Z-Score Multi-Model ClusteringA price/volume clustering framework combining three market behavior models into a single indicator. Designed to help identify emerging trend strength, turning points, and volatility-driven entries or exits.
🔍 How It Works
This indicator classifies market states by comparing normalized price/volume behavior (via Z-Score) to different types of statistical or geometric "cluster centers." You can choose from three clustering approaches:
🧠 Clustering Models
1. Percentile (Z+CVD) – Trend Momentum Bias
Uses volume Z-Score + Cumulative Volume Delta (CVD).
Detects institutional pressure by clustering volume surges with directional delta.
Best for: Breakouts, momentum trades, volume-led reversals.
Cluster Colors:
🔹 Green triangle = Strong bullish confluence
🔻 Red triangle = Bearish divergence (bull trap risk)
⚪ Gray = Neutral/low conviction
2. Euclidean (Z+Slope) – Swing Mean-Reversion
Measures the angle of recent Z-score slope and compares it to directional cluster centers.
Helps detect early directional shifts or exhaustion.
Best for: Swing entries, pullback setups, exit timing
3. Hilbert Phase – Turn Detection via Signal Phase
Applies Hilbert Transform to the Z-Score, measuring the phase difference between trend and oscillator components.
Ideal for anticipating turns or detecting cyclical inflection points.
Useful for: Scalping, top/bottom spotting, volatility fades
✅ Features
Auto-updating cluster logic based on current data
Tooltips and clean user interface
Optional cluster bar coloring (can be toggled off)
Signal-only plotting keeps candlesticks readable
Clear entry/exit logic with triangle markers
Supports trend, swing, and oscillation-based systems
🛠️ Suggested Use Cases
Combine with VWAP, Session High/Low, or Liquidity Zones to confirm entry conditions.
Use Cluster 2 (strong bullish) on pullbacks to trend structure for add-on entries.
Use Cluster 1 in strong trends to watch for potential traps or exits.
Toggle models based on your strategy: e.g., Hilbert for scalping, Percentile for macro trend breaks.
🧪 Best Timeframes
Works across all markets and timeframes
For Percentile (Z+CVD), use intraday TF with 1m–5m CVD source
Hilbert and Euclidean preferred on 5m–1h for accurate slope/phase signals
⚠️ Notes
Clusters do not generate trade signals alone; use them in context with structure, VWAP, or trend filters.
Marker signals are filtered with a magnitude threshold to reduce noise.
Statistics
Multi-Crypto Principal Component AnalysisVersion 0.2
## 📌 Multi-Crypto Principal Component Analysis (PCA) — Indicator Summary
### 🎯 Purpose
This indicator identifies **cryptocurrency assets that are behaving differently** from the rest of the market, using a simplified approach inspired by Principal Component Analysis (PCA). It’s designed to help traders spot **cross-market divergences**, detect outliers, and improve asset selection and correlation-based strategies.
### ⚙️ How It Works
The indicator analyzes the **log returns** of up to 7 user-defined assets over a configurable lookback period (default: 100 bars). It computes the **z-score** (standardized deviation) for each asset’s return series and compares it against the average behavior of the group.
If an asset’s behavior deviates significantly (beyond a threshold of 1.5 standard deviations), it’s flagged as an **outlier**.
- Each outlier is plotted as a **colored dot horizontally spaced** above the price bar
- Up to **3 dots per bar** are shown for visual clarity
This PCA-style detection works in real time, directly on the chart, and gives you a quick overview of which assets are breaking correlation.
### 🔧 Inputs
- 🕒 **Lookback Period**: Number of bars to analyze (default: 100)
- 🔢 **Assets 1–7**: Choose any 7 crypto symbols from any exchange
- 🎨 **Colors**: Predefined per asset (e.g. BTCUSDT = red, ETHUSDT = yellow)
- 📈 **Threshold**: Internal (1.5 std dev); adjustable in code if needed
### 📊 Outputs
- 🟢 Dots above candles representing assets that are acting as outliers
- 🧠 Real-time clustering insight based on statistical deviation
- 🧭 Spatially spaced dots to avoid visual overlap when multiple outliers appear
### ⚠️ Limitations
- This is a **PCA-inspired approximation**, not true matrix-based PCA
- It does **not compute principal components or eigenvectors**
- Sensitivity may vary with asset volatility or sparse trading data
- Real PCA requires external tools like Python or R for full dimensional analysis
This tool is ideal for traders who want real-time crypto correlation insights without needing external data science platforms. It’s lightweight, fast, and highly visual — and gives you a powerful lens into market dislocations across multiple assets.
M2 Global G13 Liquidity (Custom & Shift, US DXY Adj.)🌎 M2 Global G13 Liquidity index (Custom & Shift, US DXY Adj.)
💡 Indicator Overview
The M2 Global G13 Liquidity indicator combines the M2 liquidity of 13 major countries, allowing users to selectively include or exclude each country to visualize global capital flows and potential investment liquidity at a glance.
Each country's M2 data is converted to USD using real-time exchange rates, and the US M2 is further adjusted using the Dollar Index (DXY) to reflect the impact of dollar strength or weakness on US liquidity.
✅ What is M2?
M2 is a broad measure of money supply that includes cash, demand deposits, savings deposits, and certain financial products.
It represents a country's overall liquidity and capital supply and is often interpreted as "dry powder" ready to be deployed into various assets such as equities, real estate, and bonds.
Therefore, M2 serves as a crucial benchmark for assessing a country's potential investment capacity that can flow into markets at any time.
💰 Exchange Rate & Dollar Index Adjustment
- All country M2 data is converted from local currencies to USD.
- The US M2 is further adjusted using the Dollar Index (DXY) to better reflect its real global power:
- DXY > 100 → Liquidity contraction (strong dollar effect)
- DXY < 100 → Liquidity expansion (weak dollar effect)
🗺️ Country Selection Options
- Default selection: United States
- Major selections: China, Eurozone, Japan, United Kingdom (core G5 economies)
- Additional selections: Switzerland, Canada, India, Russia, Brazil, South Korea, Mexico, South Africa
- Users can freely add or remove countries to customize the indicator to match their analytical needs.
📈 Example Use Cases
- Monitor global capital flows: Track worldwide liquidity trends and detect potential market risk signals.
- Analyze exchange rate and monetary policy trends: Compare dollar strength with major central bank policies.
- Benchmark against equity indices: Evaluate correlations with MSCI World, KOSPI, NASDAQ, etc.
- Valuation analysis: Compare overall liquidity levels to equity index prices or market capitalization to assess relative valuation and identify potential overvaluation or undervaluation.
- Crisis response strategy: Identify liquidity contraction during global credit crises or deleveraging phases.
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🌎 M2 글로벌 G13 유동성 지수 (Custom & Shift, US DXY Adj.)
💡 지표 소개
M2 Global G13 Liquidity 지표는 세계 13개 주요국의 M2 유동성을 선택적으로 결합하여, 글로벌 자금 흐름과 잠재 투자 자금을 한눈에 시각화할 수 있도록 설계된 종합 유동성 지표입니다.
국가별 M2 데이터를 환율과 결합해 달러 기준으로 표준화하며, 특히 미국 M2는 달러지수(DXY)로 보정하여 달러 강약에 따른 파급력을 반영합니다.
✅ M2란?
M2는 광의 통화지표로, 현금 + 요구불 예금 + 저축성 예금 + 일부 금융상품을 포함합니다.
이는 한 국가의 유동성 수준과 자금 공급 상태를 나타내는 핵심 거시경제 지표이며, **주식·부동산·채권 등 다양한 자산에 투자될 준비가 된 '대기자금'**으로도 해석됩니다.
따라서 M2는 투자시장으로 언제든지 흘러들어갈 수 있는 잠재적 투자 역량을 평가할 때 중요한 기준입니다.
💰 환율 및 달러지수 보정
- 모든 국가 M2는 자국 통화에서 **달러(USD)**로 환산됩니다.
- 특히 미국 M2는 달러 가치의 글로벌 실질 파워를 평가하기 위해 DXY 보정을 적용합니다.
- DXY > 100 → 유동성 축소 (강달러 효과)
- DXY < 100 → 유동성 확대 (약달러 효과)
🗺️ 국가별 선택 옵션
- 기본 선택: 미국
- 주요 선택: 중국, 유로존, 일본, 영국 (주요 G5)
- 추가 선택: 스위스, 캐나다, 인도, 러시아, 브라질, 한국, 멕시코, 남아공
- 사용자는 각 국가를 자유롭게 더하거나 빼면서 커스터마이즈할 수 있습니다.
📈 활용 예시
- 글로벌 자금 흐름 모니터링: 전세계 유동성 추세 및 시장 리스크 신호 분석
- 환율/금리 정책 분석: 달러 강약과 주요국 정책 변화 비교
- 주가지수 벤치마크 비교: MSCI World, 코스피, 나스닥 등과 상관관계 확인
- 밸류에이션 분석: 전체 유동성 수준을 주가지수나 시가총액과 비교하여, 시장의 상대적 고평가·저평가 여부를 평가
- 위기 대응 전략: 글로벌 신용위기·자금 긴축 국면 대비
3D Surface Modeling [PhenLabs]📊 3D Surface Modeling
Version: PineScript™ v6
📌 Description
The 3D Surface Modeling indicator revolutionizes technical analysis by generating three-dimensional visualizations of multiple technical indicators across various timeframes. This advanced analytical tool processes and renders complex indicator data through a sophisticated matrix-based calculation system, creating an intuitive 3D surface representation of market dynamics.
The indicator employs array-based computations to simultaneously analyze multiple instances of selected technical indicators, mapping their behavior patterns across different temporal dimensions. This unique approach enables traders to identify complex market patterns and relationships that may be invisible in traditional 2D charts.
🚀 Points of Innovation
Matrix-Based Computation Engine: Processes up to 500 concurrent indicator calculations in real-time
Dynamic 3D Rendering System: Creates depth perception through sophisticated line arrays and color gradients
Multi-Indicator Integration: Seamlessly combines VWAP, Hurst, RSI, Stochastic, CCI, MFI, and Fractal Dimension analyses
Adaptive Scaling Algorithm: Automatically adjusts visualization parameters based on indicator type and market conditions
🔧 Core Components
Indicator Processing Module: Handles real-time calculation of multiple technical indicators using array-based mathematics
3D Visualization Engine: Converts indicator data into three-dimensional surfaces using line arrays and color mapping
Dynamic Scaling System: Implements custom normalization algorithms for different indicator types
Color Gradient Generator: Creates depth perception through programmatic color transitions
🔥 Key Features
Multi-Indicator Support: Comprehensive analysis across seven different technical indicators
Customizable Visualization: User-defined color schemes and line width parameters
Real-time Processing: Continuous calculation and rendering of 3D surfaces
Cross-Timeframe Analysis: Simultaneous visualization of indicator behavior across multiple periods
🎨 Visualization
Surface Plot: Three-dimensional representation using up to 500 lines with dynamic color gradients
Depth Indicators: Color intensity variations showing indicator value magnitude
Pattern Recognition: Visual identification of market structures across multiple timeframes
📖 Usage Guidelines
Indicator Selection
Type: VWAP, Hurst, RSI, Stochastic, CCI, MFI, Fractal Dimension
Default: VWAP
Starting Length: Minimum 5 periods
Default: 10
Step Size: Interval between calculations
Range: 1-10
Visualization Parameters
Color Scheme: Green, Red, Blue options
Line Width: 1-5 pixels
Surface Resolution: Up to 500 lines
✅ Best Use Cases
Multi-timeframe market analysis
Pattern recognition across different technical indicators
Trend strength assessment through 3D visualization
Market behavior study across multiple periods
⚠️ Limitations
High computational resource requirements
Maximum 500 line restriction
Requires substantial historical data
Complex visualization learning curve
🔬 How It Works
1. Data Processing:
Calculates selected indicator values across multiple timeframes
Stores results in multi-dimensional arrays
Applies custom scaling algorithms
2. Visualization Generation:
Creates line arrays for 3D surface representation
Applies color gradients based on value magnitude
Renders real-time updates to surface plot
3. Display Integration:
Synchronizes with chart timeframe
Updates surface plot dynamically
Maintains visual consistency across updates
🌟 Credits:
Inspired by LonesomeTheBlue (modified for multiple indicator types with scaling fixes and additional unique mappings)
💡 Note:
Optimal performance requires sufficient computing resources and historical data. Users should start with default settings and gradually adjust parameters based on their analysis requirements and system capabilities.
Average Daily % Change by Weekday📊 Average Daily % Change by Weekday
This script calculates and displays the average daily percentage change for each weekday (Monday through Sunday) based on historical price data. It helps traders analyze which days tend to be bullish or bearish over a selected backtest date range.
✅ Features:
Customizable date range (From Year/Month/Day to To Year/Month/Day)
Calculates average % change for each weekday (Mon–Sun)
Supports assets that trade 7 days (e.g., crypto)
Color-coded outputs (green = positive, red = negative)
Final results shown as a table in the bottom-right corner
Works only on the 1D timeframe (daily)
🧠 How it works:
For each day within the selected date range:
The script calculates the % change as: (Close - Open) / Open * 100
Then, it groups the data by weekday and averages the values
This gives you insight into how each day of the week behaves historically for the current asset.
⚠️ Notes:
This script only works on daily (1D) timeframes.
For most accurate results, use it on assets with long trading history (e.g., BTCUSD).
Designed for educational and statistical analysis purposes.
NQ Hourly Standard Deviation ZonesNQ Hourly Standard Deviation ZonesDescriptionThe NQ Hourly Standard Deviation Zones indicator is designed for traders analyzing the NASDAQ 100 futures (NQ) on an hourly timeframe. It plots dynamic support and resistance zones based on historical standard deviation (SD) levels calculated from the hourly open price. These zones represent the expected price range for each hour of the trading day, offering insights into potential price targets, reversals, or breakout levels. The indicator is highly customizable, allowing users to adjust the data period, display settings, and visual preferences to suit their trading style.The indicator calculates and displays:
• 0.5 SD Zones: Representing the price levels one-half standard deviation above and below the hourly open.
• 1.0 SD Zones: Representing the price levels one standard deviation above and below the hourly open.
• Hourly Open Line: A reference line marking the hourly open price.
These zones are derived from pre-calculated standard deviation data for the high and low price movements relative to the hourly open, segmented by each hour of the day (0–23). Users can select from multiple historical data periods (3 months to 17+ years) to align the zones with their preferred lookback period, accommodating both short-term and long-term trading strategies.Key Features
• Customizable Data Periods: Choose from 3 months, 6 months, 9 months, 1 year, 2 years, 3 years, 4 years, 5 years, 10 years, 15 years, or 17+ years of historical data to calculate standard deviation zones.
• RTH Filter: Option to display zones only during Regular Trading Hours (RTH, 9:00–15:59, America/New_York timezone) for traders focusing on the main trading session.
• Visual Customization:
• Toggle visibility of 0.5 SD and 1.0 SD labels.
• Customize line styles (Solid, Dotted, Dashed) and colors for 0.5 SD and 1.0 SD lines.
• Enable or disable shaded fills between the 0.5 SD and 1.0 SD zones, with customizable fill color.
• Timezone Support: Aligns with user-specified timezone (default: America/New_York) for accurate hourly calculations.
• Dynamic Updates: Zones are redrawn at the start of each new hourly bar, ensuring real-time relevance.
How It WorksThe indicator uses pre-computed standard deviation values for price movements (high and low) from the hourly open, based on the selected data period. For each hour of the day:
• High Zones: The +0.5 SD and +1.0 SD levels are plotted above the hourly open price.
• Low Zones: The -0.5 SD and -1.0 SD levels are plotted below the hourly open price.
• Hourly Open: A dotted line marks the open price for reference.
• Fills: Optional shaded areas between the 0.5 SD and 1.0 SD zones highlight the expected price range.
• Labels: Optional labels display "+0.5 σ," "-0.5 σ," "+1.0 σ," "-1.0 σ," and "h.o" (hourly open) at the end of each hourly bar for clarity.
The zones are plotted as horizontal lines spanning the duration of the hour, with fills and labels updated dynamically as new hourly bars form. The indicator clears previous lines and labels at the start of each new hour to maintain a clean chart.Usage
• Intraday Trading: Use the 0.5 SD and 1.0 SD zones as dynamic support and resistance levels for identifying potential entry/exit points, reversals, or breakout opportunities.
• Range Trading: The zones help visualize the expected price range for each hour, aiding in range-bound strategies.
• Risk Management: The 1.0 SD zones represent statistically significant levels, useful for setting stop-loss or take-profit levels.
• Session Filtering: Enable the "Show RTH Only" option to focus on high-liquidity hours, ideal for day traders.
• Historical Analysis: Select different data periods to analyze how price behavior varies over short-term (e.g., 3 months) versus long-term (e.g., 17+ years) market conditions.
Settings
• Settings:
• Show RTH Only (9:00–15:59): Toggle to display zones only during Regular Trading Hours (default: true).
• Timezone: Select the timezone for accurate hourly alignment (default: America/New_York).
• Select Data Period: Choose the historical data period for standard deviation calculations (options: 3 Months, 6 Months, 9 Months, 1 Year, 2 Years, 3 Years, 4 Years, 5 Years, 10 Years, 15 Years, 17+ Years; default: 17+ Years).
• Visuals:
• Show Fill: Toggle shaded areas between 0.5 SD and 1.0 SD zones (default: true).
• Fill Color: Customize the color and transparency of the fill (default: light gray, 90% transparency).
• 0.5 SD Line: Set the color (default: gray, 50% transparency) and style (Solid, Dotted, Dashed; default: Dashed) for 0.5 SD lines.
• 1.0 SD Line: Set the color (default: gray, 0% transparency) and style (Solid, Dotted, Dashed; default: Solid) for 1.0 SD lines.
• Show 0.5 SD Labels: Toggle visibility of 0.5 SD labels (default: true) and set their text color (default: gray).
• Show 1.0 SD Labels: Toggle visibility of 1.0 SD labels (default: true) and set their text color (default: gray).
Notes
• The indicator is optimized for the NASDAQ 100 futures (NQ) on an hourly timeframe. Ensure the chart is set to a compatible timeframe (e.g., 1-hour) for accurate results.
• Standard deviation values are pre-calculated and stored for each hour of the day, based on historical data. They are not dynamically recalculated from live data, ensuring consistent performance.
• The indicator uses up to 500 lines and labels to comply with TradingView’s rendering limits, ensuring smooth operation even on extended charts.
• For best results, use on liquid instruments like NQ futures, and consider combining with other technical indicators for confirmation.
Example Use CaseA trader focusing on NQ day trading can enable "Show RTH Only" and select a 3-month data period to plot zones for the 9:00–15:59 session. During the 10:00 AM hour, if the price approaches the +1.0 SD zone, the trader might anticipate resistance and consider a short position, using the -1.0 SD zone as a potential target. Conversely, a break above the +1.0 SD zone could signal a breakout, prompting a long position.Limitations
• The indicator relies on pre-computed standard deviation values, which may not reflect real-time market volatility.
• It is designed specifically for hourly charts and may not function correctly on other timeframes.
• The RTH filter assumes a standard trading session (9:00–15:59); custom session times are not supported.
AuthorThis indicator is designed for traders seeking a statistical approach to intraday price analysis, leveraging historical volatility patterns to inform trading decisions.
Korea M2 Liquidity Index💡 Korea M2 Liquidity Index
- This indicator visualizes Korea's M2 liquidity trends, designed to help both domestic and global investors easily understand the overall money supply situation in the Korean economy.
- In particular, by comparing it with the KOSPI index, investors can assess the equity market level relative to liquidity, allowing for a more precise valuation analysis to determine whether the Korean stock market is overvalued or undervalued.
✅ What is M2?
- M2 is a broad measure of money supply, which includes cash, demand deposits, savings deposits, and certain financial products.
- It serves as a crucial macroeconomic indicator that reflects the overall liquidity and capital supply in the Korean economy.
💰 KRW and USD display options
- KRW basis: Displays the total M2 amount in Korean won (in trillion units).
- USD basis: Converts the total M2 amount into US dollars using the KRW/USD exchange rate(KRW/USD) making it useful for global investors or those analyzing in USD terms.
📊 Display style and interpretation
- Users can freely choose to display Korea’s M2 and liquidity index and turn them on or off as needed.
- The index is simplified and displayed in trillion won units, allowing for an intuitive view of long-term trends and structural changes.
- The Offset (days) feature enables temporal adjustments, making it easier to compare this indicator with other economic or financial data series.
🌏 Example use cases
- Domestic policy analysis: Analyze the correlation between Bank of Korea's monetary policy changes (base rates, liquidity injections, etc.) and M2 growth.
- FX and global capital flow analysis: Understand the relationship between KRW/USD exchange rate fluctuations and changes in domestic liquidity.
- Leading indicator for asset markets: Use it as a forward-looking signal for stock, real estate, and bond markets.
- Comparison with KOSPI index: Identify gaps between liquidity and market levels to support strategic investment decisions and evaluate market capitalization levels more precisely.
copyright @invest_hedgeway
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💡 Korea M2 Liquidity Index
- 이 지표는 대한민국의 M2 유동성 흐름을 시각화하여, 국내 및 글로벌 투자자들이 한국 경제의 자금 공급 상태를 한눈에 파악할 수 있도록 설계되었습니다.
- 특히 코스피 지수와 비교 분석함으로써 유동성 대비 주가지수 수준을 평가하고, 한국 증시의 상대적 고평가·저평가 여부를 판단해 보다 정교한 밸류에이션 분석에 활용할 수 있습니다.
✅ M2란?
- M2는 광의통화 지표로, 현금 + 요구불 예금 + 저축성 예금 + 금융상품(일부) 등을 포함하는 총 유동성을 의미합니다. 이는 한국 경제의 자금 공급 상태를 나타내는 중요한 거시경제 지표로 활용됩니다.
💰 KRW 및 USD 표시 선택
- KRW(원화) 기준: 한국 원화 기준으로 M2 총액(조 단위)을 나타냅니다.
- USD 기준: M2 총액을 환율(KRW/USD) 기준으로 달러화 환산 후 표시하여, 글로벌 투자자나 달러화 기준 평가 시 활용 가능합니다.
📊 표시 방식과 해석
- 사용자는 한국의 M2와 유동성지수를 자유롭게 선택해 원하는 방식으로 켜거나 끌 수 있습니다.
- 지표는 조원(Trillion won) 단위로 단순화해 표시되며, 장기 흐름과 추세 변화를 시각적으로 확인할 수 있습니다.
- Offset (days) 기능을 통해 시리즈를 시차 조정할 수 있어, 다른 경제 지표와의 비교 분석에 유용합니다.
🌏 활용 예시
- 국내 정책 분석: 한국은행의 통화정책 변화(기준금리, 유동성 공급 등)와 M2 증가율 간 상관성 분석.
- 환율 및 글로벌 자금 흐름 분석: 원/달러 환율 변동과 유동성 간 상관관계 파악.
- 주식, 부동산, 채권 등 자산시장 선행 지표로서 활용.
- 코스피 지수와의 비교 분석: 시장 유동성과 지수의 괴리를 파악하여 전략적 투자 판단과 시가총액 수준에 대한 평가에 활용.
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Correlation Coefficient with MA & BB中文版介紹
相關係數、移動平均線與布林帶指標 (Correlation Coefficient with MA & BB)
這個 Pine Script 指標是一款強大的工具，旨在幫助交易者和投資者深入分析兩個市場標的之間的關係強度與方向，並結合移動平均線 (MA) 和布林帶 (BB) 來進一步洞察這種關係的趨勢和波動性。
無論您是想尋找配對交易機會、管理投資組合風險，還是僅僅想更好地理解市場動態，這個指標都能提供有價值的見解。
指標特色與功能：
動態相關係數計算：
您可以選擇任何您想比較的股票、商品或加密貨幣代號（例如，預設為 GOOG）。
指標會自動計算當前圖表（主數據源，預設為收盤價）與您指定標的之間的相關係數。
相關係數值介於 -1 (完美負相關) 至 1 (完美正相關) 之間，0 表示無線性關係。
視覺化呈現相關係數線，並標示 1、0、-1 參考水平線，同時填充完美相關區間，讓您一目了然。
特別之處：程式碼中包含了 ticker.modify，確保比較標的數據考慮了股息調整或延長交易時段，使相關性分析更加精準。
相關係數的移動平均線 (MA)：
為了平滑相關係數的短期波動，指標提供了多種移動平均線類型供您選擇，包括：SMA、EMA、WMA、SMMA。
您可以設定計算 MA 的週期長度（預設 20 週期）。
這條 MA 線有助於識別相關係數的長期趨勢，判斷兩者關係是趨於增強還是減弱。
相關係數的布林帶 (BB)：
將布林帶應用於相關係數，以衡量其波動性和相對高低水平。
中軌與您選擇的移動平均線保持一致。
上軌和下軌則根據相關係數的標準差和您設定的 Z 值（預設 2.0 倍標準差）動態調整。
布林帶可以幫助您識別相關係數何時處於極端水平，可能預示著未來會回歸均值。
如何運用這個指標？
配對交易策略：當兩個通常高度相關的資產，其相關係數短期內顯著偏離平均水平（例如，一個資產價格上漲而另一個原地踏步），您可能可以考慮利用此「失衡」進行配對交易。
投資組合多元化：了解不同資產之間的相關性，有助於構建更穩健的投資組合，避免過度集中於同向變動的資產，有效分散風險。
市場趨勢洞察：透過觀察相關係數的趨勢和波動，您可以更好地理解不同市場板塊或資產類別之間的聯動性，為您的宏觀經濟分析提供數據支持。
請注意，相關性不等於因果性。使用此指標時，請結合您的整體交易策略、宏觀經濟分析以及其他技術指標進行綜合判斷。
English Version Introduction
Correlation Coefficient with Moving Average & Bollinger Bands Indicator (Correlation Coefficient with MA & BB)
This Pine Script indicator is a powerful tool designed to help traders and investors deeply analyze the strength and direction of the relationship between two market instruments. It integrates Moving Averages (MA) and Bollinger Bands (BB) to further insight into the trend and volatility of this relationship.
Whether you're looking for pair trading opportunities, managing portfolio risk, or simply aiming to better understand market dynamics, this indicator can provide valuable insights.
Indicator Features & Functionality:
Dynamic Correlation Coefficient Calculation:
You can select any symbol you wish to compare (e.g., default is GOOG), be it stocks, commodities, or cryptocurrencies.
The indicator automatically calculates the correlation coefficient between the current chart (main data source, default is close price) and your specified symbol.
Correlation values range from -1 (perfect negative correlation) to 1 (perfect positive correlation), with 0 indicating no linear relationship.
It visually plots the correlation line, marks 1, 0, -1 reference levels, and fills the perfect correlation zone for clear visualization.
Special Feature: The code includes ticker.modify, ensuring that the comparative symbol's data accounts for dividend adjustments or extended trading hours, leading to more precise correlation analysis.
Moving Average (MA) for Correlation:
To smooth out short-term fluctuations in the correlation coefficient, the indicator offers multiple MA types for you to choose from: SMA, EMA, WMA, SMMA.
You can set the length of the MA period (default 20 periods).
This MA line helps identify the long-term trend of the correlation coefficient, indicating whether the relationship between the two instruments is strengthening or weakening.
Bollinger Bands (BB) for Correlation:
Bollinger Bands are applied to the correlation coefficient itself to gauge its volatility and relative high/low levels.
The middle band aligns with your chosen Moving Average.
The upper and lower bands dynamically adjust based on the correlation coefficient's standard deviation and your set Z-score (default 2.0 standard deviations).
Bollinger Bands can help you identify when the correlation coefficient is at extreme levels, potentially signaling a future reversion to the mean.
How to Utilize This Indicator:
Pair Trading Strategies: When two typically highly correlated assets show a significant short-term deviation from their average correlation (e.g., one asset's price rises while the other stagnates), you might consider exploiting this "imbalance" for pair trading.
Portfolio Diversification: Understanding the correlation between different assets helps build a more robust investment portfolio, preventing over-concentration in co-moving assets and effectively diversifying risk.
Market Trend Insight: By observing the trend and volatility of the correlation coefficient, you can better understand the联动 (interconnectedness) between different market sectors or asset classes, providing data support for your macroeconomic analysis.
Please note that correlation does not imply causation. When using this indicator, combine it with your overall trading strategy, macroeconomic analysis, and other technical indicators for comprehensive decision-making.
Kase Convergence Divergence [BackQuant]Kase Convergence Divergence
The Kase Convergence Divergence is a sophisticated oscillator designed to measure directional market strength through the lens of volatility-adjusted log return structures. Inspired by Cynthia Kase’s work on statistical momentum and price projection ranges, this unique indicator offers a hybrid framework that merges signal processing, multi-length sweep logic, and adaptive smoothing techniques.
Unlike traditional momentum oscillators like MACD or RSI, which rely on static moving average differences, KCD introduces a dual-process system combining:
Kase-style statistical range projection (via log returns and volatility),
A sweeping loop of lookback lengths for robustness,
First and second derivative modes to capture both velocity and acceleration of price movement.
Core Logic & Computation
The KCD calculation is centered on two volatility-normalized transforms:
KSDI Up: Measures how far the current high has moved relative to a past low, normalized by return volatility.
KSDI Down: Measures how far the current low has moved relative to a past high, also normalized.
For every length in a user-defined sweep range (e.g., 25–35), both KSDI_up and KSDI_dn are computed, and their maximum values across the loop are retained. The difference between these two max values produces the raw signal:
KPO (Kase Projection Oscillator): Measures directional skew.
KCD (Kase Convergence Divergence): Defined as KPO – MA(KPO) — similar in spirit to MACD but structurally different.
Users can choose to visualize either the first derivative (KPO) , or the second derivative (KCD) , depending on market conditions or strategy style.
Key Features
✅ Multi-Length Sweep Logic: Improves signal reliability by aggregating statistical range projections across a set of lookbacks.
✅ Advanced Smoothing Modes: Supports DEMA, HMA, TEMA, LINREG, WMA and more for dynamic adaptation.
✅ Dual Derivative Modes: Choose between speed (first derivative) or smoothness (second derivative) to fit your trading regime.
✅ Color-Encoded Signal Bands: Heatmap-style oscillator coloring enhances visual feedback on trend strength.
✅ Candlestick Painting: Optional bar coloring makes it easy to spot trend shifts on the main chart.
✅ Adaptive Fill Zones: Green and red fills between the oscillator and zero line help distinguish bullish and bearish regimes at a glance.
Practical Applications
📈 Trend Confirmation: Use KCD as a secondary confirmation layer after breakout or pullback entries.
📉 Momentum Shifts: Crossover and crossunder of the zero line highlight potential regime changes.
📊 Strategy Filters: Incorporate into algos to avoid trendless or mean-reverting environments.
🧪 Derivative Switching: Flip between KPO and KCD modes depending on whether you want to measure acceleration or deceleration of price flow.
Alerts & Signals
Two built-in alerts help you catch regime shifts in real time:
Long Signal: Triggered when the selected oscillator crosses above zero.
Short Signal: Triggered when it crosses below zero.
These events can be used to generate entries, exits, or trend validation cues in multi-layer systems.
Conclusion
The Kase Convergence Divergence goes beyond traditional oscillators by offering a volatility-normalized, derivative-aware signal engine with enhanced visual dynamics. Its sweeping architecture and dynamic fill logic make it especially powerful for identifying trending environments, filtering chop, and adding statistical rigor to your trading toolkit.
Whether you’re a discretionary trader seeking precision, or a quant looking to model more robust return structures, KCD offers a creative yet analytically grounded solution.
RISK ROTATION MATRIX ║ BullVision [3.0]🔍 Overview
The Risk Rotation Matrix is a comprehensive market regime detection system that analyzes global market conditions across four critical domains: Liquidity, Macroeconomic, Crypto/Commodities, and Risk/Volatility. Through proprietary algorithms and advanced statistical analysis, it transforms 20+ diverse market metrics into a unified framework for identifying regime transitions and risk rotations.
This institutional-grade system aims to solve a fundamental challenge: how to synthesize complex, multi-domain market data into clear, actionable trading intelligence. By combining proprietary liquidity calculations with sophisticated cross-asset analysis.
The Four-Domain Architecture
1. 💧 LIQUIDITY DOMAIN
Our liquidity analysis combines standard metrics with proprietary calculations:
Proprietary Components:
Custom Global Liquidity Index (GLI): Unique formula aggregating central bank assets, credit spreads, and FX dynamics through our weighted algorithm
Federal Reserve Balance Proxy: Advanced calculation incorporating reverse repos, TGA fluctuations, and QE/QT impacts
China Liquidity Proxy: First-of-its-kind metric combining PBOC operations with FX-adjusted aggregates
Global M2 Composite: Custom multi-currency M2 aggregation with proprietary FX normalization
2. 📈 MACRO DOMAIN
Sophisticated integration of global economic indicators:
S&P 500: Momentum and trend analysis with custom z-score normalization
China Blue Chips: Asian market sentiment with correlation filtering
MBA Purchase Index: Real estate market health indicator
Emerging Markets (EEMS): Risk appetite measurement
Global ETF (URTH): Worldwide equity exposure tracking
Each metric undergoes proprietary transformation to ensure comparability and regime-specific sensitivity.
3. 🪙 CRYPTO/COMMODITIES DOMAIN
Unique cross-asset analysis combining:
Total Crypto Market Cap: Liquidity flow indicator with custom smoothing
Bitcoin SOPR: On-chain profitability analysis with adaptive periods
MVRV Z-Score: Advanced implementation with multiple MA options
BTC/Silver Ratio: Novel commodity-crypto relationship metric
Our algorithms detect when crypto markets lead or lag traditional assets, providing crucial timing signals.
4. ⚡ RISK/VOLATILITY DOMAIN
Advanced volatility regime detection through:
MOVE Index: Bond volatility with inverse correlation analysis
VVIX/VIX Ratio: Volatility-of-volatility for regime extremes
SKEW Index: Tail risk measurement with custom normalization
Credit Stress Composite: Proprietary combination of credit spreads
USDT Dominance: Crypto flight-to-safety indicator
All risk metrics are inverted and normalized to align with the unified scoring system.
🧠 Advanced Integration Methodology
Multi-Stage Processing Pipeline
Data Collection: Real-time aggregation from 20+ sources
Normalization: Custom z-score variants accounting for regime-specific volatility
Domain Scoring: Proprietary weighting within each domain
Cross-Domain Synthesis: Advanced correlation matrix between domains
Regime Detection: State-transition model identifying four market phases
Signal Generation: Composite score with adaptive smoothing
🔁 Composite Smoothing & Signal Generation
The user can apply smoothing (ALMA, EMA, etc.) to highlight trends and reduce noise. Smoothing length, type, and parameters are fully customizable for different trading styles.
🎯 Color Feedback & Market Regimes
Visual dynamics (color gradients, labels, trails, and quadrant placement) offer an at-a-glance interpretation of the market’s evolving risk environment—without forecasting or forward-looking assumptions.
🎯 The Quadrant Visualization System
Our innovative visual framework transforms complex calculations into intuitive intelligence:
Dynamic Ehlers Loop: Shows current position and momentum
Trailing History: Visual path of regime transitions
Real-Time Animation: Immediate feedback on condition changes
Multi-Layer Information: Depth through color, size, and positioning
🚀 Practical Applications
Primary Use Cases
Multi-Asset Portfolio Management: Optimize allocation across asset classes based on regime
Risk Budgeting: Adjust exposure dynamically with regime changes
Tactical Trading: Time entries/exits using regime transitions
Hedging Strategies: Implement protection before risk-off phases
Specific Trading Scenarios
Domain Divergence: When liquidity improves but risk metrics deteriorate
Early Rotation Detection: Crypto/commodity signals often lead broader markets
Volatility Regime Trades: Position for mean reversion or trend following
Cross-Asset Arbitrage: Exploit temporary dislocations between domains
⚙️ How It Works
The Composite Score Engine
The system's intelligence emerges from how it combines domains:
Each domain produces a normalized score (-2 to +2 range)
Proprietary algorithms weight domains based on market conditions
Composite score indicates overall market regime
Smoothing options (ALMA, EMA, etc.) optimize for different timeframes
Regime Classification
🟢 Risk-On (Green): Positive composite + positive momentum
🟠 Weakening (Orange): Positive composite + negative momentum
🔵 Recovery (Blue): Negative composite + positive momentum
🔴 Risk-Off (Red): Negative composite + negative momentum
Signal Interpretation Framework
The indicator provides three levels of analysis:
Composite Score: Overall market regime (-2 to +2)
Domain Scores: Identify which factors drive regime
Individual Metrics: Granular analysis of specific components
🎨 Features & Functionality
Core Components
Risk Rotation Quadrant: Primary visual interface with Ehlers loop
Data Matrix Dashboard: Real-time display of all 20+ metrics
Domain Aggregation: Separate scores for each domain
Composite Calculation: Unified score with multiple smoothing options
Customization Options
Selective Metrics: Enable/disable individual components
Period Adjustment: Optimize lookback for each metric
Smoothing Selection: 10 different MA types including ALMA
Visual Configuration: Quadrant scale, colors, trails, effects
Advanced Settings
Pre-smoothing: Reduce noise before final calculation
Adaptive Periods: Automatic adjustment during volatility
Correlation Filters: Remove redundant signals
Regime Memory: Hysteresis to prevent whipsaws
📋 Implementation Guide
Setup Process
Add to chart (optimized for daily, works on all timeframes)
Review default settings for your market focus
Adjust domain weights based on trading style
Configure visual preferences
Optimization by Trading Style
Position Trading: Longer periods (60-150), heavy smoothing
Swing Trading: Medium periods (20-60), balanced smoothing
Active Trading: Shorter periods (10-40), minimal smoothing
Best Practices
Monitor domain divergences for early signals
Use extreme readings (-1.5/+1.5) for high-conviction trades
Combine with price action for confirmation
Adjust parameters during major events (FOMC, earnings)
💎 What Makes This Unique
Beyond Traditional Indicators
Multi-Domain Integration: Only system combining liquidity, macro, crypto, and volatility
Proprietary Calculations: Custom formulas for GLI, Fed, China, and M2 proxies
Adaptive Architecture: Dynamically adjusts to market regimes
Institutional Depth: 20+ integrated metrics vs typical 3-5
Technical Innovation
Statistical Normalization: Custom z-score variants for cross-asset comparison
Correlation Management: Prevents double-counting related signals
Regime Persistence: Algorithms to identify sustainable vs temporary shifts
Visual Intelligence: Information-dense display without overwhelming
🔢 Performance Characteristics
Strengths
Early regime detection (typically 1-3 weeks ahead)
Robust across different market environments
Clear visual feedback reduces interpretation errors
Comprehensive coverage prevents blind spots
Optimal Conditions
Most effective with 100+ bars of history
Best on daily timeframe (4H minimum recommended)
Requires liquid markets for accurate signals
Performance improves with more enabled components
⚠️ Risk Considerations & Limitations
Important Disclaimers
Probabilistic system, not predictive
Requires understanding of macro relationships
Signals should complement other analysis
Past regime behavior doesn't guarantee future patterns
Known Limitations
Black swan events may cause temporary distortions
Central bank interventions can override signals
Requires active management during regime transitions
Not suitable for pure technical traders
💎 Conclusion
The Risk Rotation Matrix represents a new paradigm in market regime analysis. By combining proprietary liquidity calculations with comprehensive multi-domain monitoring, it provides institutional-grade intelligence previously available only to large funds. The system's strength lies not just in its individual components, but in how it synthesizes diverse market information into clear, actionable trading signals.
⚠️ Access & Intellectual Property Notice
This invite-only indicator contains proprietary algorithms, custom calculations, and years of quantitative research. The mathematical formulations for our liquidity proxies, cross-domain correlation matrices, and regime detection algorithms represent significant intellectual property. Access is restricted to protect these innovations and maintain their effectiveness for serious traders who understand the value of comprehensive market regime analysis.
Premium/Discount with Candle Open stats [Herman]Premium/Discount with Stats
This indicator is designed to help traders identify and analyze premium/discount zones on any timeframe while automatically tracking statistics on price behavior relative to these zones. It is especially valuable for traders looking to structure entries, manage targets, and quantify market reactions to prior session ranges.
What it draws on the chart
✅ Range High and Low Lines
For each selected timeframe period (15min, 30min 1H, 4H, Daily), the indicator plots the high and low of the completed previous period.
These lines are color-coded dynamically based on sweep detection:
If the high was swept (price broke the previous high), the high line is marked as Premium.
If the low was swept, the low line is marked as Discount.
If both were swept or neither, it uses the default color settings.
✅ Midline
An optional midline at the 50% level of the previous period’s high-low range.
Helpful for mean-reversion traders or anyone watching for retests of equilibrium.
✅ Quartile Lines (25%–75%)
Optional additional lines at 25% and 75% of the previous range, helping traders visualize inner range subdivisions.
✅ Open Price Line
Marks the open price of the previous period as a horizontal reference.
✅ Background Fills
The region between low and midline is shaded with the Discount color.
The region between high and midline is shaded with the Premium color.
These optional fills help highlight the premium and discount zones visually.
✅ Current Incomplete Period Lines (optional)
You can choose to display provisional high, low, midline, quartiles, and open for the current forming period.
These update in real-time until the period closes.
Sweep Detection Logic
The indicator automatically tracks if the current period price sweeps above the previous period’s high or below the low.
A "sweep" is simply defined as price exceeding the previous high/low while tracking is active.
The sweep status affects the colors of the premium/discount lines, helping traders see potential liquidity grabs or stop hunts.
What it counts and tracks (Statistics)
The script automatically compiles statistics over time:
✅ Total Touches
Counts how many times the price in a new period touches either the previous period’s high or low.
A “touch” is registered once per side per period.
✅ Midline Returns
Counts how often, after touching the previous high/low, price returns to the previous period’s midline.
Gives you a measure of mean-reversion success.
✅ Open Returns
Similarly, tracks how often price returns to the previous period’s open after touching the previous high/low.
✅ Return Percentages
Displays the percentage of touches that result in a return to midline or open.
These percentages are calculated live on your chart and updated after each period closes.
✅ Stats Table
A customizable on-chart table summarizing all of these stats in real-time.
Helps traders evaluate the effectiveness of range-based trading setups over time.
How it Works (Technical details)
On each new bar, the script checks if a new period (as defined by your timeframe selection) has begun.
When a new period starts, the previous period’s high, low, open, midline, quartiles are recorded and drawn on the chart.
The script then “watches” the current period:
Updates provisional high and low.
Detects sweeps of previous highs/lows.
Tracks if price returns to the previous period’s midline or open after those sweeps.
Increments statistical counters if conditions are met.
Background fills and lines update dynamically based on real-time data.
Intended Use Cases
This indicator is ideal for:
✅ Identifying premium/discount zones for swing or intraday trades.
✅ Spotting liquidity sweeps and possible manipulation zones.
✅ Structuring trades with logical, data-driven target zones (midline, open).
✅ Quantifying the probability of mean-reversion moves after liquidity events.
✅ Developing and backtesting range-based trading models with live stats.
Highly Customizable
Choose any timeframe for defining the premium/discount range.
Toggle visibility of midline, quartiles, open line, current period preview.
Full control over colors, line styles, line widths, and background shading.
Optional real-time statistical table with total counts and return percentages.
ShadowStats vs Official CPI YoY%This chart visualizes and compares the year-over-year (YoY) percentage change in the Consumer Price Index (CPI) as calculated by the U.S. government versus the alternative methodology used by ShadowStats, which reflects pre-1980 inflation measurement techniques. The red line represents ShadowStats' CPI YoY% estimates, while the blue line shows the official CPI YoY% reported by government sources. This side-by-side view highlights the divergence in reported inflation rates over time, particularly from the 1980s onward, offering a visual representation of how different calculation methods can lead to vastly different interpretations of inflation and purchasing power loss.
Trading CalculatorTrading Calculator Indicator
VIBE CODED WITH GROK 3
The Trading Calculator is a Pine Script indicator designed to perform quick and useful trading-related calculations directly on your chart. It allows traders to execute basic arithmetic operations—such as addition, subtraction, multiplication, and division—as well as calculate percent change and average using either numerical values or trading variables (e.g., close, open, high, low, volume). The indicator displays its results in a table that resembles a calculator interface, making it both functional and visually intuitive. Unlike typical indicators, it does not overlay on the price chart but instead appears in a separate pane.
Inputs
Formula (new | old): First value or variable (e.g., 100, close, close ). Example: close uses the current closing price.
Operator: Mathematical operation (e.g., Plus, Minus, Multiply). Example: Plus adds the two inputs.
Second Input: Second value or variable (e.g., 50, open, close ). Example: open uses the current opening price.
Risk Distribution HistogramStatistical risk visualization and analysis tool for any ticker 📊
The Risk Distribution Histogram visualizes the statistical distribution of different risk metrics for any financial instrument. It converts risk data into histograms with quartile-based color coding, so that traders can understand their risk, tail-risks, exposure patterns and make data-driven decisions based on empirical evidence rather than assumptions.
The indicator supports multiple risk calculation methods, each designed for different aspects of market analysis, from general volatility assessment to tail risk analysis.
Risk Measurement Methods
Standard Deviation
Captures raw daily price volatility by measuring the dispersion of price movements. Ideal for understanding overall market conditions and timing volatility-based strategies.
Use case: Options trading and volatility analysis.
Average True Range (ATR)
Measures true range as a percentage of price, accounting for gaps and limit moves. Valuable for position sizing across different price levels.
Use case: Position sizing and stop-loss placement.
The chart above illustrates how ATR statistical distribution can be used by looking at the ATR % of price distribution. For example, 90% of the movements are below 5%.
Downside Deviation
Only considers negative price movements, making it ideal for checking downside risk and capital protection rather than capturing upside volatility.
Use case: Downside protection strategies and stop losses.
Drawdown Analysis
Tracks peak-to-trough declines, providing insight into maximum loss potential during different market conditions.
Use case: Risk management and capital preservation.
The chart above illustrates tale risk for the asset (TQQQ), showing that it is possible to have drawdowns higher than 20%.
Entropy-Based Risk (EVaR)
Uses information theory to quantify market uncertainty. Higher entropy values indicate more unpredictable price action, valuable for detecting regime changes.
Use case: Advanced risk modeling and tail-risk.
VIX Histogram
Incorporates the market's fear index directly into analysis, showing how current volatility expectations compare to historical patterns. The CAPITALCOM:VIX histogram is independent from the ticker on the chart.
Use case: Volatility trading and market timing.
Visual Features
The histogram uses quartile-based color coding that immediately shows where current risk levels stand relative to historical patterns:
Green (Q1): Low Risk (0-25th percentile)
Yellow (Q2): Medium-Low Risk (25-50th percentile)
Orange (Q3): Medium-High Risk (50-75th percentile)
Red (Q4): High Risk (75-100th percentile)
The data table provides detailed statistics, including:
Count Distribution: Historical observations in each bin
PMF: Percentage probability for each risk level
CDF: Cumulative probability up to each level
Current Risk Marker: Shows your current position in the distribution
Trading Applications
When current risk falls into upper quartiles (Q3 or Q4), it signals conditions are riskier than 50-75% of historical observations. This guides position sizing and portfolio adjustments.
Key applications:
Position sizing based on empirical risk distributions
Monitoring risk regime changes over time
Comparing risk patterns across timeframes
Risk distribution analysis improves trade timing by identifying when market conditions favor specific strategies.
Enter positions during low-risk periods (Q1)
Reduce exposure in high-risk periods (Q4)
Use percentile rankings for dynamic stop-loss placement
Time volatility strategies using distribution patterns
Detect regime shifts through distribution changes
Compare current conditions to historical benchmarks
Identify outlier events in tail regions
Validate quantitative models with empirical data
Configuration Options
Data Collection
Lookback Period: Control amount of historical data analyzed
Date Range Filtering: Focus on specific market periods
Sample Size Validation: Automatic reliability warnings
Histogram Customization
Bin Count: 10-50 bins for different detail levels
Auto/Manual Bin Width: Optimize for your data range
Visual Preferences: Custom colors and font sizes
Implementation Guide
Start with Standard Deviation on daily charts for the most intuitive introduction to distribution-based risk analysis.
Method Selection: Begin with Standard Deviation
Setup: Use daily charts with 20-30 bins
Interpretation: Focus on quartile transitions as signals
Monitoring: Track distribution changes for regime detection
The tool provides comprehensive statistics including mean, standard deviation, quartiles, and current position metrics like Z-score and percentile ranking.
Enjoy, and please let me know your feedback! 😊🥂
Fundig Rate OI# 🚀 Bitcoin Funding Rate + Open Interest Indicator - PineScript v6
## 📋 Summary
I've developed a **Bitcoin-specific** indicator that combines **Funding Rate** with **normalized Open Interest** for advanced futures analysis. After months of testing exclusively on BTC, the results have been excellent for identifying reversal points and confirming trends.
---
## 🎯 Why Bitcoin Only?
**Technical reasons:**
- BTC has the highest volume and liquidity in futures
- More consistent and reliable data
- Less manipulation than altcoins
- More stable correlation between FR and OI
**Problem it solves:**
- Traditional indicators only show one metric
- Difficult to correlate FR with BTC market volume/interest
- Lack of normalization makes OI hard to interpret
- Need for a tool specific to the king of cryptos
**Solution:**
✅ **Dynamic Funding Rate** optimized for BTC
✅ **Normalized Open Interest** (3 different methods)
✅ **Binance BTCUSDTPERP data** exclusively
✅ **Alert system** calibrated for BTC volatility
✅ **Real-time info table**
---
## 🔧 Technical Features
### Main Configurations:
- **Fixed symbol:** BTCUSDTPERP (Binance)
- **Lower timeframe:** 1m, 5m, 15m for precise calculations
- **OI normalization methods:**
- Min-Max (0-1 range)
- RSI (momentum-based)
- Z-Score (statistical distribution)
- **Optimized lookback:** 100 bars (ideal for BTC)
- **Alert system:** Thresholds calibrated for BTC
### Data Sources:
🔸 **Premium Index:** BINANCE:BTCUSDT_PREMIUM
🔸 **Open Interest:** BINANCE:BTCUSDTPERP_OI
🔸 **Timeframes:** From 1m to Daily
🔸 **Precision:** 4 decimals for FR
---
## 📊 How to Interpret Bitcoin Signals
### Funding Rate (Histogram):
- **FR > 0.1%:** BTC longs paying high → Possible short
- **FR < -0.1%:** BTC shorts paying high → Possible long
- **FR extreme (>0.5%):** High probability of BTC reversal
- **FR neutral (±0.05%):** Balanced market
### Open Interest (Blue line):
- **OI > 0.8 + high FR:** Many BTC longs trapped → Bearish
- **OI < 0.2 + low FR:** Short capitulation → Bullish
- **OI divergence:** BTC trend weakening
### Bitcoin-Specific Combinations:
1. **FR > 0.3% + OI > 0.85:** Imminent bearish reversal
2. **FR < -0.2% + OI < 0.15:** Probable bullish reversal
3. **FR oscillating + OI growing:** Accumulation before move
---
## 💡 Real Bitcoin Use Cases
**Example 1 - Bullish Reversal (March 2024):**
```
Situation: BTC falling from 73k to 60k
FR: -0.18% (shorts paying high premium)
OI: 0.12 (very low, short capitulation)
Result: Bounce to 67k (+11%)
```
**Example 2 - Local Top (February 2024):**
```
Situation: BTC at ATH 73.8k
FR: +0.42% (desperate longs paying)
OI: 0.91 (extremely high)
Result: Correction to 60k (-18%)
```
**Example 3 - Bullish Continuation:**
```
Situation: BTC consolidating at 45k
FR: +0.05% (neutral)
OI: 0.65 (steadily growing)
Result: Breakout to 52k (+15%)
```
---
## 🚨 Bitcoin-Calibrated Alert System
The indicator includes Bitcoin-specific alerts:
1. **BTC FR Spike Up:** FR > 0.15% (adjusted to BTC volatility)
2. **BTC FR Spike Down:** FR < -0.15%
3. **BTC OI Extreme High:** Normalized OI > 0.88
4. **BTC OI Extreme Low:** Normalized OI < 0.12
**Recommended BTC configuration:**
- **Scalping:** 5m and 15m
- **Swing Trading:** 1h and 4h
- **Position Trading:** Daily
- Always combine with BTC support/resistance
---
## 📈 Bitcoin Backtesting Results
**Testing period:** 12 months (July 2023 - July 2024)
**Exclusive pair:** BTCUSDTPERP
**Timeframes:** 15m, 1h, 4h, 1D
**BTC-specific results:**
- **Reversal accuracy:** ~78% (better than altcoins)
- **False signals:** Reduced 45% vs FR alone
- **Best timeframe:** 1h for swing, 15m for scalping
- **Worst period:** Sideways market (Nov-Dec 2023)
- **Best period:** Strong trends (Oct 2023, Mar 2024)
**Key statistics:**
- **23 major reversal signals:** 18 successful
- **Average gain:** +8.3% per successful trade
- **Average loss:** -2.1% per failed trade
- **Risk/reward ratio:** 1:3.9
OI BTC Profile# 🚀 Bitcoin Open Interest Profile
## 📊 **What is this indicator?**
The **Bitcoin Open Interest Profile** is an advanced indicator developed in Pine Script v6 that visualizes the distribution of Bitcoin's Open Interest (OI) across different price levels, similar to a Volume Profile but using Open Interest data.
## 🎯 **Key Features**
### **Open Interest Analysis**
- **Dual Mode**: Visualizes both absolute OI value and net changes
- **Data Source**: Uses Open Interest data from BINANCE:BTCUSDT.P-OI
- **Configurable Lookback**: Up to 1000 historical bars for analysis
### **Professional Visualization**
- **Horizontal Profile**: Horizontal bars showing OI concentration by price level
- **Point of Control (POC)**: Automatically identifies the level with highest OI concentration
- **Rolling POC**: Option to display dynamic POC in real-time
### **Advanced Customization**
- **3 Color Schemes**:
- **OI Gradient**: Colors by Open Interest intensity
- **Bull/Bear**: Green for increases, red for decreases
- **Custom**: Customizable color
- **Adjustable Histogram**: Width, position, and orientation configurable
- **Up to 500 levels**: Ultra-high resolution for detailed analysis
## 🔧 **Configurable Parameters**
### **Basic Settings**
- `Lookback`: Number of bars to analyze (1-1000)
- `Row Size`: Profile resolution (1-500 levels)
- `Rolling POC`: Show dynamic POC
- `OI Calculation`: Absolute value or net change
### **Style Settings**
- `Width`: Histogram width (% of range)
- `Bar Width`: Bar thickness
- `Flip Histogram`: Invert orientation
- `Color Schemes`: Multiple coloring options
## 📈 **Trading Applications**
### **Support and Resistance Analysis**
- Identifies levels with highest concentration of open positions
- POC acts as a magnetic price attractor
### **Liquidity Zone Detection**
- High OI levels may indicate potential liquidation zones
- Useful for identifying stop-loss clusters
### **Sentiment Analysis**
- OI changes reveal accumulation or distribution patterns
- Difference between absolute value and net changes provides context
### **Entry Timing**
- Rolling POC can act as dynamic support/resistance
- Confluence with traditional technical analysis
## 💡 **Competitive Advantages**
### **Optimized Performance**
- Maximum 500 simultaneous lines for smooth operation
- Efficient calculations with native arrays
- Compatible with multiple timeframes
### **Total Flexibility**
- Adaptable to different trading strategies
- Granular configuration for each trader
- Overlay that doesn't interfere with price analysis
### **Institutional Data**
- Access to market-moving metrics
- Information not available in traditional indicators
- Informational advantage over retail traders
## 🚨 **Recommended Use Cases**
### **Scalping and Day Trading**
- Use high resolution (300-500 rows) with short lookback (50-100 bars)
- Rolling POC as intraday reference
### **Swing Trading**
- Medium resolution (100-200 rows) with extended lookback (200-500 bars)
- Focus on high OI levels for targets
### **Positional Analysis**
- Maximum lookback (500-1000 bars) for historical context
- Identification of accumulation/distribution zones
## 🎨 **Visual Examples**
The indicator generates a horizontal profile showing:
- **Longer bars**: Higher Open Interest concentration
- **POC (dotted line)**: Level of maximum interest
- **Color gradient**: OI intensity or bull/bear sentiment
## 🔥 **Why is it unique?**
1. **First of its kind**: Combines volume analysis with derivatives metrics
2. **Institutional precision**: Real-time Open Interest data
3. **Extreme versatility**: Adaptable to any trading style
4. **Optimized performance**: Efficient code for professional use
## 📞 **Feedback and Improvements**
Would you like to see any additional functionality? Any specific parameters for your strategy?
---
*Developed by an experienced trader for experienced traders. Compatible with Pine Script v6 and optimized for Bitcoin, but adaptable to other instruments with available OI data.*
Noon Curve Box with Quadrants & 1st FVGOverview 📜
The Noon Curve Box with Quadrants & 1st FVG is a comprehensive analysis tool built for intraday traders. It automates the process of identifying and visualizing key time-based concepts popularized by ICT (Inner Circle Trader) and other price action methodologies.
While the concepts themselves are public, this script's value lies in its unique automation and clear presentation. It saves you the manual effort of marking session ranges, quadrants, and searching for critical imbalances every single day, allowing you to focus purely on execution.
Underlying Concepts Explained 🧠
This script is built on a few core price action principles:
Time-Based Profiling: The idea that different times of the trading day have different characteristics. The script visually separates the main session into 2-hour quadrants to help you track momentum shifts.
Fair Value Gaps (FVG): An FVG is a three-bar pattern that indicates a price imbalance or inefficiency. It's a foundational concept in many institutional trading methods.
A Bullish FVG (or BISI) forms when there is a gap between the first candle's high and the third candle's low:
Candle 1 HighCandle 3 High
"Silver Bullet" Time Windows: This indicator specifically targets the first FVG formed during the high-impact AM session (9:30-10:00 NY Time) and a corresponding PM session (13:30-14:00 NY Time), as these are often considered high-probability reversal or continuation zones.
Key Features & How It Works ✨
Automated Session Box: The script automatically draws a box around the high and low of your specified trading session (default is 8:00 AM - 4:00 PM New York time). This provides an instant view of the day's operating range.
Dynamic Quadrant Analysis: The session is automatically divided into 2-hour quadrants. Each box is colored based on its internal momentum (close vs. open), providing an at-a-glance summary of buying or selling pressure throughout the day.
Precision FVG Detection:
The script's core logic scans for the very first FVG within the AM (9:30-10:00) and PM (13:30-14:00) windows.
It identifies the exact 3-bar pattern and immediately draws a box marking the imbalance zone. Once the first FVG is found for a window, the script stops searching, ensuring your chart remains clean and focused on the most significant, initial imbalance.
The FVG boxes extend to the current bar, keeping these key levels of interest visible all day.
How to Use This Indicator 🎯
Context: Use the Session Box high and low as your primary intraday support and resistance levels.
Momentum: Use the Quadrant Box colors to gauge the flow of the market. A switch from red to green, for example, can signal a potential shift in control.
High-Probability Setups: The AM and PM First FVG boxes are your key points of interest. These imbalances often act as price magnets. Look for price to return to these zones to find potential entries, as they may act as support (bullish FVG) or resistance (bearish FVG).
Settings and Customization ⚙️
You have full control over all visual elements.
Session Control: Adjust the session time and timezone.
Visual Toggles: Enable or disable the Session Box, Quadrants, and AM/PM FVGs.
Color Customization: Match all elements to your personal chart theme.
History: Limit the number of historical FVG boxes displayed to keep your chart clean.
Range & Consolidation DetectorHello friends,
I’m excited to share my latest discovery with you — the Range & Consolidation Detector. This script is built on a unique methodology I’m truly proud of. It uses no traditional indicators like ADX, RSI, or ATR — just pure statistics and mathematics under the hood. No parameters to tweak, no settings to guess — it just works, right out of the box.
🛠️ How It Works
At its core is a proprietary formula that reliably identifies ranging conditions across all tickers and timeframes. It’s simple, robust, and consistent — exactly what traders need to spot sideways markets without noise or lag.
🔥 Key Features
Pine Script v6 – Uses the latest version for maximum performance
Zero configuration – No inputs to adjust, no hidden settings — the algorithm works automatically
Optimized performance – Runs efficiently for smooth charting
Universal compatibility – Works flawlessly on any asset and timeframe, in every market condition — from euphoric peaks to choppy ranges
📸 Visual Examples
If you’d like access or have any questions, feel free to reach out to me directly via DM.
👋 Good luck and happy trading!
Alpha - Combined BreakoutThis Pine Script indicator, "Alpha - Combined Breakout," is a combination between Smart Money Breakout Signals and UT Bot Alert, The UT Bot Alert indicator was initially developer by Yo_adriiiiaan
The idea of original code belongs HPotter.
This Indicator helps you identify potential trading opportunities by combining two distinct strategies: Smart Money Breakout and a modified UT Bot (likely a variation of the Ultimate Trend Bot). It provides visual signals, draws lines for potential take profit (TP) and stop loss (SL) levels, and includes a dashboard to track performance metrics.
Tutorial:
Understanding and Using the "Alpha - Combined Breakout" Indicator
This indicator is designed for traders looking for confirmation of market direction and potential entry/exit points by blending structural analysis with a trend-following oscillator.
How it Works (General Concept)
The indicator combines two main components:
Smart Money Breakout: This part identifies significant breaks in market structure, which "smart money" traders often use to gauge shifts in supply and demand. It looks for higher highs/lows or lower highs/lows and flags when these structural points are broken.
UT Bot: This is a trend-following component that generates buy and sell signals based on price action relative to an Average True Range (ATR) based trailing stop.
You can choose to use these signals independently or combined to generate trading alerts and visual cues on your chart. The dashboard provides a quick overview of how well the signals are performing based on your chosen settings and display mode.
Parameters and What They Do
Let's break down each input parameter:
1. Smart Money Inputs
These settings control how the indicator identifies market structure and breakouts.
swingSize (Market Structure Time-Horizon):
What it does: This integer value defines the number of candles used to identify significant "swing" (pivot) points—highs and lows.
Effect: A larger swingSize creates a smoother market structure, focusing on longer-term trends. This means signals might appear less frequently and with some delay but could be more reliable for higher timeframes or broader market movements. A smaller swingSize will pick up more minor market structure changes, leading to more frequent but potentially noisier signals, suitable for lower timeframes or scalping.
Analogy: Think of it like a zoom level on your market structure map. Higher values zoom out, showing only major mountain ranges. Lower values zoom in, showing every hill and bump.
bosConfType (BOS Confirmation Type):
What it does: This string input determines how a Break of Structure (BOS) is confirmed. You have two options:
'Candle Close': A breakout is confirmed only if a candle's closing price surpasses the previous swing high (for bullish) or swing low (for bearish).
'Wicks': A breakout is confirmed if any part of the candle (including its wick) surpasses the previous swing high or low.
Effect: 'Candle Close' provides stronger, more conservative confirmation, as it implies sustained price movement beyond the structure. 'Wicks' provides earlier, more aggressive signals, as it captures momentary breaches of the structure.
Analogy: Imagine a wall. 'Candle Close' means the whole person must get over the wall. 'Wicks' means even a finger touching over the top counts as a breach.
choch (Show CHoCH):
What it does: A boolean (true/false) input to enable or disable the display of "Change of Character" (CHoCH) labels. CHoCH indicates the first structural break against the current dominant trend.
Effect: When true, it helps identify early signs of a potential trend reversal, as it marks where the market's "character" (its tendency to make higher highs/lows or lower lows/highs) first changes.
BULL (Bullish Color) & BEAR (Bearish Color):
What they do: These color inputs allow you to customize the visual appearance of bullish and bearish signals and lines drawn by the Smart Money component.
Effect: Purely cosmetic, helps with visual identification on the chart.
sm_tp_sl_multiplier (SM TP/SL Multiplier (ATR)):
What it does: A float value that acts as a multiplier for the Average True Range (ATR) to calculate the Take Profit (TP) and Stop Loss (SL) levels specifically when you're in "Smart Money Only" mode. It uses the ATR calculated by the UT Bot's nLoss_ut as its base.
Effect: A higher multiplier creates wider TP/SL levels, potentially leading to fewer trades but larger wins/losses. A lower multiplier creates tighter TP/SL levels, potentially leading to more frequent but smaller wins/losses.
2. UT Bot Alerts Inputs
These parameters control the behavior and sensitivity of the UT Bot component.
a_ut (UT Key Value (Sensitivity)):
What it does: This integer value adjusts the sensitivity of the UT Bot.
Effect: A higher value makes the UT Bot less sensitive to price fluctuations, resulting in fewer and potentially more reliable signals. A lower value makes it more sensitive, generating more signals, which can include more false signals.
Analogy: Like a noise filter. Higher values filter out more noise, keeping only strong signals.
c_ut (UT ATR Period):
What it does: This integer sets the look-back period for the Average True Range (ATR) calculation used by the UT Bot. ATR measures market volatility.
Effect: This period directly influences the calculation of the nLoss_ut (which is a_ut * xATR_ut), thus defining the distance of the trailing stop loss and take profit levels. A longer period makes the ATR smoother and less reactive to sudden price spikes. A shorter period makes it more responsive.
h_ut (UT Signals from Heikin Ashi Candles):
What it does: A boolean (true/false) input to determine if the UT Bot calculations should use standard candlestick data or Heikin Ashi candlestick data.
Effect: Heikin Ashi candles smooth out price action, often making trends clearer and reducing noise. Using them for UT Bot signals can lead to smoother, potentially delayed signals that stay with a trend longer. Standard candles are more reactive to raw price changes.
3. Line Drawing Control Buttons
These crucial boolean inputs determine which type of signals will trigger the drawing of TP/SL/Entry lines and flags on your chart. They act as a priority system.
drawLinesUtOnly (Draw Lines: UT Only):
What it does: If checked (true), lines and flags will only be drawn when the UT Bot generates a buy/sell signal.
Effect: Isolates UT Bot signals for visual analysis.
drawLinesSmartMoneyOnly (Draw Lines: Smart Money Only):
What it does: If checked (true), lines and flags will only be drawn when the Smart Money Breakout logic generates a bullish/bearish breakout.
Effect: Overrides drawLinesUtOnly if both are checked. Isolates Smart Money signals.
drawLinesCombined (Draw Lines: UT & Smart Money (Combined)):
What it does: If checked (true), lines and flags will only be drawn when both a UT Bot signal AND a Smart Money Breakout signal occur on the same bar.
Effect: Overrides both drawLinesUtOnly and drawLinesSmartMoneyOnly if checked. Provides the strictest entry criteria for line drawing, looking for strong confluence.
Dashboard Metrics Explained
The dashboard provides performance statistics based on the lines drawing control button selected. For example, if "Draw Lines: UT Only" is active, the dashboard will show stats only for UT Bot signals.
Total Signals: The total number of buy or sell signals generated by the selected drawing mode.
TP1 Win Rate: The percentage of signals where the price reached Take Profit 1 (TP1) before hitting the Stop Loss.
TP2 Win Rate: The percentage of signals where the price reached Take Profit 2 (TP2) before hitting the Stop Loss.
TP3 Win Rate: The percentage of signals where the price reached Take Profit 3 (TP3) before hitting the Stop Loss. (Note: TP1, TP2, TP3 are in order of distance from entry, with TP3 being furthest.)
SL before any TP rate: This crucial metric shows the number of times the Stop Loss was hit / the percentage of total signals where the stop loss was triggered before any of the three Take Profit levels were reached. This gives you a clear picture of how often a trade resulted in a loss without ever moving into profit target territory.
Short Tutorial: How to Use the Indicator
Add to Chart: Open your TradingView chart, go to "Indicators," search for "Alpha - Combined Breakout," and add it to your chart.
Access Settings: Once added, click the gear icon next to the indicator name on your chart to open its settings.
Choose Your Signal Mode:
For UT Bot only: Uncheck "Draw Lines: Smart Money Only" and "Draw Lines: UT & Smart Money (Combined)". Ensure "Draw Lines: UT Only" is checked.
For Smart Money only: Uncheck "Draw Lines: UT Only" and "Draw Lines: UT & Smart Money (Combined)". Ensure "Draw Lines: Smart Money Only" is checked.
For Combined Signals: Check "Draw Lines: UT & Smart Money (Combined)". This will override the other two.
Adjust Parameters:
Start with default settings. Observe how the signals appear on your chosen asset and timeframe.
Refine Smart Money: If you see too many "noisy" market structure breaks, increase swingSize. If you want earlier breakouts, try "Wicks" for bosConfType.
Refine UT Bot: Adjust a_ut (Sensitivity) to get more or fewer UT Bot signals. Change c_ut (ATR Period) if you want larger or smaller TP/SL distances. Experiment with h_ut to see if Heikin Ashi smoothing suits your trading style.
Adjust TP/SL Multiplier: If using "Smart Money Only" mode, fine-tune sm_tp_sl_multiplier to set appropriate risk/reward levels.
Interpret Signals & Lines:
Buy/Sell Flags: These indicate the presence of a signal based on your selected drawing mode.
Entry Line (Blue Solid): This is where the signal was generated (usually the close price of the signal candle).
SL Line (Red/Green Solid): Your calculated stop loss level.
TP Lines (Dashed): Your three calculated take profit levels (TP1, TP2, TP3, where TP3 is the furthest target).
Smart Money Lines (BOS/CHoCH): These lines indicate horizontal levels where market structure breaks occurred. CHoCH labels might appear at the first structural break against the prior trend.
Monitor Dashboard: Pay attention to the dashboard in the top right corner. This dynamically updates to show the win rates for each TP and, crucially, the "SL before any TP rate." Use these statistics to evaluate the effectiveness of the indicator's signals under your current settings and chosen mode.
*
Set Alerts (Optional): You can set up alerts for any of the specific signals (UT Bot Long/Short, Smart Money Bullish/Bearish, or the "Line Draw" combined signals) to notify you when they occur, even if you're not actively watching the chart.
By following this tutorial, you'll be able to effectively use and customize the "Alpha - Combined Breakout" indicator to suit your trading strategy.
Floor and Roof Indicator with SignalsFloor and Roof Indicator with Trading Signals
A comprehensive support and resistance indicator that identifies premium and discount zones with automated signal generation.
Key Features:
Dynamic Support/Resistance Zones: Calculates floor (support) and roof (resistance) levels using price action and volatility
Premium/Discount Zone Identification: Highlights areas where price may find resistance or support
Customizable Signal Frequency: Control how often signals are displayed (every Nth occurrence)
Visual Signal Table: Optional table showing the last 5 long and short signal prices
Multiple Timeframe Compatibility: Works across all timeframes
Technical Details:
Uses ATR-based calculations for dynamic zone width adjustment
Combines Bollinger Bands with highest/lowest price analysis
Smoothing options for cleaner signal generation
Fully customizable colors and display options
How to Use:
Floor Zones (Blue): Potential support areas where long positions may be considered
Roof Zones (Pink): Potential resistance areas where short positions may be considered
Signal Crosses: Visual markers when price interacts with key levels
Signal Table: Track recent signal prices for analysis
Settings:
Length: Period for calculations (default: 200)
Smooth: Smoothing factor for cleaner signals
Zone Width: Adjust the thickness of support/resistance zones
Signal Frequency: Control signal display frequency
Visual Options: Customize colors and table position
Alerts Available:
Long signal alerts when price touches discount zones
Short signal alerts when price reaches premium zones
Educational Purpose: This indicator is designed to help traders identify potential support and resistance areas. Always combine with proper risk management and additional analysis.
This description focuses on the technical aspects and educational value while avoiding any language that could be interpreted as financial advice or guaranteed profits.
Jumping watermark# Jumping watermark
## Function description
- Dynamic watermark: Mainly used to add dynamic watermarks to prevent theft and transfer when recording videos.
- Static watermark: Sharing opinions can easily include information such as trading pairs, cycles, current time, and individual signatures.
### Static watermark:
Display the watermark related to the current trading pair in the center of the chart.
- Configuration items:
- You can choose to configure the display content: current trading pair code and name, cycle, date, time, and individual signature content
### Dynamic watermark
Display the configured watermark content in a dynamic random position.
- Configuration items:
- Turn on or off the display of watermark jumping
- Modify the display text content and style by yourself
----- 中文简介-----
# 跳动水印
## 功能描述
- 动态水印： 主要可用于视频录制时添加动态水印防盗、防搬运。
- 静态水印：观点分享是可方便的带上交易对、周期、当前时间、个签等信息。
### 静态水印：
在图表中心位置显示当前交易对相关信息水印。
- 配置项：
- 可选择配置显示内容：当前交易对代码及名称、周期、日期、时间、个签内容
### 动态水印
动态随机位置显示配置水印内容。
- 配置项：
- 开启或关闭显示水印跳动
- 自行修改配置显示文字内容和样式
Kelly Optimal Leverage IndicatorThe Kelly Optimal Leverage Indicator mathematically applies Kelly Criterion to determine optimal position sizing based on market conditions.
This indicator helps traders answer the critical question: "How much capital should I allocate to this trade?"
Note that "optimal position sizing" does not equal the position sizing that you should have. The Optima position sizing given by the indicator is based on historical data and cannot predict a crash, in which case, high leverage could be devastating.
Originally developed for gambling scenarios with known probabilities, the Kelly formula has been adapted here for financial markets to dynamically calculate the optimal leverage ratio that maximizes long-term capital growth while managing risk.
Key Features
Kelly Position Sizing: Uses historical returns and volatility to calculate mathematically optimal position sizes
Multiple Risk Profiles: Displays Full Kelly (aggressive), 3/4 Kelly (moderate), 1/2 Kelly (conservative), and 1/4 Kelly (very conservative) leverage levels
Volatility Adjustment: Automatically recommends appropriate Kelly fraction based on current market volatility
Return Smoothing: Option to use log returns and smoothed calculations for more stable signals
Comprehensive Table: Displays key metrics including annualized return, volatility, and recommended exposure levels
How to Use
Interpret the Lines: Each colored line represents a different Kelly fraction (risk tolerance level). When above zero, positive exposure is suggested; when below zero, reduce exposure. Note that this is based on historical returns. I personally like to increase my exposure during market downturns, but this is hard to illustrate in the indicator.
Monitor the Table: The information panel provides precise leverage recommendations and exposure guidance based on current market conditions.
Follow Recommended Position: Use the "Recommended Position" guidance in the table to determine appropriate exposure level.
Select Your Risk Profile: Conservative traders should follow the Half Kelly or Quarter Kelly lines, while more aggressive traders might consider the Three-Quarter or Full Kelly lines.
Adjust with Volatility: During high volatility periods, consider using more conservative Kelly fractions as recommended by the indicator.
Mathematical Foundation
The indicator calculates the optimal leverage (f*) using the formula:
f* = μ/σ²
Where:
μ is the annualized expected return
σ² is the annualized variance of returns
This approach balances potential gains against risk of ruin, offering a scientific framework for position sizing that maximizes long-term growth rate.
Notes
The Full Kelly is theoretically optimal for maximizing long-term growth but can experience significant drawdowns. You should almost never use full kelly.
Most practitioners use fractional Kelly strategies (1/2 or 1/4 Kelly) to reduce volatility while capturing most of the growth benefits
This indicator works best on daily timeframes but can be applied to any timeframe
Negative Kelly values suggest reducing or eliminating market exposure
The indicator should be used as part of a complete trading system, not in isolation
Enjoy the indicator! :)
P.S. If you are really geeky about the Kelly Criterion, I recommend the book The Kelly Capital Growth Investment Criterion by Edward O. Thorp and others.
Crypto Risk-Weighted Allocation SuiteCrypto Risk-Weighted Allocation Suite
This indicator is designed to help users explore dynamic portfolio allocation frameworks for the crypto market. It calculates risk-adjusted allocation weights across major crypto sectors and cash based on multi-factor momentum and volatility signals. Best viewed on INDEX:BTCUSD 1D chart. Other charts and timeframes may give mixed signals and incoherent allocations.
🎯 How It Works
This model systematically evaluates the relative strength of:
BTC Dominance (CRYPTOCAP:BTC.D)
Represents Bitcoin’s share of the total crypto market. Rising dominance typically indicates defensive market phases or BTC-led trends.
ETH/BTC Ratio (BINANCE:ETHBTC)
Gauges Ethereum’s relative performance versus Bitcoin. This provides insight into whether ETH is leading risk appetite.
SOL/BTC Ratio (BINANCE:SOLBTC)
Measures Solana’s performance relative to Bitcoin, capturing mid-cap layer-1 strength.
Total Market Cap excluding BTC and ETH (CRYPTOCAP:TOTAL3ES)
Represents Altcoins as a broad category, reflecting appetite for higher-risk assets.
Each of these series is:
✅ Converted to a momentum slope over a configurable lookback period.
✅ Standardized into Z-scores to normalize changes relative to recent behavior.
✅ Smoothed optionally using a Hull Moving Average for cleaner signals.
✅ Divided by ATR-based volatility to create a risk-weighted score.
✅ Scaled to proportionally allocate exposure, applying user-configured minimum and maximum constraints.
🪙 Dynamic Allocation Logic
All signals are normalized to sum to 100% if fully confident.
An overall confidence factor (based on total signal strength) scales the allocation up or down.
Any residual is allocated to cash (unallocated capital) for conservative exposure.
The script automatically avoids “all-in” bias and prevents negative allocations.
📊 Outputs
The indicator displays:
Market Phase Detection (which asset class is currently leading)
Risk Mode (Risk On, Neutral, Risk Off)
Dynamic Allocations for BTC, ETH, SOL, Alts, and Cash
Optional momentum plots for transparency
🧠 Why This Is Unique
Unlike simple dominance indicators or crossovers, this model:
Integrates multiple cross-asset signals (BTC, ETH, SOL, Alts)
Adjusts exposure proportionally to signal strength
Normalizes by volatility, dynamically scaling risk
Includes configurable constraints to reflect your own risk tolerance
Provides a cash fallback allocation when conviction is low
Is entirely non-repainting and based on daily closing data
⚠️ Disclaimer
This script is provided for educational and informational purposes only.
It is not financial advice and should not be relied upon to make investment decisions.
Past performance does not guarantee future results.
Always consult a qualified financial advisor before acting on any information derived from this tool.
🛠 Recommended Use
As a framework to visualize relative momentum and risk-adjusted allocations
For research and backtesting ideas on portfolio allocation across crypto sectors
To help build your own risk management process
This script is not a turnkey strategy and should be customized to fit your goals.
✅ Enjoy exploring dynamic crypto allocations responsibly!
