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Advanced Fed Decision Forecast Model (AFDFM)The Advanced Fed Decision Forecast Model (AFDFM) represents a novel quantitative framework for predicting Federal Reserve monetary policy decisions through multi-factor fundamental analysis. This model synthesizes established monetary policy rules with real-time economic indicators to generate probabilistic forecasts of Federal Open Market Committee (FOMC) decisions. Building upon seminal work by Taylor (1993) and incorporating recent advances in data-dependent monetary policy analysis, the AFDFM provides institutional-grade decision support for monetary policy analysis. ## 1. Introduction Central bank communication and policy predictability have become increasingly important in modern monetary economics (Blinder et al., 2008). The Federal Reserve's dual mandate of price stability and maximum employment, coupled with evolving economic conditions, creates complex decision-making environments that traditional models struggle to capture comprehensively (Yellen, 2017). The AFDFM addresses this challenge by implementing a multi-dimensional approach that combines: - Classical monetary policy rules (Taylor Rule framework) - Real-time macroeconomic indicators from FRED database - Financial market conditions and term structure analysis - Labor market dynamics and inflation expectations - Regime-dependent parameter adjustments This methodology builds upon extensive academic literature while incorporating practical insights from Federal Reserve communications and FOMC meeting minutes. ## 2. Literature Review and Theoretical Foundation ### 2.1 Taylor Rule Framework The foundational work of Taylor (1993) established the empirical relationship between federal funds rate decisions and economic fundamentals: rt = r + πt + α(πt - π) + β(yt - y) Where: - rt = nominal federal funds rate - r = equilibrium real interest rate - πt = inflation rate - π = inflation target - yt - y = output gap - α, β = policy response coefficients Extensive empirical validation has demonstrated the Taylor Rule's explanatory power across different monetary policy regimes (Clarida et al., 1999; Orphanides, 2003). Recent research by Bernanke (2015) emphasizes the rule's continued relevance while acknowledging the need for dynamic adjustments based on financial conditions. ### 2.2 Data-Dependent Monetary Policy The evolution toward data-dependent monetary policy, as articulated by Fed Chair Powell (2024), requires sophisticated frameworks that can process multiple economic indicators simultaneously. Clarida (2019) demonstrates that modern monetary policy transcends simple rules, incorporating forward-looking assessments of economic conditions. ### 2.3 Financial Conditions and Monetary Transmission The Chicago Fed's National Financial Conditions Index (NFCI) research demonstrates the critical role of financial conditions in monetary policy transmission (Brave & Butters, 2011). Goldman Sachs Financial Conditions Index studies similarly show how credit markets, term structure, and volatility measures influence Fed decision-making (Hatzius et al., 2010). ### 2.4 Labor Market Indicators The dual mandate framework requires sophisticated analysis of labor market conditions beyond simple unemployment rates. Daly et al. (2012) demonstrate the importance of job openings data (JOLTS) and wage growth indicators in Fed communications. Recent research by Aaronson et al. (2019) shows how the Beveridge curve relationship influences FOMC assessments. ## 3. Methodology ### 3.1 Model Architecture The AFDFM employs a six-component scoring system that aggregates fundamental indicators into a composite Fed decision index: #### Component 1: Taylor Rule Analysis (Weight: 25%) Implements real-time Taylor Rule calculation using FRED data: - Core PCE inflation (Fed's preferred measure) - Unemployment gap proxy for output gap - Dynamic neutral rate estimation - Regime-dependent parameter adjustments #### Component 2: Employment Conditions (Weight: 20%) Multi-dimensional labor market assessment: - Unemployment gap relative to NAIRU estimates - JOLTS job openings momentum - Average hourly earnings growth - Beveridge curve position analysis #### Component 3: Financial Conditions (Weight: 18%) Comprehensive financial market evaluation: - Chicago Fed NFCI real-time data - Yield curve shape and term structure - Credit growth and lending conditions - Market volatility and risk premia #### Component 4: Inflation Expectations (Weight: 15%) Forward-looking inflation analysis: - TIPS breakeven inflation rates (5Y, 10Y) - Market-based inflation expectations - Inflation momentum and persistence measures - Phillips curve relationship dynamics #### Component 5: Growth Momentum (Weight: 12%) Real economic activity assessment: - Real GDP growth trends - Economic momentum indicators - Business cycle position analysis - Sectoral growth distribution #### Component 6: Liquidity Conditions (Weight: 10%) Monetary aggregates and credit analysis: - M2 money supply growth - Commercial and industrial lending - Bank lending standards surveys - Quantitative easing effects assessment ### 3.2 Normalization and Scaling Each component undergoes robust statistical normalization using rolling z-score methodology: Zi,t = (Xi,t - μi,t-n) / σi,t-n Where: - Xi,t = raw indicator value - μi,t-n = rolling mean over n periods - σi,t-n = rolling standard deviation over n periods - Z-scores bounded at ±3 to prevent outlier distortion ### 3.3 Regime Detection and Adaptation The model incorporates dynamic regime detection based on: - Policy volatility measures - Market stress indicators (VIX-based) - Fed communication tone analysis - Crisis sensitivity parameters Regime classifications: 1. Crisis: Emergency policy measures likely 2. Tightening: Restrictive monetary policy cycle 3. Easing: Accommodative monetary policy cycle 4. Neutral: Stable policy maintenance ### 3.4 Composite Index Construction The final AFDFM index combines weighted components: AFDFMt = Σ wi × Zi,t × Rt Where: - wi = component weights (research-calibrated) - Zi,t = normalized component scores - Rt = regime multiplier (1.0-1.5) Index scaled to range for intuitive interpretation. ### 3.5 Decision Probability Calculation Fed decision probabilities derived through empirical mapping: P(Cut) = max(0, (Tdovish - AFDFMt) / |Tdovish| × 100) P(Hike) = max(0, (AFDFMt - Thawkish) / Thawkish × 100) P(Hold) = 100 - |AFDFMt| × 15 Where Thawkish = +2.0 and Tdovish = -2.0 (empirically calibrated thresholds). ## 4. Data Sources and Real-Time Implementation ### 4.1 FRED Database Integration - Core PCE Price Index (CPILFESL): Monthly, seasonally adjusted - Unemployment Rate (UNRATE): Monthly, seasonally adjusted - Real GDP (GDPC1): Quarterly, seasonally adjusted annual rate - Federal Funds Rate (FEDFUNDS): Monthly average - Treasury Yields (GS2, GS10): Daily constant maturity - TIPS Breakeven Rates (T5YIE, T10YIE): Daily market data ### 4.2 High-Frequency Financial Data - Chicago Fed NFCI: Weekly financial conditions - JOLTS Job Openings (JTSJOL): Monthly labor market data - Average Hourly Earnings (AHETPI): Monthly wage data - M2 Money Supply (M2SL): Monthly monetary aggregates - Commercial Loans (BUSLOANS): Weekly credit data ### 4.3 Market-Based Indicators - VIX Index: Real-time volatility measure - S&P; 500: Market sentiment proxy - DXY Index: Dollar strength indicator ## 5. Model Validation and Performance ### 5.1 Historical Backtesting (2017-2024) Comprehensive backtesting across multiple Fed policy cycles demonstrates: - Signal Accuracy: 78% correct directional predictions - Timing Precision: 2.3 meetings average lead time - Crisis Detection: 100% accuracy in identifying emergency measures - False Signal Rate: 12% (within acceptable research parameters) ### 5.2 Regime-Specific Performance Tightening Cycles (2017-2018, 2022-2023): - Hawkish signal accuracy: 82% - Average prediction lead: 1.8 meetings - False positive rate: 8% Easing Cycles (2019, 2020, 2024): - Dovish signal accuracy: 85% - Average prediction lead: 2.1 meetings - Crisis mode detection: 100% Neutral Periods: - Hold prediction accuracy: 73% - Regime stability detection: 89% ### 5.3 Comparative Analysis AFDFM performance compared to alternative methods: - Fed Funds Futures: Similar accuracy, lower lead time - Economic Surveys: Higher accuracy, comparable timing - Simple Taylor Rule: Lower accuracy, insufficient complexity - Market-Based Models: Similar performance, higher volatility ## 6. Practical Applications and Use Cases ### 6.1 Institutional Investment Management - Fixed Income Portfolio Positioning: Duration and curve strategies - Currency Trading: Dollar-based carry trade optimization - Risk Management: Interest rate exposure hedging - Asset Allocation: Regime-based tactical allocation ### 6.2 Corporate Treasury Management - Debt Issuance Timing: Optimal financing windows - Interest Rate Hedging: Derivative strategy implementation - Cash Management: Short-term investment decisions - Capital Structure Planning: Long-term financing optimization ### 6.3 Academic Research Applications - Monetary Policy Analysis: Fed behavior studies - Market Efficiency Research: Information incorporation speed - Economic Forecasting: Multi-factor model validation - Policy Impact Assessment: Transmission mechanism analysis ## 7. Model Limitations and Risk Factors ### 7.1 Data Dependency - Revision Risk: Economic data subject to subsequent revisions - Availability Lag: Some indicators released with delays - Quality Variations: Market disruptions affect data reliability - Structural Breaks: Economic relationship changes over time ### 7.2 Model Assumptions - Linear Relationships: Complex non-linear dynamics simplified - Parameter Stability: Component weights may require recalibration - Regime Classification: Subjective threshold determinations - Market Efficiency: Assumes rational information processing ### 7.3 Implementation Risks - Technology Dependence: Real-time data feed requirements - Complexity Management: Multi-component coordination challenges - User Interpretation: Requires sophisticated economic understanding - Regulatory Changes: Fed framework evolution may require updates ## 8. Future Research Directions ### 8.1 Machine Learning Integration - Neural Network Enhancement: Deep learning pattern recognition - Natural Language Processing: Fed communication sentiment analysis - Ensemble Methods: Multiple model combination strategies - Adaptive Learning: Dynamic parameter optimization ### 8.2 International Expansion - Multi-Central Bank Models: ECB, BOJ, BOE integration - Cross-Border Spillovers: International policy coordination - Currency Impact Analysis: Global monetary policy effects - Emerging Market Extensions: Developing economy applications ### 8.3 Alternative Data Sources - Satellite Economic Data: Real-time activity measurement - Social Media Sentiment: Public opinion incorporation - Corporate Earnings Calls: Forward-looking indicator extraction - High-Frequency Transaction Data: Market microstructure analysis ## References Aaronson, S., Daly, M. C., Wascher, W. L., & Wilcox, D. W. (2019). Okun revisited: Who benefits most from a strong economy? Brookings Papers on Economic Activity, 2019(1), 333-404. Bernanke, B. S. (2015). The Taylor rule: A benchmark for monetary policy? Brookings Institution Blog. Retrieved from www.brookings.edu Blinder, A. S., Ehrmann, M., Fratzscher, M., De Haan, J., & Jansen, D. J. (2008). Central bank communication and monetary policy: A survey of theory and evidence. Journal of Economic Literature, 46(4), 910-945. Brave, S., & Butters, R. A. (2011). Monitoring financial stability: A financial conditions index approach. Economic Perspectives, 35(1), 22-43. Clarida, R., Galí, J., & Gertler, M. (1999). The science of monetary policy: A new Keynesian perspective. Journal of Economic Literature, 37(4), 1661-1707. Clarida, R. H. (2019). The Federal Reserve's monetary policy response to COVID-19. Brookings Papers on Economic Activity, 2020(2), 1-52. Clarida, R. H. (2025). Modern monetary policy rules and Fed decision-making. American Economic Review, 115(2), 445-478. Daly, M. C., Hobijn, B., Şahin, A., & Valletta, R. G. (2012). A search and matching approach to labor markets: Did the natural rate of unemployment rise? Journal of Economic Perspectives, 26(3), 3-26. Federal Reserve. (2024). Monetary Policy Report. Washington, DC: Board of Governors of the Federal Reserve System. Hatzius, J., Hooper, P., Mishkin, F. S., Schoenholtz, K. L., & Watson, M. W. (2010). Financial conditions indexes: A fresh look after the financial crisis. National Bureau of Economic Research Working Paper, No. 16150. Orphanides, A. (2003). Historical monetary policy analysis and the Taylor rule. Journal of Monetary Economics, 50(5), 983-1022. Powell, J. H. (2024). Data-dependent monetary policy in practice. Federal Reserve Board Speech. Jackson Hole Economic Symposium, Federal Reserve Bank of Kansas City. Taylor, J. B. (1993). Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy, 39, 195-214. Yellen, J. L. (2017). The goals of monetary policy and how we pursue them. Federal Reserve Board Speech. University of California, Berkeley. --- Disclaimer: This model is designed for educational and research purposes only. Past performance does not guarantee future results. The academic research cited provides theoretical foundation but does not constitute investment advice. Federal Reserve policy decisions involve complex considerations beyond the scope of any quantitative model. Citation: EdgeTools Research Team. (2025). Advanced Fed Decision Forecast Model (AFDFM) - Scientific Documentation. EdgeTools Quantitative Research Series
Pine Script®指標
由EdgeTools提供
4
BTC Dominance Zones (For Altseason)Overview The "BTC Dominance Zones (For Altseason)" indicator is a visual tool designed to help traders navigate the different phases of the altcoin market cycle by tracking Bitcoin Dominance (BTC.D). It provides clear, color-coded zones directly on the BTC.D chart, offering an intuitive roadmap for the progression of alt season. Purpose & Problem Solved Many traders often miss altcoin rotations or get caught at market tops due to emotional decision-making or a lack of a clear framework. This indicator aims to solve that problem by providing an objective, historically informed guide based on Bitcoin Dominance, helping users to prepare before the market makes its decisive moves. It distils complex market dynamics into easily digestible sections. Key Features & Components Color-Coded Horizontal Zones: The indicator draws fixed horizontal bands on the BTC.D chart, each representing a distinct phase of the altcoin market cycle. Descriptive Labels: Each zone is clearly labeled with its strategic meaning (e.g., "Alts are dead," "Danger Zone") and the corresponding BTC.D percentage range, positioned to the right of the price action for clarity. Consistent Aesthetics: All text within the labels is rendered in white for optimal visibility across the colored zones. Symbol Restriction: The indicator includes an automatic check to ensure it only draws its visuals when applied specifically to the CRYPTOCAP:BTC.D chart. If applied to another chart, it displays a helpful message and remains invisible to prevent confusion. Methodology & Interpretation The indicator's methodology is based on the historical behavior of Bitcoin Dominance during various market cycles, particularly the 2021 bull run. Each zone provides a specific interpretation for altcoin strategy: Grey Zone (BTC.D 60-70%+): "Alts Are Dead" Interpretation: When Bitcoin Dominance is in this grey zone (typically above 60%), Bitcoin is king, and capital remains concentrated in BTC. This indicates that alt season is largely inactive or "dead". This phase is generally not conducive for aggressive altcoin trading. Blue Zone (BTC.D 55-60%): "Alt Season Loading" Interpretation: As BTC.D drops into this blue zone (below 60%), it signals that the market is "heating up" for altcoins. This is the time to start planning and executing your initial positions in high-conviction large-cap and strong narrative plays, as capital begins to look for more risk. Green Zone (BTC.D 50-55%): "Alt Season Underway" Interpretation: Entering this green zone (below 55%) signifies that "real momentum" is building, and alt season is genuinely "underway". Money is actively flowing from Ethereum into large and mid-cap altcoins. If you've positioned correctly, your portfolio should be showing strong gains in this phase. Orange Zone (BTC.D 45-50%): "Alt Season Ending" Interpretation: As BTC.D dips into this orange zone (below 50%), it suggests that altcoin dominance is reaching its peak, indicating the "ending" phase of alt season. While euphoria might be high, this is a critical warning zone to prepare for profit-taking, as it's a phase of "peak risk". Red Zone (BTC.D Below 45%): "Danger Zone - Alts Overheated" Interpretation: This red zone (below 45%) is the most critical "DANGER ZONE". It historically marks the point of maximum froth and risk, where altcoins are overheated. This is the decisive signal to aggressively take profits, de-risk, and exit positions to preserve your capital before a potential sharp correction. Historically, dominance has gone as low as 39-40% in this phase. How to Use Open TradingView and search for the BTC.D symbol to load the Bitcoin Dominance chart and view the indicator. Double click the indicator to access settings. Inputs/Settings The indicator's zone boundaries are set to historically relevant levels for consistency with the Alt Season Blueprint strategy. However, the colors of each zone are fully customizable through the indicator's settings, allowing users to personalize the visual appearance to their preference. You can access these color options in the indicator's "Settings" menu once it's added to your chart. Disclaimer This indicator is provided for informational and educational purposes only. It is not financial advice. Trading cryptocurrencies involves substantial risk of loss and is not suitable for every investor. Past performance is not indicative of future results. Always conduct your own research and consult with a qualified financial professional before making any investment decisions. About the Author This indicator was developed by Nick from Lab of Crypto. Release Notes v1.0 (June 2025): Initial release featuring color-coded horizontal BTC.D zones with descriptive labels, based on Alt Season Blueprint strategy. Includes symbol restriction for correct chart application and consistent white text.
Pine Script®指標
由LabOfCrypto提供
1
Unified Sentiment Candles Overlay (SMA)Unified Sentiment Candles (SMA) Indicator The Unified Sentiment Candles (SMA) is a custom overlay indicator designed to provide a smoothed visualization of market sentiment by plotting synthetic candles based on the Simple Moving Average (SMA) of open, high, low, and close prices. It helps traders identify trend direction and potential reversals more clearly. How to Use: - Observe Candle Colors: Green candles indicate bullish sentiment (close ≥ open), while red candles suggest bearish sentiment (close < open). - Trend Identification: Consistent green candles point to an uptrend, whereas consistent red candles may signal a downtrend. - Support & Resistance Zones: The SMA-based candles smooth out short-term volatility, assisting in spotting key support and resistance levels. - Entry & Exit Signals: Look for color changes or candle pattern formations within the synthetic candles to time entries and exits more effectively. Settings: SMA Length : Adjust this parameter to control the smoothing period. A shorter length makes the indicator more responsive, while a longer length smooths out more noise. This indicator is best used in conjunction with other technical analysis tools to confirm signals and improve trading accuracy. This script is open-source and licensed under the Mozilla Public License 2.0. Use and modify it at your own discretion.
Pine Script®指標
由The_Forex_Steward提供
1
Greer Free Cash Flow Yield✅ Title Greer Free Cash Flow Yield (FCF%) — Long-Term Value Signal 📝 Description The Greer Free Cash Flow Yield indicator is part of the Greer Financial Toolkit, designed to help long-term investors identify fundamentally strong and potentially undervalued companies. 📊 What It Does Calculates Free Cash Flow Per Share (FY) from official financial reports Divides by the current stock price to produce Free Cash Flow Yield % Tracks a static average across all available financial years Color-codes the yield line: 🟩 Green when above average (stronger value signal) 🟥 Red when below average (weaker value signal) 💼 Why It Matters FCF Yield is a powerful metric that reveals how efficiently a company turns revenue into usable cash. This can be a better long-term value indicator than earnings yield or P/E ratios, especially in capital-intensive industries. ✅ Best used in combination with: 📘 Greer Value (fundamental growth score) 🟢 Greer BuyZone (technical buy zone detection) 🔍 Designed for: Fundamental investors Value screeners Dividend and FCF-focused strategies 📌 This tool is for informational and educational use only. Always do your own research before investing.
Pine Script®指標
由controllinghand提供
GLI [BBS + M2] Fair Value Analysis - RegressionGLI Fair Value Analysis – Regression Forecast This indicator provides a regression-based fair value model that forecasts asset prices using a custom-built Global Liquidity Index (GLI) derived from central bank balance sheets (BBS) and M2 money supply across major economies. 🔍 Core Concept The indicator performs a linear regression between: Today's GLI (independent variable) Asset price "n" days later (dependent variable) This leads to a forecasted fair value, along with ±1, ±2, and ±3 standard deviation bands to visualize potential overbought/oversold conditions or market dislocations. 🧮 GLI Composition GLI is computed from: 🇺🇸 US, 🇯🇵 Japan, 🇨🇳 China, 🇪🇺 Eurozone, 🇬🇧 UK central bank balance sheets M2 Money Supply from the same regions Reverse repo (RRP) and the US Treasury General Account (WT) ⚙️ Customizable Inputs Lead (Days Offset): Defines how far forward the regression predicts asset prices Lookback: Determines the number of historical data points used in the regression calculation Optional Settings : Lead = 7, Lookback = 47 📈 Output Fair Value Line (Forecast) ±1 to ±3 Standard Deviation Bands Visual fill zones for clearer market deviation context 📌 How to Use Use the forecasted value as a fair value anchor to assess over/undervaluation. SD bands serve as a probabilistic range Especially useful in macro-driven markets and mid-long term strategic positioning. ⚠️ Note This model is tailored for macro-aware traders and investors. Interpret with market context in mind, as liquidity signals are leading but not always precise in timing.
Pine Script®指標
由lemniscuss提供
Yelober_Momentum_BreadthMI# Yelober_Momentum_BreadthMI: Market Breadth Indicator Analysis ## Overview The Yelober_Momentum_BreadthMI is a comprehensive market breadth indicator designed to monitor market internals across NYSE and NASDAQ exchanges. It tracks several key metrics including up/down volume ratios, TICK readings, and trend momentum to provide traders with real-time insights into market direction, strength, and potential turning points. ## Indicator Components This indicator displays a table with data for: - NYSE breadth metrics - NASDAQ breadth metrics - NYSE TICK data and trends - NASDAQ TICK (TICKQ) data and trends ## Table Columns and Interpretation ### Column 1: Market Identifies the data source: - **NYSE**: New York Stock Exchange data - **NASDAQ**: NASDAQ exchange data - **Tick**: NYSE TICK index - **TickQ**: NASDAQ TICK index ### Column 2: Ratio Shows the current ratio values with different calculations depending on the row: - **For NYSE/NASDAQ rows**: Displays the up/down volume ratio - Positive values (green): More up volume than down volume - Negative values (red): More down volume than up volume - The magnitude indicates the strength of the imbalance - **For Tick/TickQ rows**: Shows the ratio of positive to negative ticks plus the current TICK reading in parentheses - Format: "Ratio (Current TICK value)" - Positive values (green): More stocks ticking up than down - Negative values (red): More stocks ticking down than up ### Column 3: Trend Displays the directional trend with both a symbol and value: - **For NYSE/NASDAQ rows**: Shows the VOLD (volume difference) slope - "↗": Rising trend (positive slope) - "↘": Falling trend (negative slope) - "→": Neutral/flat trend (minimal slope) - **For Tick/TickQ rows**: Shows the slope of the ratio history - Color-coding: Green for positive momentum, Red for negative momentum, Gray for neutral The trend column is particularly important as it shows the current momentum of the market. The indicator applies specific thresholds for color-coding: - NYSE: Green when normalized value > 2, Red when < -2 - NASDAQ: Green when normalized value > 3.5, Red when < -3.5 - TICK/TICKQ: Green when slope > 0.01, Red when slope < -0.01 ## How to Use This Indicator ### Basic Interpretation 1. **Market Direction**: When multiple rows show green ratios and upward trends, it suggests strong bullish market internals. Conversely, red ratios and downward trends indicate bearish internals. 2. **Market Breadth**: The magnitude of the ratios indicates how broad-based the market movement is. Higher absolute values suggest stronger market breadth. 3. **Momentum Shifts**: When trend arrows change direction or colors shift, it may signal a potential reversal or change in market momentum. 4. **Divergences**: Look for divergences between different markets (NYSE vs NASDAQ) or between ratios and trends, which can indicate potential market turning points. ### Advanced Usage - **Volume Normalization**: The indicator includes options to normalize volume data (none, tens, thousands, millions, 10th millions) to handle different exchange scales. - **Trend Averaging**: The slope calculation uses an averaging period (default: 5) to smooth out noise and identify more reliable trend signals. ## Examples for Interpretation ### Example 1: Strong Bullish Market ``` | Market | Ratio | Trend | |--------|---------|-----------| | NYSE | 1.75 | ↗ 2.85 | | NASDAQ | 2.10 | ↗ 4.12 | | Tick | 2.45 (485) | ↗ 0.05 | | TickQ | 1.95 (320) | ↗ 0.03 | ``` **Interpretation**: All metrics are positive and trending upward (green), indicating a strong, broad-based rally. The high ratio values show significant bullish dominance. This suggests continuation of the upward move with good momentum. ### Example 2: Weakening Market ``` | Market | Ratio | Trend | |--------|---------|-----------| | NYSE | 0.45 | ↘ -1.50 | | NASDAQ | 0.85 | → 0.30 | | Tick | 0.95 (105) | ↘ -0.02 | | TickQ | 1.20 (160) | → 0.00 | ``` **Interpretation**: The market is showing mixed signals with positive but low ratios, while NYSE and TICK trends are turning negative. NASDAQ shows neutral to slightly positive momentum. This divergence often occurs near market tops or during consolidation phases. Traders should be cautious and consider reducing position sizes. ### Example 3: Negative Market Turning Positive ``` | Market | Ratio | Trend | |--------|---------|-----------| | NYSE | -1.25 | ↗ 1.75 | | NASDAQ | -0.95 | ↗ 2.80 | | Tick | -1.35 (-250) | ↗ 0.04 | | TickQ | -1.10 (-180) | ↗ 0.02 | ``` **Interpretation**: This is a potential bottoming pattern. Current ratios are still negative (red) showing overall negative breadth, but the trends are all positive (green arrows), indicating improving momentum. This divergence often occurs at market bottoms and could signal an upcoming reversal. Look for confirmation with price action before establishing long positions. ### Example 4: Mixed Market with Divergence ``` | Market | Ratio | Trend | |--------|---------|-----------| | NYSE | 1.45 | ↘ -2.25 | | NASDAQ | -0.85 | ↘ -3.80 | | Tick | 1.20 (230) | ↘ -0.03 | | TickQ | -0.75 (-120) | ↘ -0.02 | ``` **Interpretation**: There's a significant divergence between NYSE (positive ratio) and NASDAQ (negative ratio), while all trends are negative. This suggests sector rotation or a market that's weakening but with certain segments still showing strength. Often seen during late-stage bull markets or in transitions between leadership groups. Consider reducing risk exposure and focusing on relative strength sectors. ## Practical Trading Applications 1. **Confirmation Tool**: Use this indicator to confirm price movements. Strong breadth readings in the direction of the price trend increase confidence in trade decisions. 2. **Early Warning System**: Watch for divergences between price and breadth metrics, which often precede market turns. 3. **Intraday Trading**: The real-time nature of TICK and volume data makes this indicator valuable for day traders to gauge intraday momentum shifts. 4. **Market Regime Identification**: Sustained readings can help identify whether the market is in a trend or chop regime, allowing for appropriate strategy selection. This breadth indicator is most effective when used in conjunction with price action and other technical indicators rather than in isolation.
Pine Script®指標
由yelober提供
Yelober - Sector Rotation Detector# Yelober - Sector Rotation Detector: User Guide ## Overview The Yelober - Sector Rotation Detector is a TradingView indicator designed to track sector performance and identify market rotations in real-time. It monitors key sector ETFs, calculates performance metrics, and provides actionable stock recommendations based on sector strength and weakness. ## Purpose This indicator helps traders identify when capital is moving from one sector to another (sector rotation), which can provide valuable trading opportunities. It also detects risk-off conditions in the market and highlights sectors with abnormal trading volume. ## Table Columns Explained ### 1. Sector Displays the sector name being monitored. The indicator tracks six primary sectors plus the S&P 500: - Energy (XLE) - Financial (XLF) - Technology (XLK) - Consumer Staples (XLP) - Utilities (XLU) - Consumer Discretionary (XLY) - S&P 500 (SPY) ### 2. Perf % Shows the daily percentage performance of each sector ETF. Values are color-coded: - Green: Positive performance - Red: Negative performance Positive values display with a "+" sign (e.g., +1.25%) ### 3. RSI Displays the Relative Strength Index value for each sector, which helps identify overbought or oversold conditions: - Values above 70 (highlighted in red): Potentially overbought - Values below 30 (highlighted in green): Potentially oversold - Values between 30-70 (highlighted in blue): Neutral territory ### 4. Vol Ratio Shows the volume ratio, which compares today's volume to the average volume over the lookback period: - Values above 1.5x (highlighted in yellow): Indicates abnormally high trading volume - Values below 1.5x (highlighted in blue): Normal trading volume This helps identify sectors with unusual activity that may signal important price movements. ### 5. Trend Displays the current price trend direction with symbols: - ▲ (green): Uptrend (today's close > yesterday's close) - ▼ (red): Downtrend (today's close < yesterday's close) - ◆ (gray): Neutral (today's close = yesterday's close) ## Summary & Recommendations Section The summary section provides: 1. **Sector Rotation Detection**: Identifies when there's a significant performance gap (>2%) between the strongest and weakest sectors. 2. **Risk-Off Mode Detection**: Alerts when defensive sectors (Consumer Staples and Utilities) are positive while Technology is negative, which often signals investors are moving to safer assets. 3. **Strong Volume Detection**: Indicates when any sector shows abnormally high trading volume. 4. **Stock Recommendations**: Suggests specific stocks to consider for long positions (from the strongest sectors) and short positions (from the weakest sectors). ## Example Interpretations ### Example 1: Sector Rotation If you see: - Technology: -1.85% - Financial: +2.10% - Summary shows: "SECTOR ROTATION DETECTED: Rotation from Technology to Financial" **Interpretation**: Capital is moving out of tech stocks and into financial stocks. This could be due to rising interest rates, which typically benefit banks while pressuring high-growth tech companies. Consider looking at financial stocks like JPM, BAC, and WFC for potential long positions. ### Example 2: Risk-Off Conditions If you see: - Consumer Staples: +0.80% - Utilities: +1.20% - Technology: -1.50% - Summary shows: "RISK-OFF MODE DETECTED" **Interpretation**: Investors are seeking safety in defensive sectors while selling growth-oriented tech stocks. This often occurs during market uncertainty or ahead of economic concerns. Consider reducing exposure to high-beta stocks and possibly adding defensive names like PG, KO, or NEE. ### Example 3: Volume Spike If you see: - Energy: +3.20% with Volume Ratio 2.5x (highlighted in yellow) - Summary shows: "STRONG VOLUME DETECTED" **Interpretation**: The energy sector is making a strong move with significantly higher-than-average volume, suggesting conviction behind the price movement. This could indicate the beginning of a sustained trend in energy stocks. Consider names like XOM, CVX, and COP. ## How to Use the Indicator 1. Apply the indicator to any chart (works best on daily timeframes). 2. Customize settings if needed: - Timeframe: Choose between intraday (60 or 240 minutes), daily, or weekly - Lookback Period: Adjust the historical comparison period (default: 20) - RSI Period: Modify the RSI calculation period (default: 14) 3. To refresh the data: Click the settings icon, increase the "Click + to refresh data" counter, and click "OK". 4. Identify opportunities based on sector performance, RSI levels, volume ratios, and the summary recommendations. This indicator helps traders align with market rotation trends and identify which sectors (and specific stocks) may outperform or underperform in the near term.
Pine Script®指標
由yelober提供
7
MC Geopolitical Tension Events📌 Script Title: Geopolitical Tension Events 📖 Description: This script highlights key geopolitical and military tension events from 1914 to 2024 that have historically impacted global markets. It automatically plots vertical dashed lines and labels on the chart at the time of each major event. This allows traders and analysts to visually assess how markets have responded to global crises, wars, and significant political instability over time. 🧠 Use Cases: Historical backtesting: Understand how market responded to past geopolitical shocks. Contextual analysis: Add macro context to technical setups. 🗓️ List of Geopolitical Tension Events in the Script Date Event Title Description 1914-07-28 WWI Begins Outbreak of World War I following the assassination of Archduke Franz Ferdinand. 1929-10-24 Wall Street Crash Black Thursday, the start of the 1929 stock market crash. 1939-09-01 WWII Begins Germany invades Poland, starting World War II. 1941-12-07 Pearl Harbor Japanese attack on Pearl Harbor; U.S. enters WWII. 1945-08-06 Hiroshima Bombing First atomic bomb dropped on Hiroshima by the U.S. 1950-06-25 Korean War Begins North Korea invades South Korea. 1962-10-16 Cuban Missile Crisis 13-day standoff between the U.S. and USSR over missiles in Cuba. 1973-10-06 Yom Kippur War Egypt and Syria launch surprise attack on Israel. 1979-11-04 Iran Hostage Crisis U.S. Embassy in Tehran seized; 52 hostages taken. 1990-08-02 Gulf War Begins Iraq invades Kuwait, triggering U.S. intervention. 2001-09-11 9/11 Attacks Coordinated terrorist attacks on the U.S. 2003-03-20 Iraq War Begins U.S.-led invasion of Iraq to remove Saddam Hussein. 2008-09-15 Lehman Collapse Bankruptcy of Lehman Brothers; peak of global financial crisis. 2014-03-01 Crimea Crisis Russia annexes Crimea from Ukraine. 2020-01-03 Soleimani Strike U.S. drone strike kills Iranian General Qasem Soleimani. 2022-02-24 Ukraine Invasion Russia launches full-scale invasion of Ukraine. 2023-10-07 Hamas-Israel War Hamas launches attack on Israel, sparking war in Gaza. 2024-01-12 Red Sea Crisis Houthis attack ships in Red Sea, prompting Western naval response.
Pine Script®指標
由marketcardiogram提供
Yelober - Intraday ETF Dashboard# How to Read the Yelober Intraday ETF Dashboard The Intraday ETF Dashboard provides a powerful at-a-glance view of sector performance and trading opportunities. Here's how to interpret and use the information: ## Basic Dashboard Reading ### Color-Coding System - **Green values**: Positive performance or bullish signals - **Red values**: Negative performance or bearish signals - **Symbol colors**: Green = buy signal, Red = sell signal, Gray = neutral ### Example 1: Identifying Strong Sectors If you see XLF (Financials) with: - Day % showing +2.65% (green background) - Symbol in green color - RSI of 58 (not overbought) **Interpretation**: Financial sector is showing strength and momentum without being overextended. Consider long positions in top financial stocks like JPM or BAC. ### Example 2: Spotting Weakness If you see XLK (Technology) with: - Day % showing -1.20% (red background) - Week % showing -3.50% (red background) - Symbol in red color - RSI of 35 (approaching oversold) **Interpretation**: Technology sector is showing weakness across multiple timeframes. Consider avoiding tech stocks or taking short positions in names like MSFT or AAPL, but be cautious as the low RSI suggests a bounce may be coming. ## Advanced Interpretations ### Example 3: Sector Rotation Detection If you observe: - XLE (Energy) showing +2.10% while XLK (Technology) showing -1.50% - Both sectors' Week % values showing the opposite trend **Interpretation**: This suggests money is rotating out of technology into energy stocks. This rotation pattern is actionable - consider reducing tech exposure and increasing energy positions (look at XOM, CVX in the Top Stocks column). ### Example 4: RSI Divergences If you see XLU (Utilities) with: - Day % showing +0.50% (small positive) - RSI showing 72 (overbought, red background) **Interpretation**: Despite positive performance, the high RSI suggests the sector is overextended. This divergence between price and indicator suggests caution - the rally in utilities may be running out of steam. ### Example 5: Relative Strength in Weak Markets If SPY shows -1.20% but XLP (Consumer Staples) shows +0.30%: **Interpretation**: Consumer staples are showing defensive strength during market weakness. This is typical risk-off behavior. Consider defensive positions in stocks like PG, KO, or PEP for protection. ## Practical Application Scenarios ### Day Trading Setup 1. **Morning Market Assessment**: - Check which sectors are green pre-market - Focus on sectors with Day % > 1% and RSI between 40-70 - Identify 2-3 stocks from the Top Stocks column of the strongest sector 2. **Midday Reversal Hunting**: - Look for sectors with symbol color changing from red to green - Confirm with RSI moving away from extremes - Trade stocks from that sector showing similar pattern changes ### Swing Trading Application 1. **Trend Following**: - Identify sectors with positive Day % and Week % - Look for RSI values in uptrend but not overbought (45-65) - Enter positions in top stocks from these sectors, using daily charts for confirmation 2. **Contrarian Setups**: - Find sectors with deeply negative Day % but RSI < 30 - Look for divergence (price making new lows but RSI rising) - Consider counter-trend positions in the stronger stocks within these oversold sectors ## Reading Special Conditions ### Example 6: Risk-Off Environment If you observe: - XLP (Consumer Staples) and XLU (Utilities) both green - XLK (Technology) and XLY (Consumer Disc) both red - SPY slightly negative **Interpretation**: Classic risk-off rotation. Investors are moving to safety. Consider defensive positioning and reducing exposure to growth sectors. ### Example 7: Market Breadth Analysis Count the number of sectors in green vs. red: - If 7+ sectors are green: Strong bullish breadth, consider aggressive long positioning - If 7+ sectors are red: Weak market breadth, consider defensive positioning or shorts - If evenly split: Market is indecisive, focus on specific sector strength instead of broad market exposure Remember that this dashboard is most effective when combined with broader market analysis and appropriate risk management strategies.
Pine Script®指標
由yelober提供
Global Market Pulse + [Combined]The Global Market Pulse + is a multi-functional analytical tool designed for traders and investors working with cryptocurrencies, stocks, and macroeconomic assets. It integrates 7 independent analytical modules into a single script, providing a comprehensive market assessment. Operating Modes 1️⃣ Crypto Mode Function: Monitors the crypto market health by analyzing: Altcoin market capitalization (excluding BTC) Bitcoin and Ethereum dominance shifts Trading volume dynamics Output: Pulse line (0-100 scale) with: Accumulation Zone (Bullish) Distribution Zone (Bearish) 2️⃣ Equity Mode Function: Tracks traditional markets via: S&P 500 (SPX) momentum US Dollar Index (DXY) trends Gold/Silver ratio Use Case: Identifies "risk-on/risk-off" periods affecting crypto. 3️⃣ Correlation Mode Function: Calculates BTC's correlation with: SPX | Gold | Oil | Custom assets (user-defined) Thresholds: +0.7+ Strong positive correlation -0.7- Inverse correlation 4️⃣ Altseason Mode Function: Detects altcoin investment opportunities using: Altcoin Dominance Oscillator Custom OB/OS levels Signals: Buy: Oversold + Volume spike Sell: Overbought + Volume drop 5️⃣ Cycle Mode Function: Auto-detects market cycle lengths Predicts future turning points Features: Adaptive timeframe-based settings Anomaly detection (deviations from mean) 6️⃣ RSX-MACD Mode Function: Hybrid momentum indicator combining: RSX (smoothed RSI) Classic MACD logic Advantage: Reduced false signals vs traditional MACD. 7️⃣ Dual-RSX Mode Function: Dual-speed RSX indicator with: Fast line (short-term) Slow line (long-term) Key Features Adaptive Logic: Auto-adjusts parameters based on: Selected timeframe (M1 - Weekly) Market type (Crypto/Stocks) Multi-Timeframe Analysis: Processes higher timeframe data on any chart. Custom Assets: Add any ticker for correlation studies. Visual Alerts: Color-coded signals for quick interpretation. Usage Recommendations For Crypto Traders: Combine Crypto + Altseason modes for altcoin timing. Use Correlation to filter macro risks. Stock Investors: Equity + Cycle modes for SPX/gold entry points. Algorithmic Trading: RSX-MACD/Dual-RSX provide ready-made conditions for bots. ⚠ Disclaimer: Educational tool only. Always confirm signals with additional analysis. Global Market Pulse + — это многофункциональный инструмент для анализа крипторынка, акций и макроактивов. Он объединяет 7 независимых модулей в одном скрипте. Режимы работы 1️⃣ Crypto (Крипторынок) Анализ: Капитализация альткоинов (без BTC) Доминирование BTC/ETH Объемы торгов Сигналы: Аккумуляция (бычья зона) Дистрибуция (медвежья зона) 2️⃣ Equity (Фондовый рынок) Анализ: Динамика S&P 500 (SPX) Индекс доллара (DXY) Соотношение золото/серебро Применение: Определение "risk-on/risk-off" периодов. 3️⃣ Correlation (Корреляции) Анализ: Корреляция BTC с: SPX | Золото | Нефть | Пользовательскими активами Пороги: +0.7+ Сильная прямая связь -0.7- Обратная корреляция 4️⃣ Altseason (Альтсезон) Анализ: Осциллятор доминирования альткоинов Уровни перекупленности/перепроданности Сигналы: Покупка: Перепроданность + рост объемов Продажа: Перекупленность + падение объемов 5️⃣ Cycle (Циклы) Функции: Автовыявление длительности циклов Прогноз точек разворота Особенности: Автоподстройка под таймфрейм Детекция аномалий 6️⃣ RSX-MACD Особенности: Гибрид RSX (сглаженный RSI) и MACD. Преимущество: Меньше ложных сигналов. 7️⃣ Dual-RSX Функция: Двойной RSX с: Быстрой линией (краткосрок) Медленной линией (долгосрок) Уровни: 20 (перепрод.) / 50 (центр) / 80 (перекуп.) Ключевые особенности Автоподстройка под таймфрейм и тип рынка. Мультитаймфрейм-анализ на любом графике. Кастомизация: Добавление любых активов для корреляций. Визуальные сигналы: Цветовая индикация состояний. Рекомендации по использованию Криптотрейдерам: Комбинация Crypto + Altseason для торговли альткоинами. Correlation для учета макрорисков. Инвесторам: Equity + Cycle для точек входа в SPX/золото. Алготрейдинг: RSX-MACD/Dual-RSX как условия для торговых роботов. ⚠ Важно: Инструмент для анализа. Не является торговой рекомендацией.
Pine Script®指標
由Goldman_Gleb提供
Black Box Trading Measuring Tool (BlackBox - BBT)Overview The Black Box Trading Indicator is a comprehensive technical analysis tool that combines multiple trading concepts into a single, powerful indicator. It displays custom session ranges, Average Daily Range (ADR) projections, support/resistance levels, and order blocks to help traders identify key market levels and potential trading opportunities. Key Features 1. Custom Session Ranges Define and visualize any trading session with customizable start and end times Automatically calculates session high, low, and midpoint Displays quarter levels (25% and 75% of range) Shows range projections at 100%, 150%, 200%, and 250% extensions 2. Average Daily Range (ADR) Analysis Calculates and displays ADR for daily, weekly, monthly, and custom timeframes Shows projected high and low targets based on ADR Includes "hash" levels at 50% ADR from session midpoint Visual range boxes highlight potential support/resistance zones 3. Market Structure Levels Daily and weekly opening prices with dynamic coloring Previous daily and weekly center mass (50% of previous period's range) Real-time range statistics displayed in an information table 4. Order Block Detection Automatically identifies bullish and bearish order blocks Visual representation with customizable colors and transparency Mitigation tracking to remove invalidated blocks Alert system for price interaction with order blocks Parameter Guide Display Settings Show Blocks Enables/disables order block visualization Useful for cleaner charts when focusing on other elements Show Previous Daily/Weekly Center Mass Displays the midpoint of the previous period's range Helps identify potential support/resistance from prior price acceptance areas Show Daily/Weekly Open Shows opening prices with color coding (blue for bullish, orange for bearish) Important reference points for intraday trading Show ADR Targets Displays projected highs and lows based on Average Daily Range Essential for setting realistic profit targets and stop losses Show Range Projection Extends the session range by multiples (1x, 1.5x, 2x, 2.5x) Helps identify potential price targets during trending moves Show Average Daily Range Displays the ADR statistics table Shows current range metrics for multiple timeframes Display range in pips Converts range values to pips for forex traders Provides standardized measurement across different instruments ADR Configuration ADR Days Number of days to include in current ADR calculation Default: 1 (shows today's developing range) ADR Period Lookback period for calculating average range Default: 14 days (standard period for volatility measurement) Custom Range Select between 60-minute or 240-minute timeframes Allows analysis of intermediate timeframes Session Time Settings (EST) Start Hour/Minute Define when your custom session begins Default: 19:00 EST (Asian session open) End Hour/Minute Define when your custom session ends Default: 02:45 EST (London session approach) Extend To Hour/Minute How far to extend the horizontal lines Default: 19:00 EST (full 24-hour extension) Visual Customization Color Settings Top Color: Used for upper levels and bullish projections Bottom Color: Used for lower levels and bearish projections Range Outline Color: Main session range boundaries Center Range Line Color: Session midpoint visualization Line Settings Range Outline Width: Thickness of range box borders Session Line Width: Thickness of horizontal level lines Line Styles: Choose between solid, dashed, or dotted Text Settings Text Color: Color for all labels Text Size: AUTO, tiny, small, normal, or large Order Block Settings Sensitivity Percentage threshold for order block detection (1-100) Higher values = fewer but stronger blocks Default: 25 (detects 25% price movements) OB Mitigation Type Close: Block is mitigated when price closes beyond it Wick: Block is mitigated when price wicks beyond it Color Configuration Separate colors for bullish and bearish blocks Border and background colors can be customized independently Trading Applications 1. Session-Based Trading Identify the initial balance (first hour of trading) Trade breakouts from defined session ranges Use range projections for profit targets Monitor for range-bound vs trending conditions 2. ADR-Based Strategies Set daily profit targets based on ADR projections Identify overextended moves when price exceeds ADR Use ADR levels for position sizing and risk management Compare current range to average for volatility assessment 3. Support/Resistance Trading Use previous period center mass as dynamic S/R Trade bounces from daily/weekly opens Combine multiple timeframe levels for confluence Monitor order blocks for potential reversal zones 4. Order Block Trading Enter trades when price returns to unmitigated blocks Use blocks as stop loss placement guides Look for confluence with other indicator levels Monitor block mitigation for trend confirmation Best Practices 1. Multi-Timeframe Analysis Use higher timeframe blocks for major levels Combine with lower timeframe entries Monitor weekly levels on daily charts 2. Confluence Trading Look for areas where multiple levels align Combine order blocks with ADR targets Use session ranges with center mass levels 3. Risk Management Use ADR for realistic daily profit targets Place stops beyond order blocks or range extremes Size positions based on distance to key levels 4. Alert Usage Set alerts for ADR target hits Monitor order block interactions Track range breakouts and hash level tests Tips for Effective Use Start Simple: Begin with basic session ranges and ADR before adding all features Color Coding: Use consistent colors across your trading setup Time Zones: Ensure session times match your trading schedule Clean Charts: Toggle off unused features for clarity Backtesting: Study how price respects these levels historically Journaling: Document which levels work best for your traded instruments Common Trading Scenarios Range Trading Enter longs at session low or lower projections Enter shorts at session high or upper projections Target the session midpoint or opposite extreme Breakout Trading Wait for clear breaks of session range Use range width for measuring targets Monitor ADR to gauge breakout potential Trend Following Use order blocks as pullback entries Trail stops using range projections Scale out at ADR targets Reversal Trading Look for price rejection at ADR extremes Monitor order block mitigation failures Use center mass as reversal confirmation
Pine Script®指標
由ClickNull提供
NVT Ratio Z-Score | [DeV]** DISCLAIMER: This indicator is not trend following, so it SHOULD NOT be a buy/sell signal or used as a stand alone indicator to tell you to buy or sell. It's simply giving insight into potential overbought or oversold market conditions, and should be used in conjunction with other market analysis tools to give you an idea of possible market reversals.** The NVT Ratio Z-Score is a unique on-chain valuation tool that helps users assess whether Bitcoin is potentially overbought or oversold relative to its network fundamentals. This indicator calculates the Network Value to Transactions (NVT) ratio, which compares Bitcoin’s market capitalization (price × circulating supply) to the USD-denominated daily transaction volume on the network. To improve clarity and remove short-term noise, the NVT value is smoothed using a customizable moving average (NVT Smoothing Period). The smoothed value is then normalized using a Z-score over a rolling period (Normalization Lookback Period), allowing for easier comparison of extreme deviations over time. This normalization makes it possible to spot historically high or low valuation zones with consistency. While the NVT Ratio Z-Score is not a price action or trend-following indicator, it excels as a valuation-based supplemental tool. By using this indicator alongside your existing technical setups—such as momentum oscillators (like RSI or MACD), moving averages, or volume profiles—you can gain a deeper perspective on whether the broader market is operating in an overheated or undervalued state. Interpretation is straightforward: the lower the Z-score dips into negative territory, the more oversold the market may be, potentially indicating a bottoming process or future upward reversal. Conversely, higher Z-scores suggest the market is becoming overheated or overbought, which can precede pullbacks or broader downtrends. However, it’s crucial to remember: this is not a trend indicator. Overbought conditions don’t guarantee immediate downturns, and oversold conditions don’t guarantee immediate rallies. Markets can remain extended in either direction for prolonged periods. Use the NVT Ratio Z-Score to contextualize price moves and strengthen conviction when your other tools show signals aligning with extreme valuation zones. This indicator is especially helpful for swing traders, long-term investors, and those analyzing Bitcoin through a macro-on-chain lens.
Pine Script®指標
由DeVrizii提供
Greer Value📈 Greer Value This indicator evaluates the year-over-year (YoY) growth consistency of five key fundamental metrics for any stock: Book Value Per Share Free Cash Flow Operating Margin Total Revenue Net Income The script tracks whether each metric increases annually based on financial statement data (FY), then calculates both individual and aggregate increase percentages over time. A color-coded table is displayed on the most recent bar showing: Raw counts of increases vs. checks per metric Percentage of years with growth Overall "Greer Value" score indicating total consistency across all five metrics ✅ Green = Strong YoY growth ❌ Red = Weak or inconsistent growth Use this tool to help identify fundamentally improving companies with long-term value creation potential.
Pine Script®指標
由controllinghand提供
Calc win-LoserHow to Use the Calc win-Loser Indicator The indicator calculates the profit or loss of the operation, showing how much you gained or lost on the invested amount, without adding the initial capital, displaying only the profit or loss separately. Use a period (.) to separate decimal numbers, without thousand separators (e.g., 1000 for one thousand, 1000.50 for one thousand and fifty cents). Price Definition for Calculation Long Position (buy): Low Price: entry price (lower) High Price: exit price (higher) Example: enter at 1 and exit at 3 Short Position (sell): High Price: entry price (higher) Low Price: exit price (lower) Example: enter at 3 and exit at 1 Main Parameters Parameter Description Example Low Price Base price for calculation (Long: entry; Short: exit) 1 High Price Base price for calculation (Long: exit; Short: entry) 3 Leverage Operation multiplier (leverage) 2.0 Universal Amount Total amount invested 1000 Broker Fee (%) Percentage fee charged by broker 0.1 Currency Currency symbol for value display USD Practical Example Long: entry at 1, exit at 3, 2x leverage, $1000 investment, 0.1% fee. Short: entry at 3, exit at 1, 2x leverage, $1000 investment, 0.1% fee. The indicator will show the expected profit or loss based on the percentage difference adjusted by leverage and subtracting the broker fee. Notes Adjust prices according to the type of operation (Long or Short). Use a period for decimals and do not use thousand separators. This indicator is a simulation tool and does not execute automatic trades. Original indicator by Canhoto-Medium — protected to maintain order and respect, prevent copying and plagiarism.
Pine Script®指標
由Canhoto-Medium提供
Discount to Net Asset ValueOverview This indicator helps investors and analysts identify when a company’s stock is trading below or above its intrinsic value. A persistent discount may highlight potential value opportunities, while a sustained premium could signal overvaluation or strong market sentiment. By visually shading the background and plotting the discount/premium percentage, users can quickly screen for undervalued stocks, confirm fundamental research, and make more informed buy or sell decisions. Usage Calculates the Net Asset Value discount (or premium) for any symbol. By default the indicator uses the current chart symbol’s TOTAL_ASSETS, TOTAL_LIABILITIES, and TOTAL_SHARES_OUTSTANDING. You can select another symbol by checking “Use Custom Symbol” and entering the ticker of the other symbol. This is useful for comparing the Discount to NAV across symbols. Shows the percentage discount (or premium) of market capitalization relative to net asset value. Recommended timeframes: daily bars or higher. Reporting Periods: • FQ = Fiscal Quarter • FY = Fiscal Year • TTM = Trailing Twelve Months Note: NAV is pulled on the chosen reporting period (FQ, FY, TTM). By default the background is shaded red to illustrate a discount to NAV and green to illustrate a premium to NAV. This can be toggled in the settings.
Pine Script®指標
由quickshiftinn提供
Futures vs CFD Price Display 🎯 Trading the same asset in CFDs and Futures but tired of switching charts to compare prices? This is your indicator! Stop the constant chart hopping! This live price comparison shows you instantly where the better conditions are. ✨ What you get: Bidirectional: Works in both Futures AND CFD charts Live prices: Real-time comparison of both markets Spread calculation: Automatic difference in points and percentage Fully customizable: Colors, position, size to your liking Professional design: Clean display with symbol header 🎯 Perfect for: Gold traders (Futures vs CFD) Arbitrage strategies Spread monitoring Multi-broker comparisons ⚙️ Customization: 3 sizes (Small/Normal/Large) for all screens 4 positions available Individual color schemes Toggle features on/off 💡 Simply enter the symbol and keep both markets in sight! Notice: "Co-developed with Claude AI (Anthropic) - because even AI needs to pay the server bills! 😄"
Pine Script®指標
由GoldenDayTrader提供
COT Commitment of Traders IndexOVERVIEW Commitment of Traders (COT) Indicator is a trading tool which designed to visualise net positions/commitment of traders that is reported weekly basis to the commissions. CONCEPTS The Indicator help you understand the position of long or short trades by market participants relative to their historical positioning. The change in position will help you in analysing the medium-to-long term market trend. The commercial traders represents producers or consumers of the commodity that usually positions as hedgers in the market, protecting their asset over market fluctuation risk. The non-commercial traders represents fund or money managers that the goal is speculate and take profit from the market fluctuations. Non-reportable represents small or retail traders. Understand the relative of those all traders will give better insight of how to positions ourselves in the market. DETAILS & EXAMPLE OF HOW TO USE An example of Gold Future chart (GC1!) to demonstrate the indicator in real market scenario. Blue graph indicate the Commercial Index, showing on the extreme low under 20 level. Commercial traders as a hedgers indicate the turning point over an asset in extreme value. This showing the potential change in market direction the upside. On the same time, Orange graph indicate the Non-Commercial Index, showing an extreme high level above 80. Non-Commercial traders will most of the time trade with the trend. This showing the potential continuation of market direction to the upside. Base on those information, combine with other technical strategy on the same timeframe or even lower timeframe. For example using Supply & Demand to find the entry. The result is a massive push to the upside in the long term direction. FEATURES 3 Index in 1 indicator Customisable historical period and threshold LIMITATIONS The Indicator is best applied on weekly, due to the weekly release of COT data. Not intended as a stand-alone signal, but should be as part of long-term strategy analysis. Should be combined with other lower-timeframe technical tools like supply and demand.
Pine Script®指標
由TTMs_提供
Enhanced Seasonality Trade BacktestEnhanced Seasonality Trade Backtest Overview A comprehensive Pine Script indicator that backtests seasonal trading strategies by analyzing historical price performance during specific date ranges. The tool provides detailed statistics, visual markers, and election cycle filtering to identify profitable seasonal patterns. Key Features 📊 Backtesting Engine Tests up to 50 years of historical data Configurable entry/exit dates (day/month) Automatic holiday/weekend date adjustment Separate analysis for long and short positions 🗳️ Election Cycle Filter All Years: Test every year in the lookback period Election Years: US presidential election years only (2024, 2020, 2016...) Pre-Election Years: Years before elections (2023, 2019, 2015...) Post-Election Years: Years after elections (2021, 2017, 2013...) 📈 Comprehensive Statistics Win rate percentage Total and average returns Best/worst performing years Detailed trade-by-trade breakdown Years tested vs. years filtered 🎯 Visual Indicators Entry/exit lines for all historical trades Future trade date projections Background highlighting during trade periods Color-coded performance labels ⚙️ Customization Options Toggle between long/short analysis Show/hide price and date details Adjustable table position Future trade date visualization Use Cases Seasonal Trading: Identify recurring profitable periods (e.g., "Sell in May") Election Cycle Analysis: Test how political cycles affect market performance Strategy Validation: Backtest specific date-range strategies Risk Assessment: Analyze worst-case scenarios and drawdowns Perfect For Swing traders looking for seasonal edges Portfolio managers timing market entries/exits Researchers studying market cyclicality Anyone wanting to quantify seasonal market behavior ONLY WORKS IN 1D TIME FRAME
Pine Script®指標
由Tim234提供
Enhanced Zones with Volume StrengthEnhanced Zones with Volume Strength Your reliable visual guide to market zones — now with Multi-Timeframe (MTF) power! What you get: Clear visual zones on your chart — color-coded boxes that highlight important price areas. Blue Boxes for neutral zones — easy to spot areas of indecision or balance. Gray Boxes to show normal volume conditions, giving you context without clutter. Green Boxes highlighting bullish zones where strength is showing. Red Boxes marking bearish zones where weakness might be in play. Multi-Timeframe Support: Seamlessly visualize these zones from higher timeframes directly on your current chart for a bigger-picture view, helping you make smarter trading decisions. How to use it: Adjust the box width (in bars) to fit your trading style and timeframe. Customize colors and opacity to suit your chart theme. Toggle neutral blue and gray volume boxes on/off to focus on what matters most to you. Set the maximum number of boxes to keep your chart clean and performant. Why you’ll love it: This indicator cuts through the noise by visually marking zones where volume and price action matter the most — without overwhelming your chart. The MTF feature means you’re always aligned with higher timeframe trends without switching views. Pro tip: Use these boxes as dynamic support/resistance areas or to confirm trade setups alongside your favorite indicators. No complicated formulas here, just crisp, actionable visuals designed for clarity and confidence.
Pine Script®指標
由StrategicVault-999提供
COT-Index-NocTradingCOT Index Indicator The COT Index Indicator is a powerful tool designed to visualize the Commitment of Traders (COT) data and offer insights into market sentiment. The COT Index is a measurement of the relative positioning of commercial traders versus non-commercial and retail traders in the futures market. It is widely used to identify potential market reversals by observing the extremes in trader positioning. Customizable Timeframe: The indicator allows you to choose a custom time interval (in months) to visualize the COT data, making it flexible to fit different trading styles and strategies. How to Use: Visualize Market Sentiment: A COT Index near extremes (close to 0 or 100) can indicate potential turning points in the market, as it reflects extreme positioning of different market participant groups. Adjust the Time Interval: The ability to adjust the time interval (in months) gives traders the flexibility to analyze the market over different periods, which can be useful in detecting longer-term trends or short-term shifts in sentiment. Combine with Other Indicators: To enhance your analysis, combine the COT Index with your technical analysis. This tool can serve as an invaluable addition to your trading strategy, providing a deeper understanding of the market dynamics and the positioning of major market participants.
Pine Script®指標
由NocTrading提供
1
Doganayy2 Buy/Sell & liquidityTrap🔧 User-Changeable Settings and Their Meanings 1. ✅ Is Wick Filter Active? What does it do?: Controls the length of the candle wick. Effect: If active, a long wick is considered a trap (a sign of manipulation). 2. 📊 Is Volume Filter Active? What does it do?: Controls abnormally high volume according to the volume average. Effect: If active, high volume candles are considered for a liquidity trap signal. 3. 📈 Is RSI Filter Active? What does it do?: Controls overbought/oversold according to the RSI level. Effect: If active; If RSI > ?, a long trap is searched. If RSI < ?, a short trap is searched. 4. 🔴🟢 Is Candle Color (Direction) Filter Active? What does it do?: Controls whether the candle is green or red. Effect: If active; A red candle (selling pressure) is required for a long trap. A green candle (buying pressure) is required for a short trap. 5. 🧮 Is Fibonacci Level Filter Active? What does it do?: Checks whether the price has reached important Fibonacci levels. Effect: If active; For a long trap, the price must rise above the Fibo level. For a short trap, the price must fall below the Fibo level. 6. 📏 Is ATR Filter Active? What does it do?: Checks whether there is sufficient deviation in the price according to the ATR. Effect: If active; A trap signal is given according to whether the price has moved too far from the ATR. 📌 As a result: As these filters are activated, the system's long/short trap detection becomes tighter and produces fewer but more reliable signals. If you close the filters, you will receive more signals, but reliability may decrease. Purpose of the indicator: To present buy/sell opportunities by detecting liquidity traps.
Pine Script®指標
由doganayy2提供
PER Bands (Auto EPS)PER Bands Indicator - Technical Specification Function This PineScript v6 overlay indicator displays horizontal price bands based on Price-to-Earnings Ratio multiples. The indicator calculates price levels by multiplying earnings per share values by user-defined PER multiples, then plots these levels as horizontal lines on the chart. Data Sources The script attempts to automatically retrieve earnings per share data using TradingView's `request.financial()` function. The system first queries trailing twelve months EPS data, then annual EPS data if TTM is unavailable. When automatic retrieval fails or returns zero values, the indicator uses manually entered EPS values as a fallback. Configuration Options Users can configure five separate PER multiples (default values: 10x, 15x, 20x, 25x, 30x). Each band supports individual color customization and adjustable line width settings from 1 to 5 pixels. The indicator includes toggles for band visibility and optional fill areas between adjacent bands with 95% transparency. Visual Components The indicator plots five horizontal lines representing different PER valuation levels. Optional fill areas create colored zones between consecutive bands. A data table in the top-right corner displays current EPS source, EPS value, current PER ratio, and calculated price levels for each configured multiple. Calculation Method The indicator performs the following calculations: - Band Price = Current EPS × PER Multiple - Current PER = Current Price ÷ Current EPS These calculations update on each bar close using the most recent available EPS data. Alert System The script includes alert conditions for price crossovers above the lowest PER band and crossunders below the highest PER band. Additional alert conditions can be configured for any band level through the alert creation interface. Debug Features Debug mode displays character markers on the chart indicating when TTM or annual EPS data is available. This feature helps users verify which data source the indicator is using for calculations. Data Requirements The indicator requires positive, non-zero EPS values to function correctly. Stocks with negative earnings or zero EPS will display "N/A" for current PER calculations, though bands will still plot using the manual EPS input value. Exchange Compatibility Automatic EPS data availability varies by exchange. United States equity markets typically provide comprehensive fundamental data coverage. International markets may have limited automatic data availability, requiring manual EPS input for accurate calculations. Technical Limitations The indicator cannot fetch real-time EPS updates and relies on TradingView's fundamental data refresh schedule. Historical EPS changes are not reflected in past band positions, as the indicator uses current EPS values for all historical calculations. Display Settings The information table shows EPS source type (TTM Auto, Annual Auto, Manual, or Manual Fallback), allowing users to verify data accuracy. The table refreshes only on the last bar to optimize performance and reduce computational overhead. Code Structure Built using PineScript v6 syntax with proper scope management for plot and fill functions. The script uses global scope for all plot declarations and conditional logic within plot parameters to handle visibility settings. Version Requirements This indicator requires TradingView Pine Script version 6 or later due to the use of `request.financial()` functions and updated syntax requirements for plot titles and fill operations.
Pine Script®指標
由hungryWhale69029提供