Institutional Momentum & Liquidity Matrix
Institutional Momentum & Liquidity Matrix
■Overview
This tool is a quantitative analysis suite designed to bridge the gap between price momentum and market liquidity structure. Moving away from the traditional approach of monitoring "where the RSI is currently," it calculates the exact price required for the RSI to reach overbought/oversold levels on the next candle and visualizes it directly on the chart. This projection is overlaid with an RSI-Anomaly Volume Profile to highlight true structural exhaustion.
■1. Originality and Design Philosophy
While RSI and Volume Profile are widely used, they are typically viewed in isolation, leading to false signals. This script is original because it mathematically merges them:
1. It projects the theoretical elastic limits of momentum directly onto the price scale using algebraic reversal of Wilder's Smoothing.
// Algebraic Reversal of Wilder's Smoothing (RMA)
f_get_reverse_price(target_rsi) =>
float target_rs = target_rsi / (100.0 - target_rsi)
float req_up = (target_rs * prev_rma_d * (rsi_len - 1)) - (prev_rma_u * (rsi_len - 1))
float req_down = (prev_rma_u * (rsi_len - 1) / target_rs) - (prev_rma_d * (rsi_len - 1))
float rev_price = req_up > 0 ? prev_c + req_up : (req_down > 0 ? prev_c - req_down : prev_c)
rev_price
2. It filters a Lower Timeframe (LTF) Volume Profile using LTF RSI data, discarding neutral volume and coloring only the specific price nodes where momentum reached extreme anomalies.
// RSI Anomaly Matrix & Peak Retention Logic
bool is_significant = (intensity * 100.0) >= vol_threshold
color base_c = color_prof_neutral
if is_significant
if rsi_color_mode == "Peak Retention"
if max_rsi >= rsi_ob and min_rsi <= rsi_os
base_c := (max_rsi - 50.0) > (50.0 - min_rsi) ? color_ob : color_os
else if max_rsi >= rsi_ob
base_c := color_ob
else if min_rsi <= rsi_os
base_c := color_os
■2. Core Mechanism 1: Reverse RSI Projection (The Math)
Instead of tracking an oscillator bounded between 0 and 100, this script mathematically reverses J. Welles Wilder Jr.'s Smoothed Moving Average (RMA) formula.
To calculate the exact closing price required on the next bar to achieve a specific Target RSI (e.g., 70 or 30), the script uses the following logic:
RS = Target_RSI / (100 - Target_RSI)
Required_Up =
(RS * Prev_RMA_D * (Length - 1)) - (Prev_RMA_U * (Length - 1))
Required_Down =
(Prev_RMA_U * (Length - 1) / RS) - (Prev_RMA_D * (Length - 1))
It plots these calculated prices as horizontal projection lines, allowing traders to evaluate momentum limits directly on the price action.
■3. Core Mechanism 2: RSI Anomaly Liquidity Matrix
Momentum limits require structural backing to be reliable. This engine aggregates LTF data to generate a filtered Volume Profile.
・Dynamic Sessions: Generates profiles based on Daily, Weekly, Monthly, or Custom Market Sessions (Defaults are set to UTC for Oceania, Asia, London, and NY).
・RSI Anomaly Coloring: Instead of plotting standard volume, the script calculates the average LTF RSI for each price node. It only applies color to nodes where the average momentum reached extreme Overbought or Oversold levels, keeping the rest of the profile neutral. This eliminates visual noise and isolates true areas of structural exhaustion.
・Point of Control (POC): Automatically extracts and highlights the price level with the highest liquidity concentration.
■4. Configuration & Parameters
・Profile Generation Mode: Determines time boundaries. Day traders can use Custom Sessions (UTC), while swing traders benefit from Daily/Weekly structures.
・Liquidity Data Source: While 'Volume' is the standard input, 'Price Delta' is provided as a proxy to ensure the profile functions on assets lacking raw volume data (e.g., certain Forex feeds).
・Max LTF Samples per Bar: Limits how many LTF candles are processed per higher timeframe candle to optimize performance and prevent calculation limits.
・RSI Coloring Mode: Controls sensitivity. "Volume-Weighted Average" is mathematically strict but colors may neutralize over time. "Peak Retention" ensures that if a price node hits an RSI extreme at any point during the session, it permanently retains that warning color, preventing dilution.
・Significance Threshold & Hide Weak Nodes: Filters out price nodes that lack sufficient volume (e.g., under 30% of the POC volume). Graying out or hiding low-volume nodes removes noise.
・POC Proximity Filter: Fades the RSI projection lines if no historical POC is nearby, utilizing ATR to define a dynamic "safe zone." Momentum extremes without structural support are prone to false breakouts.
■5. Usage & Mindset
・Best Suited For: High-liquidity instruments (Major Forex, Indices, Large-cap Crypto) on 15M to 1H charts.
・Execution: Do not enter blindly when price hits the RSI projection line. Wait for confluence: "Is this momentum extreme backed by a colored, structural POC wall?" Use the confluence zone to define strict Stop Loss levels.
■Disclaimer
This script is a quantitative analysis tool designed for educational purposes to visualize mathematical momentum and liquidity data. It does not guarantee future profits and is not intended as a signal service. Always employ strict risk management and conduct comprehensive market analysis.
Institutional Momentum & Liquidity Matrix
概要
本ツールは、価格モメンタムと市場流動性の構造的差異を統合的に分析するための定量分析スイートです。「RSIの現在値」に依存するアプローチから脱却し、「特定のRSI水準に到達するために必要な要請価格」を逆算してチャート上に直接可視化します。さらに、RSI異常値を反映した流動性マトリックスを展開し、構造的な枯渇点を浮き彫りにします。
1. 独創性と設計思想
RSIと出来高プロファイルは広く普及していますが、単体での使用はダマシを誘発します。本スクリプトはこれらを数学的に統合した点に独創性があります。
1. Wilderの平滑化移動平均（RMA）を代数的に逆算し、モメンタムの限界値を価格スケール上に直接投影します。
2. 下位足（LTF）の出来高プロファイルをLTFのRSIデータでフィルタリングし、極端な異常値（過熱感）を記録した価格帯のみを色付けして視覚化します。
2. コア・メカニズム1: 逆算RSIプロジェクション（計算根拠）
オシレーターを監視するのではなく、RMAの計算式を逆算します。次期のローソク足で指定のRSI極値（例: 70または30）に到達するための終値を、以下のロジックで算出します。
RS = 目標RSI / (100 - 目標RSI)
必要な上昇幅 =
(RS * 前回のRMA下落幅 * (期間 - 1)) - (前回のRMA上昇幅 * (期間 - 1))
必要な下落幅 =
(前回のRMA上昇幅 * (期間 - 1) / RS) - (前回のRMA下落幅 * (期間 - 1))
算出された価格を水平線として描画し、価格アクション上でモメンタムの限界を評価可能にします。
3. コア・メカニズム2: RSI異常値・流動性マトリックス
LTFデータを集計し、高度なフィルターを備えた価格帯別出来高を生成します。
・動的セッション: 日次、週次、月次、または特定の市場セッションに対応（※セッション時間はすべてUTC基準です）。
・RSI異常値カラーリング: 各価格帯の平均LTF RSIを算出し、買われすぎ/売られすぎの極限領域に達した価格帯のみを色付けします。通常の価格帯をニュートラルカラーに保つことで視覚的ノイズを排除します。
・Point of Control (POC): 最大流動性が集中する価格帯を自動抽出し、強力なレジサポとしてハイライトします。
4. パラメーター設定
・Generation Mode (生成モード): デイトレーダーには特定の市場セッションが、スイングトレーダーには日次・週次の構造が適しています。
・Liquidity Data Source (流動性データ): 「出来高」を基本としますが、出来高データがない銘柄（一部のFX等）でも機能するよう、「価格変動幅（Price Delta）」を選択可能です。
・Max LTF Samples per Bar (最大LTF参照数): 上位足1本に対して参照する下位足の本数を制限し、計算処理を最適化します。
・RSI Coloring Mode (カラーリング感度・保持): プロファイルの色付け基準を選択します。「出来高加重平均 (Volume-Weighted)」は厳格ですが、その後の通常取引によって色が中和される性質があります。「ピーク保持 (Peak Retention)」を選択すると、セッション中に一度でもRSI異常値を記録した価格帯は、その極値カラーを履歴として保持し続けます（高感度モード）。
・Significance Threshold (有意性閾値): POCに対して一定割合に満たない価格帯をグレーアウトまたは非表示にし、真の壁のみを残します。
・POC Proximity Filter (近接フィルター): 過去のPOCが近くにない場合、プロジェクションラインをフェードアウトさせます。構造的な支持を持たない極値はダマシになりやすいため、ATRを利用したリスク管理レイヤーとして機能します。
5. 使い方と環境
・得意な環境: 流動性の高いメジャー通貨ペア、主要株価指数、大型暗号資産の15分足〜1時間足。
・思考プロセス: 価格がRSIプロジェクションに到達したからといって盲目的にエントリーせず、「その極値の背後に、色付けされたPOCの壁が存在するか」を確認してください。コンフルエンス領域を基準に、厳格な損切りを設定してください。
免責事項
本スクリプトは、数学的モメンタムおよび流動性データを可視化し、市場構造の理解を深めるための教育用ツールです。将来の利益を保証するものではなく、シグナル配信ツールではありません。常に適切なリスク管理と独自の市場分析を行ってください。
Indicator
Sharpe Ratio [Alpha Extract]A sophisticated risk-adjusted return measurement system that calculates annualized Sharpe Ratio with dynamic color-coded visualization distinguishing return quality across positive and negative performance regimes. Utilizing rolling period calculations with smoothed moving average comparison, this indicator delivers institutional-grade performance assessment with overbought/oversold threshold detection for extreme risk-adjusted return conditions. The system's four-tier color classification combined with histogram fills and background highlighting provides comprehensive visual feedback on whether current returns justify their volatility risk across varying market cycles.
🔶 Advanced Sharpe Ratio Calculation Engine
Implements classic Sharpe Ratio methodology measuring mean daily return divided by return standard deviation with annualization factor for consistent interpretation. The system calculates daily percentage returns, computes rolling mean and standard deviation over configurable periods, applies square root of 365 scaling for annualized comparison, and generates unbounded ratio values where higher positive readings indicate superior risk-adjusted performance.
// Core Sharpe Ratio Framework
Daily_Return = close / close - 1
Mean_Return = ta.sma(Daily_Return, Period)
StdDev_Return = ta.stdev(Daily_Return, Period)
Sharpe_Ratio = (Mean_Return / StdDev_Return) * sqrt(365)
🔶 Dynamic Four-Tier Color Classification
Features sophisticated color logic distinguishing between strong positive returns (green), weakening positive returns (yellow), weakening negative returns (orange), and strong negative returns (red) based on relationship to smoothed average. The system compares current Sharpe against SMA-smoothed baseline, applying green when positive and accelerating, yellow when positive but decelerating, orange when negative but improving, and red when negative and deteriorating for nuanced regime assessment.
🔶 Smoothed Baseline Comparison Framework
Implements SMA smoothing of Sharpe Ratio with configurable period to establish momentum reference line for trend determination within risk-adjusted returns. The system calculates simple moving average of raw Sharpe values, uses this smoothed line as directional benchmark, and determines whether current risk-adjusted performance is strengthening or weakening relative to recent average for color classification logic.
🔶 Extreme Threshold Detection System
Provides overbought and oversold level identification with configurable upper and lower bounds marking exceptional risk-adjusted return extremes. The system defaults to +4.3 for overbought threshold (extremely favorable risk-return profile) and -2.3 for oversold threshold (severely unfavorable risk-return profile), applying dashed horizontal reference lines and background highlighting when Sharpe breaches these statistical extremes requiring attention.
🔶 Histogram Fill Visualization Architecture
Creates gradient-filled histogram between Sharpe Ratio line and zero baseline using dynamic color matching with 30% transparency for intuitive positive/negative return distinction. The system fills area above zero with bullish colors (green/yellow) and below zero with bearish colors (orange/red), providing immediate visual confirmation of whether returns are compensating for volatility risk or destroying risk-adjusted value.
🔶 Background Zone Highlighting Framework
Implements subtle background coloring when Sharpe enters extreme overbought or oversold zones, alerting traders to statistically significant risk-adjusted return conditions. The system applies semi-transparent red background when ratio exceeds +4.3 (exceptionally strong risk-adjusted returns potentially unsustainable) and green background when below -2.3 (severely poor risk-adjusted returns potentially reversionary), creating visual alerts without obscuring price action.
🔶 Annualization Methodology Integration
Utilizes standard square root of time scaling (sqrt(365)) to convert rolling period Sharpe calculations into annualized format for cross-temporal comparison. The system applies this mathematical transformation ensuring Sharpe values represent expected annual risk-adjusted returns regardless of calculation period length, enabling consistent interpretation whether using 100-day or 200-day rolling windows.
🔶 Zero-Line Reference System
Provides critical zero-line plot serving as boundary between positive risk-adjusted returns (capital allocation justified by return/risk profile) and negative risk-adjusted returns (strategy destroying value on risk-adjusted basis). The system emphasizes this threshold as decision point where values above zero suggest continuation while values below zero indicate reconsideration of exposure.
🔶 Momentum-Based Color
Transitions Implements intelligent color switching logic that considers both absolute Sharpe value and its momentum relative to smoothed average, creating four distinct regimes for granular performance assessment. The system enables identification of bullish acceleration (green), bullish deceleration (yellow), bearish improvement (orange), and bearish acceleration (red) for nuanced position management beyond simple positive/negative classification.
🔶 Configurable Period Optimization
Features adjustable calculation period and smoothing length enabling optimization across different trading timeframes and volatility regimes. The system defaults to 150-period calculation (approximately 6-7 months of daily data) with 30-period smoothing, but allows customization from short-term tactical assessment to long-term strategic evaluation based on investment horizon and strategy requirements.
🔶 Performance Optimization Framework
Employs efficient rolling calculations with streamlined daily return processing and optimized standard deviation computation for smooth real-time updates. The system includes minimal computational overhead through single-pass mean and variance calculations, enabling consistent performance across extended historical periods while maintaining accuracy of risk-adjusted return measurements.
This indicator delivers sophisticated risk-adjusted return analysis through classic Sharpe Ratio methodology with enhanced visual classification distinguishing return quality and momentum. Unlike simple return-focused indicators, Sharpe Ratio penalizes volatility ensuring traders evaluate whether returns justify the risk undertaken. The system's four-tier color coding, smoothed baseline comparison, and extreme threshold detection make it essential for portfolio managers and systematic traders seeking objective performance assessment beyond raw price gains. High positive Sharpe values indicate efficient return generation relative to volatility risk, while negative values signal value destruction on risk-adjusted basis requiring strategy reassessment. The indicator excels at identifying periods when risk-taking is rewarded (green zones) versus periods when volatility exceeds returns (red zones) across cryptocurrency, forex, and equity markets for optimal capital allocation decisions. Indicator
S&P 500 & Normalized CAPE Z-Score AnalyzerThis macro-focused indicator visualizes the historical valuation of the U.S. equity market using the CAPE ratio (Shiller P/E), normalized over its long-term average and standard deviations. It helps traders and investors identify overvaluation and undervaluation zones over time, combining both statistical signals and historical context.
💡 Why It’s Useful
This indicator is ideal for macro traders and long-term investors looking to contextualize equity valuations across decades. It helps identify statistical extremes in valuation by referencing the standard deviation of the CAPE ratio relative to its long-term mean. The overlay of S&P 500 price with valuation zones provides a visual confirmation tool for macro decisions or timing insights.
It includes:
✅ Three display modes:
-S&P 500 (color-coded by CAPE valuation zone)
-Normalized CAPE (vs. long-term mean)
-CAPE Z-Score (standardized measure)
🎯 How to Interpret
Dynamic coloring of the S&P 500 price based on CAPE valuation:
🔴 Z > +2σ → Highly Overvalued
🟠 Z > +1σ → Overvalued
⚪ -1σ < Z < +1σ → Neutral
🟢 Z < -1σ → Undervalued
✅ Z < -2σ → Strong Buy Zone
-Live valuation label showing the current CAPE, Z-score, and zone.
-Macro event shading: major historical events (e.g. Great Depression, Oil Crisis, Dot-com Bubble, COVID Crash) are shaded on the chart for context.
✅ Built-in alerts:
CAPE > +2σ → Potential risk zone
CAPE < -2σ → Potential opportunity zone
📊 Use Cases
This indicator is ideal for:
🧠 Macro traders seeking long-term valuation extremes.
📈 Portfolio managers monitoring systemic valuation risk.
🏛️ Long-term investors timing strategic allocation shifts.
🧪 How It Works
CAPE ratio (Shiller PE) is retrieved from Quandl (MULTPL/SHILLER_PE_RATIO_MONTH).
The script calculates the long-term average and standard deviation of CAPE.
The Z-score is computed as:
(CAPE - Mean) / Standard Deviation
Users can switch between:
S&P 500 chart, color-coded by CAPE valuation zones.
Normalized CAPE, centered around zero (historic mean).
CAPE Z-score, showing statistical positioning directly.
Visual bands represent +1σ, +2σ, -1σ, -2σ thresholds.
You can switch between modes using the “Display” dropdown in the settings panel.
📊 Data Sources
CAPE: MULTPL/SHILLER_PE_RATIO_MONTH via Quandl
S&P 500: Monthly close prices of SPX (PulseWire data)
All data updated on monthly resolution
This is not a repackaged built-in or autogenerated script. It’s a custom-built and interactive indicator designed for educational and analytical use in macroeconomic valuation studies. Indicator
FuTech : Earnings (All 269 Fundamental Metrics of Tradingview)FuTech : Earnings Indicator
The FuTech : Earnings Indicator is a revolutionary tool, offering the most comprehensive integration of all 269 fundamental financial metrics available from the PulseWire platform.
This groundbreaking indicator is designed to empower financial researchers, traders, investors, and analysts with an unmatched depth of data, enabling superior analysis and decision-making.
Overview
"FuTech : Earnings Indicator" is the first-ever indicator to provide a holistic comparison of fundamental financial metrics for any stock, covering quarterly, yearly, and trailing twelve months (TTM) periods.
This tool brings together key financial data from income statements, balance sheets, cash flows, and other critical metrics found in company annual reports.
It also incorporates additional unique features like per-employee data, R&D expenses, and capital expenditures (CapEx), which are typically hidden within dense financial statements of Annual Reports.
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Key Features and Capabilities
1. Comprehensive Financial Metrics
- "FuTech : Earnings Indicator" offers access to all 269 fundamental metrics available on PulseWire platform. This includes widely used data such as revenue, profit margins, and EPS, alongside more niche metrics like R&D expenditure, employee efficiency, and financial scores developed by renowned analysts.
- Users can explore income statement data (e.g., net income, gross profit), balance sheet items (e.g., total assets, liabilities), cash flow metrics, and other financial statistics such as Altman Score, per employee expenses etc. in unparalleled detail.
2. Comparison Across Time Periods
- "FuTech : Earnings Indicator" allows users to analyze data for:
- Quarterly periods (e.g., Q1, Q2, Q3, Q4).
- Yearly comparisons for a broad historical view.
- TTM analysis to observe the most recent trends and developments.
- Users can select a minimum of 4 periods up to an unlimited range for detailed comparisons in both quarter.
3. Dynamic Data Display
- Users can select up to 5 key metrics alongside the stock price column to focus their analysis on the most relevant data points.
- Highlighting with green and red symbols offers an intuitive and visual representation:
- Green : Positive trends or improvements.
- Red : Negative trends or deteriorations.
4. Automated Averages
- "FuTech : Earnings Indicator" automatically calculates averages of selected metrics across the chosen periods. This feature helps users quickly identify performance trends and smooth out anomalies, enabling faster and more reliable research.
5. Designed for Research Excellence
- FuTech serves a wide audience, including:
- Corporate finance professionals who need a deep dive into financial metrics.
- Individual investors seeking robust tools for investment analysis.
- Broking companies and equity research analysts performing stock analysis.
- Traders looking to incorporate fundamental metrics into their strategies.
- Technical analysts seeking a better understanding of price behavior in relation to fundamentals.
- Fundamental research aspirants who want an edge in their learning process.
6. Unmatched Detail for Deeper Insights
- By pulling all 269 Financial metrics from the PulseWire, "FuTech : Earnings Indicator" enables:
- Cross-comparison of a stock’s performance with its historical benchmarks.
- Evaluation of rare data like R&D expenses, CapEx trends, and employee efficiency ratios for enhanced investment insights.
- This ensures users can study stocks in greater depth than ever before.
7. Enhanced Usability
- Simple to use and visually appealing, "FuTech : Earnings Indicator" is designed with researchers in mind.
- Its intuitive interface ensures even novice users can navigate the wealth of data without feeling overwhelmed.
Applications of FuTech : Earnings Indicator
FuTech : Earnings Indicator is incredibly versatile and has applications in diverse fields of financial research and trading:
1. Corporate Finance
- Professionals in corporate finance can leverage "FuTech : Earnings Indicator" to benchmark company performance, study efficiency ratios, and evaluate financial health across various metrics.
2. Investors and Traders
- Long-term investors can use the tool to study the fundamental strengths of a stock before making buy-and-hold decisions.
- Traders can incorporate "FuTech : Earnings Indicator" into their analysis to align comprehensive fundamental trends with their targeted technical signals.
3. Equity Research Analysts
- Analysts can streamline their workflows by quickly identifying trends, outliers, and averages across large datasets.
4. Education and Research
- "FuTech : Earnings Indicator" is ideal for students and aspiring financial analysts who want a practical tool for understanding real-world data.
How FuTech : Earnings Indicator Stands Out
1. First-Ever Integration of All Financial Metrics
- It's an exclusive tool which offers the ability to explore all 269 financial metrics available on PulseWire for a single stock research in-depth for quarters, years or TTM periods.
2. Period Customization
- Users have complete flexibility to select and analyze data across any range of time periods, allowing for customized insights tailored to specific research goals.
3. Data Visualization
- The intuitive use of color-coded symbols (green for positive trends, red for negative) makes complex data easy to interpret at a glance.
4. Actionable Insights
- The automated average calculations provide actionable insights for making informed decisions without manual computations.
5. Unique Metrics
- Metrics such as research and development costs, CapEx, and per-employee efficiency data offer unique angles that aren’t typically available in traditional analysis tools.
Why to Use FuTech : Earnings Indicator ?
1. Boost Your Research Power
- With FuTech, you can unlock a world of data that gives you the edge in analyzing stocks. Whether you’re a seasoned analyst or a beginner, this tool offers something for everyone.
2. Save Time and Effort
- The automated features and intuitive interface eliminate the need for time-consuming manual calculations and formatting.
3. Make Better Decisions
- "FuTech : Earnings Indicator's" detailed comparison capabilities and insightful visual aids allow for more accurate assessments of a stock’s performance and potential.
4. Broad Appeal
- From individual investors to financial institutions, FuTech is a valuable tool for anyone in the world of finance.
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Conclusion
- The FuTech : Earnings Indicator is a must-have for anyone serious about financial analysis.
- It combines the depth of all 269 fundamental metrics with intuitive tools for comparison, visualization, and calculation.
- Designed for ease of use and powerful insights, FuTech : Earnings Indicator is set to transform the way financial data is analyzed and understood.
Thank you !
Jai Swaminarayan Dasna Das !
He Hari ! Bas Ek Tu Raji Tha ! Indicator
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