) overlaying the ML-predicted price for visual comparison with actual price action.
Alerts: Notifications for high/low Frahm Volatility (≥8 or ≤3) and QQE Bias crosses (bullish/bearish momentum shifts).
Main Table Metrics
This table focuses on predictive, positional, and macro insights:
ML-Predicted Price: A linear regression forecast using normalized price, volume, and RSI over a customizable lookback (default 500 bars). Gradient scales from low (red) to high (green) relative to the current price ± threshold (default 100 points).
Deviation %: Percentage difference between current price and predicted price. Gradient highlights extremes (±0.5% default threshold), signaling potential overextensions.
VWAP Deviation %: Percentage difference from Volume Weighted Average Price (VWAP). Gradient indicates if price is above (green) or below (red) fair value (±0.5% default).
FRED UNRATE % Change: Percentage change in U.S. unemployment rate (via FRED data). Cell turns red for increases (economic weakness), green for decreases (strength), gray if zero or disabled.
Open Interest: Total open MESM2 futures contracts. Gradient scales from low (red) to high (green) up to a hardcoded 300,000 threshold, reflecting market participation.
COT Commercial Long/Short: Weekly Commitment of Traders data for commercial positions. Long cell green if longs > shorts (bullish institutional sentiment); Short cell red if shorts > longs (bearish); gray otherwise.
New Metrics Table Metrics
This table emphasizes technical momentum and volatility, with arrows for quick bias assessment:
QQE Bias: Smoothed RSI vs. trailing stop (default length 14, factor 4.236, smooth 5). Green for bullish (RSI > stop, ↑ arrow), red for bearish (RSI < stop, ↓ arrow), gray for neutral.
RSI: Relative Strength Index (default period 14). Gradient from oversold (red, <30 + threshold offset, ↓ arrow if ≤40) to overbought (green, >70 - offset, ↑ arrow if ≥60).
ATR Volatility: Score (1–20) based on Average True Range (default period 14, lookback 50). High scores (green, ↑ if ≥15) signal swings; low (red, ↓ if ≤5) indicate calm.
ADX Trend: Average Directional Index (default period 14). Gradient from weak (red, ↓ if ≤0.25×25 threshold) to strong trends (green, ↑ if ≥0.75×25).
Volume Momentum: Score (1–20) comparing current to historical volume (lookback 50). High (green, ↑ if ≥15) suggests pressure; low (red, ↓ if ≤5) implies weakness.
Frahm Volatility: Score (1–20) from true range over a window (default 24 hours, multiplier 9). Dynamic gradient (green/red/yellow); ↑ if ≥7.5, ↓ if ≤2.5.
Frahm Avg Candle (Ticks): Average candle size in ticks over the window. Blue gradient (or dynamic green/red/yellow); ↑ if ≥0.75 percentile, ↓ if ≤0.25.
Arrows trigger on metric-specific logic (e.g., RSI ≥60 for ↑), providing directional cues without strict color ties.
Customization Options
Adapt the indicator to your strategy:
ML Inputs: Lookback (10–5000 bars) and RSI period (2+) for prediction sensitivity—shorter for volatility, longer for trends.
Timeframes: Individual per metric (e.g., 1H for QQE Bias to match higher frames; blank for chart timeframe).
Thresholds: Adjust gradients and arrows (e.g., Deviation 0.1–5%, ADX 0–100, RSI overbought/oversold).
QQE Settings: Length, factor, and smooth for fine-tuned momentum.
Data Toggles: Enable/disable FRED, Open Interest, COT for focus (e.g., disable macro for pure intraday).
Frahm Options: Window hours (1+), scale multiplier (1–10), dynamic colors for avg candle.
Plot/Table: Line color, positions, gradients, and visibility.
Ideal Use Case
Perfect for MESM2 scalpers and trend traders. Use the Main Table for entry confirmation via predicted deviations and institutional positioning. Leverage the New Metrics Table arrows for short-term signals—enter bullish on green consensus (all ↑), avoid chop on low volatility. Set alerts to catch shifts without constant monitoring.
Why It's Valuable
Info Table V1 consolidates diverse metrics into actionable visuals, answering critical questions: Is price mispriced? Is momentum aligning? Is volatility manageable? With real-time updates, consensus highlights, and extensive customization, it enhances precision in fast markets, reducing guesswork for confident trades.
Note: Optimized for futures; some metrics (OI, COT) unavailable on non-futures symbols. Test on demo accounts. No financial advice—use at your own risk.
The provided script reuses open-source elements from TradingView's Color Library and LuxAlgo's QQE Weighted Oscillator, as noted in the script comments and description. Credits are appropriately given in both the description and code comments, satisfying the requirement for attribution.
Regarding significant improvements and proportion:
The QQE logic comprises approximately 15 lines of code in a script exceeding 400 lines, representing a small proportion (<5%).
Adaptations include integration with multi-timeframe support via request.security, user-customizable inputs for length, factor, and smooth, and application within a broader table-based indicator for momentum bias display (with color gradients, arrows, and alerts). This extends the original QQE beyond standalone oscillator use, incorporating it as one of seven metrics in the New Metrics Table for confluence analysis (e.g., consensus highlighting when all metrics align). These are functional enhancements, not mere stylistic or variable changes.
The Color Library usage is via official import (import TradingView/Color/1 as Color), leveraging built-in gradient functions without copying code, and applied to enhance visual interpretation across multiple metrics.
The script complies with the rules: reused code is minimal, significantly improved through integration and expansion, and properly credited. It qualifies for open-source publication under the Mozilla Public License 2.0, as stated.
