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Bear Market Probability Model# Bear Market Probability Model: A Multi-Factor Risk Assessment Framework The Bear Market Probability Model represents a comprehensive quantitative framework for assessing systemic market risk through the integration of 13 distinct risk factors across four analytical categories: macroeconomic indicators, technical analysis factors, market sentiment measures, and market breadth metrics. This indicator synthesizes established financial research methodologies to provide real-time probabilistic assessments of impending bear market conditions, offering institutional-grade risk management capabilities to retail and professional traders alike. ## Theoretical Foundation ### Historical Context of Bear Market Prediction Bear market prediction has been a central focus of financial research since the seminal work of Dow (1901) and the subsequent development of technical analysis theory. The challenge of predicting market downturns gained renewed academic attention following the market crashes of 1929, 1987, 2000, and 2008, leading to the development of sophisticated multi-factor models. Fama and French (1989) demonstrated that certain financial variables possess predictive power for stock returns, particularly during market stress periods. Their three-factor model laid the groundwork for multi-dimensional risk assessment, which this indicator extends through the incorporation of real-time market microstructure data. ### Methodological Framework The model employs a weighted composite scoring methodology based on the theoretical framework established by Campbell and Shiller (1998) for market valuation assessment, extended through the incorporation of high-frequency sentiment and technical indicators as proposed by Baker and Wurgler (2006) in their seminal work on investor sentiment. The mathematical foundation follows the general form: Bear Market Probability = Σ(Wi × Ci) / ΣWi × 100 Where: - Wi = Category weight (i = 1,2,3,4) - Ci = Normalized category score - Categories: Macroeconomic, Technical, Sentiment, Breadth ## Component Analysis ### 1. Macroeconomic Risk Factors #### Yield Curve Analysis The inclusion of yield curve inversion as a primary predictor follows extensive research by Estrella and Mishkin (1998), who demonstrated that the term spread between 3-month and 10-year Treasury securities has historically preceded all major recessions since 1969. The model incorporates both the 2Y-10Y and 3M-10Y spreads to capture different aspects of monetary policy expectations. Implementation: - 2Y-10Y Spread: Captures market expectations of monetary policy trajectory - 3M-10Y Spread: Traditional recession predictor with 12-18 month lead time Scientific Basis: Harvey (1988) and subsequent research by Ang, Piazzesi, and Wei (2006) established the theoretical foundation linking yield curve inversions to economic contractions through the expectations hypothesis of the term structure. #### Credit Risk Premium Assessment High-yield credit spreads serve as a real-time gauge of systemic risk, following the methodology established by Gilchrist and Zakrajšek (2012) in their excess bond premium research. The model incorporates the ICE BofA High Yield Master II Option-Adjusted Spread as a proxy for credit market stress. Threshold Calibration: - Normal conditions: < 350 basis points - Elevated risk: 350-500 basis points - Severe stress: > 500 basis points #### Currency and Commodity Stress Indicators The US Dollar Index (DXY) momentum serves as a risk-off indicator, while the Gold-to-Oil ratio captures commodity market stress dynamics. This approach follows the methodology of Akram (2009) and Beckmann, Berger, and Czudaj (2015) in analyzing commodity-currency relationships during market stress. ### 2. Technical Analysis Factors #### Multi-Timeframe Moving Average Analysis The technical component incorporates the well-established moving average convergence methodology, drawing from the work of Brock, Lakonishok, and LeBaron (1992), who provided empirical evidence for the profitability of technical trading rules. Implementation: - Price relative to 50-day and 200-day simple moving averages - Moving average convergence/divergence analysis - Multi-timeframe MACD assessment (daily and weekly) #### Momentum and Volatility Analysis The model integrates Relative Strength Index (RSI) analysis following Wilder's (1978) original methodology, combined with maximum drawdown analysis based on the work of Magdon-Ismail and Atiya (2004) on optimal drawdown measurement. ### 3. Market Sentiment Factors #### Volatility Index Analysis The VIX component follows the established research of Whaley (2009) and subsequent work by Bekaert and Hoerova (2014) on VIX as a predictor of market stress. The model incorporates both absolute VIX levels and relative VIX spikes compared to the 20-day moving average. Calibration: - Low volatility: VIX < 20 - Elevated concern: VIX 20-25 - High fear: VIX > 25 - Panic conditions: VIX > 30 #### Put-Call Ratio Analysis Options flow analysis through put-call ratios provides insight into sophisticated investor positioning, following the methodology established by Pan and Poteshman (2006) in their analysis of informed trading in options markets. ### 4. Market Breadth Factors #### Advance-Decline Analysis Market breadth assessment follows the classic work of Fosback (1976) and subsequent research by Brown and Cliff (2004) on market breadth as a predictor of future returns. Components: - Daily advance-decline ratio - Advance-decline line momentum - McClellan Oscillator (Ema19 - Ema39 of A-D difference) #### New Highs-New Lows Analysis The new highs-new lows ratio serves as a market leadership indicator, based on the research of Zweig (1986) and validated in academic literature by Zarowin (1990). ## Dynamic Threshold Methodology The model incorporates adaptive thresholds based on rolling volatility and trend analysis, following the methodology established by Pagan and Sossounov (2003) for business cycle dating. This approach allows the model to adjust sensitivity based on prevailing market conditions. Dynamic Threshold Calculation: - Warning Level: Base threshold ± (Volatility × 1.0) - Danger Level: Base threshold ± (Volatility × 1.5) - Bounds: ±10-20 points from base threshold ## Professional Implementation ### Institutional Usage Patterns Professional risk managers typically employ multi-factor bear market models in several contexts: #### 1. Portfolio Risk Management - Tactical Asset Allocation: Reducing equity exposure when probability exceeds 60-70% - Hedging Strategies: Implementing protective puts or VIX calls when warning thresholds are breached - Sector Rotation: Shifting from growth to defensive sectors during elevated risk periods #### 2. Risk Budgeting - Value-at-Risk Adjustment: Incorporating bear market probability into VaR calculations - Stress Testing: Using probability levels to calibrate stress test scenarios - Capital Requirements: Adjusting regulatory capital based on systemic risk assessment #### 3. Client Communication - Risk Reporting: Quantifying market risk for client presentations - Investment Committee Decisions: Providing objective risk metrics for strategic decisions - Performance Attribution: Explaining defensive positioning during market stress ### Implementation Framework Professional traders typically implement such models through: #### Signal Hierarchy: 1. Probability < 30%: Normal risk positioning 2. Probability 30-50%: Increased hedging, reduced leverage 3. Probability 50-70%: Defensive positioning, cash building 4. Probability > 70%: Maximum defensive posture, short exposure consideration #### Risk Management Integration: - Position Sizing: Inverse relationship between probability and position size - Stop-Loss Adjustment: Tighter stops during elevated risk periods - Correlation Monitoring: Increased attention to cross-asset correlations ## Strengths and Advantages ### 1. Comprehensive Coverage The model's primary strength lies in its multi-dimensional approach, avoiding the single-factor bias that has historically plagued market timing models. By incorporating macroeconomic, technical, sentiment, and breadth factors, the model provides robust risk assessment across different market regimes. ### 2. Dynamic Adaptability The adaptive threshold mechanism allows the model to adjust sensitivity based on prevailing volatility conditions, reducing false signals during low-volatility periods and maintaining sensitivity during high-volatility regimes. ### 3. Real-Time Processing Unlike traditional academic models that rely on monthly or quarterly data, this indicator processes daily market data, providing timely risk assessment for active portfolio management. ### 4. Transparency and Interpretability The component-based structure allows users to understand which factors are driving risk assessment, enabling informed decision-making about model signals. ### 5. Historical Validation Each component has been validated in academic literature, providing theoretical foundation for the model's predictive power. ## Limitations and Weaknesses ### 1. Data Dependencies The model's effectiveness depends heavily on the availability and quality of real-time economic data. Federal Reserve Economic Data (FRED) updates may have lags that could impact model responsiveness during rapidly evolving market conditions. ### 2. Regime Change Sensitivity Like most quantitative models, the indicator may struggle during unprecedented market conditions or structural regime changes where historical relationships break down (Taleb, 2007). ### 3. False Signal Risk Multi-factor models inherently face the challenge of balancing sensitivity with specificity. The model may generate false positive signals during normal market volatility periods. ### 4. Currency and Geographic Bias The model focuses primarily on US market indicators, potentially limiting its effectiveness for global portfolio management or non-USD denominated assets. ### 5. Correlation Breakdown During extreme market stress, correlations between risk factors may increase dramatically, reducing the model's diversification benefits (Forbes and Rigobon, 2002). ## References Akram, Q. F. (2009). Commodity prices, interest rates and the dollar. Energy Economics, 31(6), 838-851. Ang, A., Piazzesi, M., & Wei, M. (2006). What does the yield curve tell us about GDP growth? Journal of Econometrics, 131(1-2), 359-403. Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The Journal of Finance, 61(4), 1645-1680. Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593-1636. Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. The Quarterly Journal of Economics, 116(1), 261-292. Beckmann, J., Berger, T., & Czudaj, R. (2015). Does gold act as a hedge or a safe haven for stocks? A smooth transition approach. Economic Modelling, 48, 16-24. Bekaert, G., & Hoerova, M. (2014). The VIX, the variance premium and stock market volatility. Journal of Econometrics, 183(2), 181-192. Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764. Brown, G. W., & Cliff, M. T. (2004). Investor sentiment and the near-term stock market. Journal of Empirical Finance, 11(1), 1-27. Campbell, J. Y., & Shiller, R. J. (1998). Valuation ratios and the long-run stock market outlook. The Journal of Portfolio Management, 24(2), 11-26. Dow, C. H. (1901). Scientific stock speculation. The Magazine of Wall Street. Estrella, A., & Mishkin, F. S. (1998). Predicting US recessions: Financial variables as leading indicators. Review of Economics and Statistics, 80(1), 45-61. Fama, E. F., & French, K. R. (1989). Business conditions and expected returns on stocks and bonds. Journal of Financial Economics, 25(1), 23-49. Forbes, K. J., & Rigobon, R. (2002). No contagion, only interdependence: measuring stock market comovements. The Journal of Finance, 57(5), 2223-2261. Fosback, N. G. (1976). Stock market logic: A sophisticated approach to profits on Wall Street. The Institute for Econometric Research. Gilchrist, S., & Zakrajšek, E. (2012). Credit spreads and business cycle fluctuations. American Economic Review, 102(4), 1692-1720. Harvey, C. R. (1988). The real term structure and consumption growth. Journal of Financial Economics, 22(2), 305-333. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. Magdon-Ismail, M., & Atiya, A. F. (2004). Maximum drawdown. Risk, 17(10), 99-102. Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175-220. Pagan, A. R., & Sossounov, K. A. (2003). A simple framework for analysing bull and bear markets. Journal of Applied Econometrics, 18(1), 23-46. Pan, J., & Poteshman, A. M. (2006). The information in option volume for future stock prices. The Review of Financial Studies, 19(3), 871-908. Taleb, N. N. (2007). The black swan: The impact of the highly improbable. Random House. Whaley, R. E. (2009). Understanding the VIX. The Journal of Portfolio Management, 35(3), 98-105. Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research. Zarowin, P. (1990). Size, seasonality, and stock market overreaction. Journal of Financial and Quantitative Analysis, 25(1), 113-125. Zweig, M. E. (1986). Winning on Wall Street. Warner Books.
Pine Script® göstergesi
EdgeTools tarafından
17
Uptrick: Asset Rotation SystemOverview The Uptrick: Asset Rotation System is a high-level performance-based crypto rotation tool. It evaluates the normalized strength of selected assets and dynamically simulates capital rotation into the strongest asset while optionally sidestepping into cash when performance drops. Built to deliver an intelligent, low-noise view of where capital should move, this system is ideal for traders focused on strength-driven allocation without relying on standard technical indicators. Purpose The purpose of this tool is to identify outperforming assets based strictly on relative price behavior and automatically simulate how a portfolio would evolve if it consistently moved into the strongest performer. By doing so, it gives users a realistic and dynamic model for capital optimization, making it especially suitable during trending markets and major crypto cycles. Additionally, it includes an optional safety fallback mechanism into cash to preserve capital during risk-off conditions. Originality This system stands out due to its strict use of normalized performance as the only basis for decision-making. No RSI, no MACD, no trend oscillators. It does not rely on any traditional indicator logic. The rotation logic depends purely on how each asset is performing over a user-defined lookback period. There is a single optional moving average filter, but this is used internally for refinement, not for entry or exit logic. The system’s intelligence lies in its minimalism and precision — using normalized asset scores to continuously rotate capital with clarity and consistency. Inputs General Normalization Length: Defines how many bars are used to calculate each asset’s normalized score. This score is used to compare asset performance. Visuals: Selects between Equity Curve (show strategy growth over time) or Asset Performance (compare asset strength visually). Detect after bar close: Ensures changes only happen after a candle closes (for safety), or allows bar-by-bar updates for quicker reactions. Moving Average Used internally for optional signal filtering. MA Type: Lets you choose which moving average type to use (EMA, SMA, WMA, RMA, SMMA, TEMA, DEMA, LSMA, EWMA, SWMA). MA Length: Sets how many bars the moving average should calculate over. Use MA Filter: Turns the filter on or off. It doesn’t affect the signal directly — just adds a layer of control. Backtest Used to simulate equity tracking from a chosen starting point. All calculations begin from the selected start date. Prior data is ignored for equity tracking, allowing users to isolate specific market cycles or testing periods. Starting Day / Month / Year: The exact day the strategy starts tracking equity. Initial Capital $: The amount of simulated starting capital used for performance calculation. Rotation Assets Each asset has 3 controls: Enable: Include or exclude this asset from the rotation engine. Symbol: The ticker for the asset (e.g., BINANCE:BTCUSDT). Color: The color for visualization (labels, plots, tables). Assets supported by default: BTC, ETH, SOL, XRP, BNB, NEAR, PEPE, ADA, BRETT, SUI Cash Rotation Normalization Threshold USDC: If all assets fall below this threshold, the system rotates into cash. Symbol & Color: Sets the cash color for plots and tables. Customization Dynamic Label Colors: Makes labels change color to match the current asset. Enable Asset Label: Plots asset name labels on the chart. Asset Table Position: Choose where the key asset usage table appears. Performance Table Position: Choose where the backtest performance table appears. Enable Realism: Enables slippage and fee simulation for realistic equity tracking. Adjusted profit is shown in the performance table. Equity Styling Show Equity Curve (STYLING): Toggles an extra-thick visual equity curve. Background Color: Adds a soft background color that matches the current asset. Features Dual Visualization Modes The script offers two powerful modes for real-time visual insights: Equity Curve Mode: Simulates the growth of a portfolio over time using dynamic asset rotation. It visually tracks capital as it moves between outperforming assets, showing compounded returns and the current allocation through both line plots and background color. Asset Performance Mode: Displays the normalized performance of all selected assets over the chosen lookback period. This mode is ideal for comparing relative strength and seeing how different coins perform in real-time against one another, regardless of price level. Multi-Asset Rotation Logic You can choose up to 10 unique assets, each fully customizable by symbol and color. This allows full flexibility for different strategies — whether you're rotating across majors like BTC, ETH, and SOL, or including meme tokens and stablecoins. You decide the rotation universe. If none of the selected assets meet the strength threshold, the system automatically moves to cash as a protective fallback. Key Asset Selection Table This on-screen table displays how frequently each enabled asset was selected as the top performer. It updates in real time and can help traders understand which assets the system has historically favored. Asset Name: Shortened for readability Color Box: Visual color representing the asset % Used: How often the asset was selected (as a percentage of strategy runtime) This table gives clear insight into historical rotation behavior and asset dominance over time. Performance Comparison Table This second table shows a full backtest vs. chart comparison, broken down into key performance metrics: Backtest Start Date Chart Asset Return (%) – The performance of the asset you’re currently viewing System Return (%) – The equity growth of the rotation strategy Outperformed By – Shows how many times the system beat the chart (e.g., 2.1x) Slippage – Estimated total slippage costs over the strategy Fees – Estimated trading fees based on rotation activity Total Switches – Number of times the system changed assets Adjusted Profit (%) – Final net return after subtracting fees and slippage Equity Curve Styling To enhance visual clarity and aesthetics, the equity curve includes styling options: Custom Thickness Curve: A second stylized line plots a shadow or highlight of the main equity curve for stronger visual feedback Dynamic Background Coloring: The chart background changes color to match the currently held asset, giving instant visual context Realism Mode By enabling Realism, the system calculates estimated: Trading Fees (default 0.1%) Slippage (default 0.05%) These costs are subtracted from the equity curve in real time, and shown in the table to produce an Adjusted Return metric — giving users a more honest and execution-aware picture of system performance. Adaptive Labeling System Each time the asset changes, an on-chart label updates to show: Current Asset Live Equity Value These labels dynamically adjust in color and visibility depending on the asset being held and your styling preferences. Full Customization From visual position settings to table placements and custom asset color coding, the entire system is fully modular. You can move tables around the screen, toggle background visuals, and control whether labels are colored dynamically or uniformly. Key Concepts Normalized values represent how much an asset has changed relative to its past price over a fixed period, allowing performance comparisons across different assets. Outperforming refers to the asset with the highest normalized value at a given time. Cash fallback means the system moves into a stable asset like USDC when no strong performers are available. The equity curve is a running total of simulated capital over time. Slippage is the small price difference between expected and actual trade execution due to market movement. Use Case Flexibility You don’t need to use all 10 assets. The system works just as effectively with only 1 asset — such as rotating between CASH and SOL — for a simple, minimal strategy. This is ideal for more focused portfolios or thematic rotation systems. How to Use the Indicator To use the Uptrick: Asset Rotation System, start by selecting which assets to include and entering their symbols (e.g., BINANCE:BTCUSDT). Choose between Equity Curve mode to see simulated portfolio growth, or Asset Performance mode to compare asset strength. Set your lookback period, backtest start date, and optionally enable the moving average filter or realism settings for slippage and fees. The system will then automatically rotate into the strongest asset, or into cash if no asset meets the strength threshold. Use alerts to be notified when a rotation occurs. Asset Switch Alerts The script includes built-in alert conditions for when the system rotates into a new asset. You can enable these to be notified when the system reallocates to a different coin or to cash. Each alert message is labeled by target asset and can be used for automation or monitoring purposes. Conclusion The Uptrick: Asset Rotation System is a next-generation rotation engine designed to cut through noise and overcomplication. It gives users direct insight into capital strength, without relying on generic indicators. Whether used to track a broad basket or focus on just two assets, it is built for accuracy, adaptability, and transparency — all in real-time. Disclaimer This script is for research and educational purposes only. It is not intended as financial advice. Past performance is not a guarantee of future results. Always consult with a financial professional and evaluate risks before trading or investing.
Pine Script® göstergesi
Uptrick tarafından
GCM Supreme Trading System Pro (With Golden Zone)Okay, bro! Here are some notes on your "GCM Supreme Trading System Pro (Dashboard + RSI)" indicator based on the Pine Script code you provided. Think of this as a breakdown of its components, logic, and how you might use it, along with some things to consider. GCM Supreme Trading System Pro (Dashboard + RSI) - Notes Overall Concept: This indicator aims to provide an "all-in-one" visual dashboard and signal system by combining several technical analysis concepts: Short-Term Trend: Using a fast EMA. Volatility/Channel: High/Low plot with fill. Sentiment: Background color based on price vs. EMA. Price Structure/Pattern: Highlighting potential AMD phases. Key Price Level: Previous day's specific Fibonacci zone (Golden Zone). Momentum: RSI Overbought/Oversold status. Volume Analysis: Identifying volume spikes. Risk Assessment: Based on ATR volatility. Signal Generation: Based on EMA direction change confirmed by candle color. Centralized Summary: A dashboard showing the status of key components. Key Components & How They Work: Trend EMA (Length: 3 by default): What: A very fast Exponential Moving Average of the specified source (close by default). How: Plots the EMA line. Colors the line green if the EMA is moving up, red if moving down, gray if flat. Usage: Provides a very quick view of the immediate price direction and momentum. High/Low Channel Lines & Fill: What: Plots the current bar's high and low. How: The area between the high and low is filled. The fill color changes based on whether the Trend EMA is moving up (green fill), down (red fill), or is neutral (gray fill). Usage: Visualizes the recent price range/volatility and ties it to the immediate trend direction. Sentiment Background: What: Colors the chart background. How: Background is lightly colored green if the close is above the Trend EMA, and red if the close is below the Trend EMA. Usage: Reinforces the current short-term bias based on price's position relative to the fast EMA. AMD Pattern Candles: What: Highlights specific candle patterns often associated with Accumulation, Manipulation, and Distribution phases. How: Accumulation (Aqua): Previous candle was Red, current candle is Green (Red -> Green). Manipulation (Yellow): Previous candle was Green, current candle is Red (Green -> Red). Distribution (Fuchsia): Two consecutive Red candles where the candle before the first Red was Not Red (Not Red -> Red -> Red). Usage: Helps visually spot potential shifts in market behavior according to the AMD concept. Previous Day's Fib Golden Zone (0.55-0.66): What: Calculates a specific Fibonacci zone (between 55% and 66%) based on the previous day's range (High-Low). How: Plots a horizontal box on the chart covering the calculated zone level. Uses the previous day's range direction (Green/Red candle) to determine if the zone is calculated up from the low (Green day) or down from the high (Red day). Usage: Identifies a potential key retracement or support/resistance zone from the previous day's price action that may be relevant for the current day. RSI (Relative Strength Index): What: A classic momentum oscillator. How: Calculates the RSI value based on the specified length and source. The dashboard shows the current value and flags it as Overbought (> OB level), Oversold (< OS level), or Neutral. Usage: Provides context on momentum extremes. High RSI suggests strong upward momentum (potentially overextended), low RSI suggests strong downward momentum (potentially oversold). Volume Spike Confirmation: What: Compares current volume to its Moving Average. How: Calculates a simple moving average of volume. Identifies a "Spike" if the current volume is significantly higher (multiplied by a factor) than the MA. Usage: Provides a contextual check for increased activity accompanying price moves. (Note: In the current script, this is calculated and shown on the dashboard but not directly used in the signal label logic, though it could be added). Risk Assessment (ATR): What: Uses the Average True Range. How: Calculates the ATR for the specified length. Compares the current ATR to a longer-term average ATR. Flags "High Risk" if the current ATR is significantly higher than the average. Usage: Gives an indication of current volatility relative to recent history, which can inform stop-loss placement or position sizing. Signals (Buy/Sell Labels): What: Plots "BUY" or "SELL" labels on the chart. How: BUY Signal: Triggers when the Trend EMA starts moving Up on the previous bar AND the current bar is Green (close > open). SELL Signal: Triggers when the Trend EMA starts moving Down on the previous bar AND the current bar is Red (close < open). Usage: These are your potential entry triggers. They indicate that the fast EMA trend has just changed direction and the current candle is confirming that move with its color. Dashboard: What: A 2x5 table displayed on the chart (bottom right by default). How: Shows the current status of: Trend (Bull/Bear/Neutral) Volume (Spike/Normal) Last Signal (🟢 BUY, 🔴 SELL, or None) Risk (High/Normal based on ATR) RSI (Overbought/Oversold/Neutral + Current Value) Usage: Provides a quick, centralized summary of multiple indicator components without having to visually check every detail on the chart or separate panes. How to Potentially Use It (Example Interpretation): Look for a BUY signal (Green label) when: The dashboard shows "🟢 BUY" as the Last Signal. Consider additional confirmation: Is Volume status "Spike"? Is Risk "Normal"? Is RSI not "Overbought" (or perhaps just coming out of "Oversold" territory)? Is the price above/interacting positively with the Golden Zone? Look for a SELL signal (Red label) when: The dashboard shows "🔴 SELL" as the Last Signal. Consider additional confirmation: Is Volume status "Spike"? Is Risk "Normal"? Is RSI not "Oversold" (or perhaps just coming out of "Overbought" territory)? Is the price below/interacting negatively with the Golden Zone? Use the Sentiment Background and High/Low Channel Fill to quickly see the immediate trend and volatility context. Watch AMD candles around key levels (like the Golden Zone or signal triggers) for potential pattern confirmation. Check the Dashboard frequently for a summary of all these factors, even without a specific signal. Strengths & Potential Benefits: Comprehensive View: Integrates multiple popular trading concepts into a single indicator. Visual Clarity: Uses colors, fills, labels, and a dashboard for easy interpretation. Customizable: Inputs allow tuning the sensitivity of the EMA, Volume, ATR, and RSI to different assets/timeframes. Dashboard Efficiency: Saves time by consolidating key status points. Non-Repainting Signals: The buy/sell labels trigger and stay based on closed bar data. Important Considerations & Limitations: Fast EMA Sensitivity: An EMA length of 3 is very fast and prone to whipsaws, especially in choppy or ranging markets. Signals based solely on this could be frequent and unreliable in non-trending conditions. Signal Logic: The core signal is only based on EMA direction change + candle color. While simple, it might miss opportunities or generate signals without broader market confirmation (like strong volume, favorable RSI position, or reaction at key levels). The dashboard provides these other factors as context, but they aren't required for the signal label in the current code. Golden Zone Reliance: The previous day's Fib zone is just one potential level. It won't always be respected, and its relevance might vary significantly across different markets and timeframes. AMD Patterns: The defined AMD patterns are specific. The market's "real" accumulation/manipulation/distribution might manifest in more complex ways. Dashboard as Summary, Not Signal: Remember the dashboard shows the current status of all components on the last bar, but the BUY/SELL signal labels are based on a specific historical event (previous bar's EMA turn). You need to look at both: the label for the trigger, and the dashboard for the confluence of other factors right now. Not a Standalone System: While called a "Trading System," no single indicator guarantees profitability. This tool provides signals and context, but requires a robust trading plan including stop losses, profit targets, position sizing, and potentially confluence with other analysis methods. Timeframe Dependency: The ideal settings (EMA length, RSI length, etc.) will likely differ significantly between timeframes (e.g., 1-minute vs. 4-hour). Testing and optimization are crucial. In Summary: The "GCM Supreme Trading System Pro (Dashboard + RSI)" is a well-designed indicator that consolidates several useful analysis tools into a single view. Its strength lies in providing quick visual context and a clear signal trigger based on short-term trend shifts. However, like any indicator, it's not perfect. Its effectiveness will largely depend on the market conditions, the chosen settings, and how it's integrated into a comprehensive trading strategy, using the dashboard components as essential confirmation and risk assessment tools alongside the primary signal labels.
Pine Script® göstergesi
uniGram tarafından
2
Uptrick: Dynamic Z-Score DeviationOverview Uptrick: Dynamic Z‑Score Deviation is a trading indicator built in Pine Script that combines statistical filters and adaptive smoothing to highlight potential reversal points in price action. It combines a hybrid moving average, dual Z‑Score analysis on both price and RSI, and visual enhancements like slope‑based coloring, ATR‑based shadow bands, and dynamically scaled reversal signals. Introduction Statistical indicators like Z‑Scores measure how far a value deviates from its average relative to the typical variation (standard deviation). Standard deviation quantifies how dispersed a set of values is around its mean. A Z‑Score of +2 indicates a value two standard deviations above the mean, while -2 is two below. Traders use Z‑Scores to spot unusually high or low readings that may signal overbought or oversold conditions. Moving averages smooth out price data to reveal trends. The Arnaud Legoux Moving Average (ALMA) reduces lag and noise through weighted averaging. A Zero‑Lag EMA (approximated here using a time‑shifted EMA) seeks to further minimize delay in following price. The RSI (Relative Strength Index) is a momentum oscillator that measures recent gains against losses over a set period. ATR (Average True Range) gauges market volatility by averaging the range between high and low over a lookback period. Shadow bands built using ATR give a visual mood of volatility around a central trend line. Together, these tools inform a dynamic but statistically grounded view of market extremes. Purpose The main goal of this indicator is to help traders spot short‑term reversal opportunities on lower timeframes. By requiring both price and momentum (RSI) to exhibit statistically significant deviations from their norms, it filters out weak setups and focuses on higher‑probability mean‑reversion zones. Reversal signals appear when price deviates far enough from its hybrid moving average and RSI deviates similarly in the same direction. This makes it suitable for discretionary traders seeking clean entry cues in volatile environments. Originality and Uniqueness Uptrick: Dynamic Z‑Score Deviation distinguishes itself from standard reversal or mean‑reversion tools by combining several elements into a single framework: A composite moving average (ALMA + Zero‑Lag EMA) for a smooth yet responsive baseline Dual Z‑Score filters on price and RSI rather than relying on a single measure Adaptive visual elements, including slope‑aware coloring, multi‑layer ATR shadows, and signal sizing based on combined Z‑Score magnitude Most indicators focus on one aspect—price envelopes or RSI thresholds—whereas Uptrick: Dynamic Z‑Score Deviation requires both layers to align before signaling. Its visual design aids quick interpretation without overwhelming the chart. Why these indicators were merged Every component in Uptrick: Dynamic Z‑Score Deviation has a purpose: • ALMA: provides a smooth moving average with reduced lag and fewer false crossovers than a simple SMA or EMA. • Zero‑Lag EMA (ZLMA approximation): further reduces the delay relative to price by applying a time shift to EMA inputs. This keeps the composite MA closer to current price action. • RSI and its EMA filter: RSI measures momentum. Applying an EMA filter on RSI smooths out false spikes and confirms genuine overbought or oversold momentum. • Dual Z‑Scores: computing Z‑Scores on both the distance between price and the composite MA, and on smoothed RSI, ensures that signals only fire when both price and momentum are unusually stretched. • ATR bands: using ATR‑based shadow layers visualizes volatility around the MA, guiding traders on potential support and resistance zones. At the end, these pieces merge into a single indicator that detects statistically significant mean reversions while staying adaptive to real‑time volatility and momentum. Calculations 1. Compute ALMA over the chosen MA length, offset, and sigma. 2. Approximate ZLMA by applying EMA to twice the price minus the price shifted by the MA length. 3. Calculate the composite moving average as the average of ALMA and ZLMA. 4. Compute raw RSI and smooth it with ALMA. Apply an EMA filter to raw RSI to reduce noise. 5. For both price and smoothed RSI, calculate the mean and standard deviation over the Z‑Score lookback period. 6. Compute Z‑Scores: • z_price = (current price − composite MA mean) / standard deviation of price deviations • z_rsi = (smoothed RSI − mean RSI) / standard deviation of RSI 7. Determine reversal conditions: both Z‑Scores exceed their thresholds in the same direction, RSI EMA is in oversold/overbought zones (below 40 or above 60), and price movement confirms directionality. 8. Compute signal strength as the sum of the absolute Z‑Scores, then classify into weak, medium, or strong. 9. Calculate ATR over the chosen period and multiply by layer multipliers to form shadow widths. 10.Derive slope over the chosen slope length and color the MA line and bars based on direction, optionally smoothing color transitions via EMA on RGB channels. How this indicator actually works 1. The script begins by smoothing price data with ALMA and approximating a zero‑lag EMA, then averaging them for the main MA. 2. RSI is calculated, then smoothed and filtered. 3. Using a rolling window, the script computes statistical measures for both price deviations and RSI. 4. Z‑Scores tell how far current values lie from their recent norms. 5. When both Z‑Scores cross configured thresholds and momentum conditions align, reversal signals are flagged. 6. Signals are drawn with size and color reflecting strength. 7. The MA is plotted with dynamic coloring; ATR shadows are layered beneath to show volatility envelopes. 8. Bars can be colored to match MA slope, reinforcing trend context. 9. Alert conditions allow automated notifications when signals occur. Inputs Main Length: Main MA Length. Sets the period for ALMA and ZLMA. RSI Length: RSI Length. Determines the lookback for momentum calculations. Z-Score Lookback: Z‑Score Lookback. Window for mean and standard deviation computations. Price Z-Score Threshold: Price Z‑Score Threshold. Minimum deviation required for price. RSI Z-Score threshold: RSI Z‑Score Threshold. Minimum deviation required for momentum. RSI EMA Filter Length: RSI EMA Filter Length. Smooths raw RSI readings. ALMA Offset: Controls ALMA’s focal point in the window. ALMA Sigma: Adjusts ALMA’s smoothing strength. Show Reversal Signals : Toggle to display reversal signal markers. Slope Sensitivity: Length for slope calculation. Higher values smooth slope changes. Use Bar Coloring: Enables coloring of price bars based on MA slope. Show MA Shadow: Toggle for ATR‑based shadow bands. Shadow Layer Count: Number of shadow layers (1–4). Base Shadow ATR Multiplier: Multiplier for ATR when sizing the first band. Smooth Color Transitions (boolean): Smooths RGB transitions for line and shadows, if enabled. ATR Length for Shadow: ATR Period for computing volatility bands. Use Dynamic Signal Size: Toggles dynamic scaling of reversal symbols. Features Moving average smoothing: a hybrid of ALMA and Zero‑Lag EMA that balances responsiveness and noise reduction. Slope coloring: MA line and optionally price bars change color based on trend direction; color transitions can be smoothed for visual continuity. ATR shadow layers: translucent bands around the MA show volatility envelopes; up to four concentric layers help gauge distance from normal price swings. Dual Z‑Score filters: price and momentum must both deviate beyond thresholds to trigger signals, reducing false positives. Dynamic signal sizing: reversal markers scale in size based on the combined Z‑Score magnitude, making stronger signals more prominent. Adaptive visuals: optional smoothing of color channels creates gradient effects on lines and fills for a polished look. Alert conditions: built‑in buy and sell alerts notify traders when reversal setups emerge. Conclusion Uptrick: Dynamic Z‑Score Deviation delivers a structured way to identify short‑term reversal opportunities by fusing statistical rigor with adaptive smoothing and clear visual cues. It guides traders through multiple confirmation layers—hybrid moving average, dual Z‑Score analysis, momentum filtering, and volatility envelopes—while keeping the chart clean and informative. Disclaimer This indicator is provided for informational and educational purposes only and does not constitute financial advice. Trading carries risk and may not be suitable for all participants. Past performance is not indicative of future results. Always do your own analysis and risk management before making trading decisions.
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Uptrick tarafından
Compare Strength with SLOPE Description This indicator compares the relative strength between the current asset and a benchmark (e.g., BTC vs. ETH or AAPL vs. SPY) using a linear regression slope of their ratio over time. The ratio is calculated as: close / benchmark A linear regression slope is computed over a user-defined window The slope represents trend strength: if it’s rising, the current asset is outperforming the benchmark Plots Gray Line: The raw ratio between the asset and benchmark Orange Line: The slope of the ratio (shows momentum) Background Color : Green: The asset is significantly stronger than the benchmark Red: The asset is significantly weaker than the benchmark No color: No clear trend Settings Slope Window Length: Number of candles used in the regression (default = 10) Slope Threshold: Sensitivity of trend detection. Smaller values detect weaker trends. Example Use Cases Style Rotation Strategy: Use the slope to determine whether "Growth" or "Value" style is leading. Pair Trading / Relative Performance: Track which asset is leading in a pair (e.g., BTC vs ETH). Factor Timing: Serve as a timing model to allocate between different sectors or factors. Happy trading!
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martinivon tarafından
[blackcat] L3 Dark Horse OscillatorOVERVIEW The L3 Dark Horse Oscillator is a sophisticated technical indicator meticulously crafted to offer traders deep insights into market momentum. By leveraging advanced calculations involving Relative Strength Value (RSV) and proprietary oscillatory techniques, this script provides clear and actionable signals for identifying potential buying and selling opportunities. Its distinctive feature—a vibrant gradient color scheme—enhances readability and makes it easier to visualize trends and reversals on the chart 📈↗️. FEATURES Advanced Calculation Methods: Utilizes complex algorithms to compute the Relative Strength Value (RSV) over specific periods, providing a nuanced view of price movements. Default Period: 27 bars for initial RSV calculation. Additional Period: 36 bars for extended RSV analysis. Dual-Oscillator Components: Component A: Derived using multiple layers of Simple Moving Averages (SMAs) applied to the RSV, offering a smoothed representation of short-term momentum. Component B: Employs a unique averaging method tailored to capture medium-term trends effectively. Dynamic Gradient Color Scheme: Enhances visualization through a spectrum of colors that change dynamically based on the calculated values, making trend identification intuitive and engaging 🌈. Customizable Horizontal Reference Lines: Key levels are marked at 0, 10, 50, and 90 to serve as benchmarks for assessing the oscillator's readings, helping traders make informed decisions quickly. Comprehensive Visual Representation: Combines the strengths of both components into a single, gradient-colored candlestick plot, providing a holistic view of market sentiment and momentum shifts 📊. HOW TO USE Adding the Indicator: Start by adding the L3 Dark Horse Oscillator to your TradingView chart via the indicators menu. This will overlay the necessary plots directly onto your price chart. Interpreting the Components: Familiarize yourself with the two primary components represented by yellow and fuchsia lines. These lines indicate the underlying momentum derived from the RSV calculations. Monitoring Momentum Shifts: Pay close attention to the gradient-colored candlesticks, which reflect the combined strength of both components. Notice how these candles transition through various shades, signaling changes in market dynamics. Utilizing Reference Levels: Leverage the horizontal lines at 0, 10, 50, and 90 as critical thresholds. For instance, values above 50 might suggest bullish conditions, while those below could hint at bearish tendencies. Combining with Other Tools: To enhance reliability, integrate this indicator with complementary technical analyses such as moving averages, volume profiles, or other oscillators like RSI or MACD. LIMITATIONS Market Volatility: In extremely volatile or sideways-trending markets, the indicator might produce false signals due to erratic price movements. Always cross-reference with broader market contexts. Testing Required: Before deploying the indicator in real-time trading, conduct thorough backtesting across diverse assets and timeframes to understand its performance characteristics fully. Asset-Specific Performance: The efficacy of the L3 Dark Horse Oscillator can differ significantly across various financial instruments and market conditions. Tailor your strategies accordingly. NOTES Historical Data: Ensure ample historical data availability to facilitate precise calculations and avoid inaccuracies stemming from insufficient data points. Parameter Adjustments: Experiment with adjusting the default periods (27 and 36 bars) if you find them unsuitable for your specific trading style or market conditions. Visual Customization: Modify the appearance settings, including line styles and gradient colors, to better suit personal preferences without compromising functionality. Risk Management: While the indicator offers valuable insights, always adhere to robust risk management practices to safeguard against unexpected market fluctuations. EXAMPLE STRATEGIES Trend Following: Use the oscillator to confirm existing trends. When Component A crosses above Component B, consider entering long positions; conversely, look for short entries during downward crossovers. Mean Reversion: Identify extreme readings near the upper (90) or lower (10) bands where prices might revert to mean levels, presenting potential reversal opportunities. Divergence Analysis: Compare the oscillator's behavior with price action to spot divergences, which often precede trend reversals. Bullish divergence occurs when prices make lower lows but the oscillator shows higher lows, suggesting upward momentum.
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blackcat1402 tarafından
CAM | Currency Strength PerformanceOverview 📊 The "CAM | Currency Strength Performance" indicator is a powerful forex trading tool that blends traditional composite analysis with dynamic performance tracking! 🚀 It compares the strength of a currency pair’s base and quote currencies against the pair’s price movement, offering traders a clear, colorful view of market dynamics through normalized lines and an upgraded strength-based histogram. 🎨 How It Works 🛠️ 🔍 Automatic Currency Detection: Instantly identifies the base (e.g., XAU in XAUUSD) and quote (e.g., USD) currencies—no setup required! 📈 Composite Strength Calculation: Measures each currency’s power by averaging its exchange rate against a basket of 10 major currencies (GBP, EUR, CHF, USD, AUD, CAD, NZD, JPY, NOK, XAU). A classic strength snapshot! 💪 📏 Normalization: Scales composites and pair prices with a smart formula (price minus moving average, divided by standard deviation) for easy comparison. ⚖️ 🎨 Dynamic Visualization: Plots 3 normalized lines with unique colors: Base Composite Quote Composite Actual Pair (⚪ white) Benefits 🌈 🧠 Simplified Analysis: Normalized composites make static strength clear, while the new histogram reveals dynamic trends. ✅ Enhanced Decisions: Color-coded lines and a performance-driven histogram pinpoint trading opportunities fast—spot when base or quote takes the lead! 🚨 ⏱️ Time-Saver: Auto-detection and dual metrics (static + dynamic) streamline your workflow. 🌍 Versatile: Works across all supported pairs, with colors adapting to currencies (e.g., orange AUD, yellow XAU). 👀 Eye-Catching: Vibrant visuals (purple GBP, green USD) and a purple histogram make it engaging and intuitive. How It Helps Traders 💡 📈 Spot Trends: Normalized lines show steady strength; the histogram tracks recent outperformance—perfect for timing trades. ⚠️ Catch Divergences: See when strength shifts (e.g., base surging, quote lagging) don’t match price—hello, reversal signals! 🔍 🛡️ Manage Risk: Levels (1, -1) and histogram swings help gauge overbought/oversold conditions for smarter stops. 🔮 Big Picture: Combines static strength with dynamic momentum, giving a fuller market view for scalping or long-term strategies. Conclusion ✨ "CAM | Currency Strength Performance" now fuses classic strength analysis with real-time performance tracking. With its upgraded histogram, traders get a dual lens—static composites plus dynamic strength—turning complex forex data into actionable insights! 📈💰 Mar 11 Release Notes ✨ New Feature: Strength Histogram: Tracks the performance of base and quote currencies over a customizable lookback period (default: 10 bars). 📅 Calculates strength as the currency’s percentage change minus the basket’s average change, then plots the difference (base - quote) as a purple histogram. 📊 ⚙️ Customizable Settings: Adjust Scaling Period (50), Histogram Scale Factor (0.5), Lookback Bars (10), and Levels (1, -1) to fit your trading style! 🎚️ How It Differs from the Previous Version 🔄 Old Histogram: Showed the static difference between normalized base and quote composites—a snapshot of relative strength at a single point in time. 📷 Focused on current exchange rate levels, scaled by the pair’s normalized price movement. New Histogram: Displays the dynamic strength difference (base strength - quote strength) over a user-defined lookback period (e.g., 10 bars). 🌊 Measures past and current performance by calculating percentage changes relative to a basket, highlighting momentum and trends. 📈 Offers a more responsive, time-based view, showing how each currency has performed recently rather than just its absolute strength.
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CAPRICORN-ASSETS tarafından
RSI and CCICombined RSI and CCI Indicator for MetaTrader The Combined RSI and CCI Indicator is a powerful hybrid momentum oscillator designed to merge the strengths of two popular indicators—the Relative Strength Index (RSI) and the Commodity Channel Index (CCI)—into a single, visually intuitive chart window. This tool enhances traders’ ability to identify overbought and oversold conditions, divergences, trend strength, and potential reversal zones with improved precision. Purpose By integrating RSI and CCI, this indicator helps filter out false signals that often occur when using each tool independently. It is especially useful for swing trading, trend confirmation, and spotting high-probability entry/exit zones. This dual-oscillator approach combines RSI’s relative momentum insights with CCI’s deviation-based analysis to produce a more reliable signal structure. Key Features Dual Oscillator Display: Plots both RSI and CCI on the same subwindow for easy comparison and correlation analysis. Customizable Parameters: RSI Period and Level (default: 14) CCI Period and Typical Price Type (default: 20, TP) Overbought/Oversold Levels for both indicators Color-Coded Zones: Background highlights when both RSI and CCI enter overbought/oversold territory, signaling high potential reversal zones. Combined Signal Logic (Optional Feature): Buy Signal: RSI < 30 and CCI < -100 Sell Signal: RSI > 70 and CCI > 100 These can be visualized as arrows or plotted as signal markers. Trend Filter Overlay (Optional): Can be combined with a moving average or price action filter to confirm trend direction before accepting signals. Divergence Detection (Advanced Option): Optional plotting of bullish or bearish divergence where both indicators diverge from price action. Multi-Timeframe Compatibility: Allows the use of higher timeframe RSI/CCI values to confirm signals on lower timeframes. Benefits Improved Signal Accuracy: Using both RSI and CCI together helps avoid false breakouts and whipsaws. More Informed Decision-Making: Correlating momentum (RSI) with deviation (CCI) provides a well-rounded picture of market behavior. Efficient Charting: Saves screen space and cognitive load by combining two indicators into one clean panel. Scalable Strategy Integration: Can be used in discretionary trading or coded into automated strategies/alerts. Use Case Example In a ranging market, the indicator highlights zones where both RSI and CCI are oversold, alerting traders to potential bounce opportunities. In trending markets, it confirms trend strength when RSI and CCI are both aligned with trend direction. When RSI is diverging from price but CCI isn’t, it can be a clue of weakening momentum, helping traders scale out or avoid traps. This combined indicator offers a versatile, high-performance toolset for traders looking to elevate their technical analysis by leveraging multiple momentum perspectives simultaneously.
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curiousEggs21247 tarafından
Trend Strength MeterThe Trend Strength Meter (TSM) is a powerful and versatile indicator designed to help traders identify market trends, measure their strength, and detect potential reversals with ease. This indicator combines the power of moving averages, divergence detection, and a clean, customizable dashboard to provide actionable insights for traders of all levels. How It Works Trend Strength Calculation: 1. The TSM calculates the trend strength using the difference between two Exponential Moving Averages (EMAs): a fast EMA (default: 20) and a slow EMA (default: 50). 2. The difference is expressed as a percentage of the slow EMA, providing a clear measure of the trend's strength and direction. Histogram Visualization: 1. A color-coded histogram visually represents the trend strength: Green: Bullish trend Red: Bearish trend Gray: Neutral or no significant trend 2. A smoothed trend strength line (SMA of the trend strength) is also plotted for better clarity. Divergence Detection: 1. The indicator detects bullish and bearish divergences using the RSI (Relative Strength Index) and price action. 2. Bullish Divergence: Price makes a lower low, but RSI makes a higher low, signaling potential upward momentum. 3. Bearish Divergence: Price makes a higher high, but RSI makes a lower high, signaling potential downward momentum. => Divergences are marked with arrows on the chart: Green Arrow: Bullish divergence Red Arrow: Bearish divergence Dashboard: 1. A clean and informative dashboard displays key information: Trend Strength Value: The current strength of the trend Trend Direction: Bullish, Bearish, or Neutral Last Signal: Buy, Sell, or None (based on divergence signals) The dashboard is fully customizable and can be positioned anywhere on the chart (e.g., top-right, bottom-left, center, etc.). Key Features 1. Trend Strength Measurement: Quickly identify the strength and direction of the trend. 2. Divergence Detection: Spot potential reversals before they occur with bullish and bearish divergence signals. 3. Customizable Dashboard: Move the dashboard to your preferred location on the chart for better visibility. 4. User-Friendly Design: Clean visuals and intuitive color coding make it easy to interpret market conditions. 5. Actionable Signals: Provides clear Buy/Sell signals based on divergence, helping traders make informed decisions. How to Use 1. Trend Confirmation: Use the histogram and trend strength value to confirm the current market trend. Green bars indicate a bullish trend, while red bars indicate a bearish trend. 2. Divergence Signals: Look for divergence arrows (green for bullish, red for bearish) to anticipate potential reversals. Combine divergence signals with other technical analysis tools for higher accuracy. 3. Dashboard Insights: Monitor the dashboard for real-time updates on trend strength, direction, and the latest signal. Use the "Last Signal" (Buy/Sell) to validate your trading decisions. 4. Custom Settings: Adjust the EMA lengths and divergence lookback period to suit your trading style and timeframe. Position the dashboard anywhere on the chart for convenience. Best Practices 1. Use the TSM in conjunction with other indicators or price action analysis for confirmation. 2. Test the indicator on different timeframes to find the one that works best for your strategy. 3. Always practice proper risk management when trading. Disclaimer This indicator is a tool to assist in technical analysis and should not be used as a standalone trading strategy. Past performance is not indicative of future results. Always conduct your own research and consult with a financial advisor before making trading decisions.
Pine Script® göstergesi
darshakssc tarafından
alphaJohnny Dynamic RSI IndicatorAlphaJohnny Dynamic RSI Indicator (Dyn RSI) The Dynamic RSI Indicator (Dyn RSI) is a custom Pine Script tool designed for TradingView that aggregates Relative Strength Index (RSI) signals from multiple timeframes to provide a comprehensive view of market momentum. It combines RSI data from Weekly, Daily, 4-hour, 1-hour, and 30-minute intervals, offering traders a flexible and customizable way to analyze trends across different periods. Key Features: Multi-Timeframe RSI Aggregation: Combines RSI signals from user-selected timeframes for a holistic momentum assessment. Dynamic or Equal Weighting: Choose between correlation-based dynamic weights (adjusting based on each timeframe’s correlation with price changes) or equal weights for simplicity. Smoothed Momentum Line: A visually intuitive line that reflects the strength of the aggregate signal, smoothed for clarity. Color-Coded Signal Strength: Dark Green: Strong buy signal Light Green: Weak buy signal Yellow: Neutral Light Red: Weak sell signal Dark Red: Strong sell signal Visual Markers: Large green triangles at the bottom for strong buy signals and red triangles at the top for strong sell signals. How to Use: Apply to Chart: Add the indicator to your TradingView chart (it will appear in a separate pane). Customize Settings: Adjust inputs like RSI period, signal thresholds, included timeframes, weighting method, and smoothing period to fit your trading style. Interpret Signals: Momentum Line: Watch for color changes to gauge market conditions. Triangles: Green at the bottom for strong buy opportunities, red at the top for strong sell opportunities. Notes: The indicator is designed for a separate pane (overlay=false), with triangles positioned relative to the pane’s range. Fine-tune thresholds and weights based on your strategy and the asset being analyzed. The source code is open for modification to suit your needs. This indicator is ideal for traders seeking a multi-timeframe perspective on RSI to identify potential trend reversals and momentum shifts.
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oneAlphaJohnny tarafından
Mswing HommaThe Mswing is a momentum oscillator that calculates the rate of price change over 20 and 50 periods (days/weeks). Apart from quantifying momentum, it can be used for assessing relative strength, sectoral rotation & entry/exit signals. Quantifying Momentum Strength The Mswing's relationship with its EMA (e.g., 5-period or 9-period) is used for momentum analysis: • M Swing >0 and Above EMA: Momentum is positive and accelerating (ideal for entries). • M Swing >0 and Below EMA: Momentum is positive but decelerating (caution). • M Swing <0 and Above EMA: Momentum is negative but improving (watch for reversals). • M Swing <0 and Below EMA: Momentum is negative and worsening (exit or avoid). Relative Strength Scanning (M Score) Sort stocks by their M Swing using TradingView’s Pine scanner. Compare the Mswing scores of indices/sectors to allocate capital to stronger groups (e.g., renewables vs. traditional energy). Stocks with strong Mswing scores tend to outperform during bullish phases, while weak ones collapse faster in downtrends. Entry and Exit Signals Entry: Buy when Mswing crosses above 0 + price breaks key moving averages (50-day SMA). Use Mswing >0 to confirm valid breakouts. Buy dips when Mswing holds above EMA during retracements. Exit: Mswing can be used for exiting a stock in 2 ways: • Sell in Strength: Mswing >4 (overbought). • Sell in Weakness: Mswing <0 + price below 50-day SMA. Multi-Timeframe Analysis • Daily: For swing trades. • Weekly: For trend confirmation. • Monthly: For long-term portfolio adjustments.
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sakatashomma tarafından
4
Uptrick: Portfolio Allocation DiversificationIntro The Uptrick: Portfolio Allocation Diversification script is designed to help traders and investors manage multiple assets simultaneously. It generates signals based on various trading systems, allocates capital using different diversification methods, and displays real-time metrics and performance tables on the chart. The indicator compares active trading strategies with a separate long-term holding (HODL) simulation, allowing you to see how a systematic trading approach stacks up against a simple buy-and-hold strategy. ------------------------------------------------------------------------ Trading System Selection 1. No signals (none) In this mode, the script does not produce bullish or bearish indicators; every asset stays in a neutral stance. This setup is useful if you prefer to observe how capital might be distributed based solely on the chosen diversification method, with no influence from directional signals. 2. rsi – neutral This mode uses an index-based measure of whether an asset appears overbought or oversold. It generates a bearish signal if market conditions point to overbought territory, and a bullish signal if they indicate oversold territory. If neither extreme surfaces, it remains neutral. Some traders apply this in sideways or range-bound conditions, where overbought and oversold levels often hint at possible turning points. It does not specifically account for divergence patterns. 3. rsi – long only In this setting, the system watches for instances where momentum readings strengthen even if the asset’s price is still under pressure or setting new lows. It also considers oversold levels as potential signals for a bullish setup. When such conditions emerge, the script flags a possible move to the upside, ignoring indications that might otherwise suggest a bearish trend. This approach is generally favored by those who want to concentrate exclusively on identifying price recoveries. 4. rsi – short only Here, the script focuses on spotting signs of deteriorating momentum while an asset’s price remains relatively high or attempts further gains. It also checks whether the market is drifting into overbought territory, suggesting a potential decline. Under such conditions, it issues a bearish signal. It provides no bullish alerts, making it particularly suitable for traders who look to take advantage of overvalued scenarios or protect themselves against sudden downward moves. 5. Deviation from fair value Under this system, the script judges how far the current price may have strayed from what is considered typical, taking into account normal fluctuations. If the asset appears to be trading at an unusually low level compared to that reference, it is flagged as bullish. If it seems abnormally high, a bearish signal is issued. This can be applied in various market environments to seek opportunities that arise from perceived mispricing. 6. Percentile channel valuation In this mode, the script determines where an asset's price stands within a historical distribution, highlighting whether it has reached unusually high or low territory compared to its recent past. When the price reaches what is deemed an extreme reading, it may indicate that a reversal is more likely. This approach is often used by traders who watch for statistical outliers and potential reversion to a more typical trading range. 7. ATH valuation This technique involves comparing an asset's current price with its previously recorded peak values. The script then interprets whether the price is positioned so far below the all-time high that it looks discounted, or so close to that high that it could be overextended. Such perspective is favored by market participants who want to see if an asset still has ample room to climb before matching historic extremes, or if it is nearing a possible ceiling. 8. Z-score system Here, the script measures how far above or below a standard reference average an asset's price may be, translated into standardized units. Substantial negative readings can suggest a price that might be unusually weak, prompting a bullish indication, while large positive readings could signal overextension and lead to a bearish call. This method is useful for traders watching for abrupt deviations from a norm that often invite a reversion to more balanced levels. RSI Divergence Period This input is particularly relevant for the RSI - Long Only and RSI - Short Only modes. The period determines how many bars in the past you compare RSI values to detect any divergences. ------------------------------------------------------------------------ Diversification Method Once the script has determined a bullish, bearish, or neutral stance for each asset, it then calculates how to distribute capital among all included assets. The diversification method sets the weighting logic. 1. None Gives each asset an equal weight. For example, if you have five included assets, each might get 20 percent. This is a simple baseline. 2. Risk-Adjusted Expected Return Using Volatility Clustering Emphasizes each asset’s average returns relative to its observed risk or volatility tendencies. Assets that exhibit good risk-adjusted returns combined with moderate or lower volatility may receive higher weights than more volatile or less appealing assets. This helps steer capital toward assets that have historically provided a better ratio of return to risk. 3. Relative Strength Allocates more capital to assets that show stronger price strength compared to a reference (for example, price above a long-term moving average plus a higher RSI). Assets in clear uptrends may be given higher allocations. 4. Trend-Following Indicators Examines trend-based signals, like positive momentum measurements or upward-trending strength indicators, to assign more weight to assets demonstrating strong directional moves. This suits those who prefer to latch onto trending markets. 5. Volatility-Adjusted Momentum Looks for assets that have strong price momentum but relatively subdued volatility. The script tends to reward assets that are trending well yet are not too volatile, aiming for stable upward performance rather than massive swings. 6. Correlation-Based Risk Parity Attempts to weight assets in such a way that the overall portfolio risk is more balanced. Although it is not an advanced correlation matrix approach in a strict sense, it conceptually scales each asset’s weight so no single outlier heavily dominates. 7. Omega Ratio Maximization Gives preference to assets with higher omega ratios. This ratio can be interpreted as the probability-weighted gains versus losses. Assets with a favorable skew are given more capital. 8. Liquidity-Weighted Valuation Considers each asset’s average trading liquidity, such as the combination of volume and price. More liquid assets typically receive a higher allocation because they can be entered or exited with lower slippage. If the trading system signals bullishness, that can further boost the allocation, and if it signals bearishness, the allocation might be set to zero or reduced drastically. 9. Drawdown-Controlled Allocation (DCA) Examines each asset’s maximum drawdown over a recent window. Assets experiencing lighter drawdowns (thus indicating somewhat less downside volatility) receive higher allocations, aiming for a smoother overall equity curve. ------------------------------------------------------------------------ Portfolio and Allocation Settings Portfolio Value Defines how much total capital is available for the strategy-based investment portion. For example, if set to 10,000, then each asset’s monetary allocation is determined by the percentage weighting times 10,000. Use Fixed Allocation When enabled, the script calculates the initial allocation percentages after 50 bars of data have passed. It then locks those percentages for the remainder of the backtest or real-time session. This feature allows traders to test a static weighting scenario to see how it differs from recalculating weights at each bar. ------------------------------------------------------------------------ HODL Simulator The script has a separate simulation that accumulates positions in an asset whenever it appears to be recovering from an undervalued state. This parallel tracking is intended to contrast a simple buy-and-hold approach with the more adaptive allocation methods used elsewhere in the script. HODL Buy Quantity Each time an asset transitions from an undervalued state to a recovery phase, the simulator executes a purchase of a predefined quantity. For example, if set to 0.5 units, the system will accumulate this amount whenever conditions indicate a shift away from undervaluation. HODL Buy Threshold This parameter determines the level at which the simulation identifies an asset as transitioning out of an undervalued state. When the asset moves above this threshold after previously being classified as undervalued, a buy order is triggered. Over time, the performance of these accumulated positions is tracked, allowing for a comparison between this passive accumulation method and the more dynamic allocation strategy. ------------------------------------------------------------------------ Asset Table and Display Settings The script displays data in multiple tables directly on your chart. You can toggle these tables on or off and position them in various corners of your TradingView screen. Asset Info Table Position This table provides key details for each included asset, displaying: Symbol – Identifies the trading pair being monitored. This helps users keep track of which assets are included in the portfolio allocation process. Current Trading Signal – Indicates whether the asset is in a bullish, bearish, or neutral state based on the selected trading system. This assists in quickly identifying which assets are showing potential trade opportunities. Volatility Approximation – Represents the asset’s historical price fluctuations. Higher volatility suggests greater price swings, which can impact risk management and position sizing. Liquidity Estimate – Reflects the asset’s market liquidity, often based on trading volume and price activity. More liquid assets tend to have lower transaction costs and reduced slippage, making them more favorable for active strategies. Risk-Adjusted Return Value – Measures the asset’s returns relative to its risk level. This helps in determining whether an asset is generating efficient returns for the level of volatility it experiences, which is useful when making allocation decisions. 2. Strategy Allocation Table Position Displays how your selected diversification method converts each asset into an allocation percentage. It also shows how much capital is being invested per asset, the cumulative return, standard performance metrics (for example, Sharpe ratio), and the separate HODL return percentage. Symbol – Displays the asset being analyzed, ensuring clarity in allocation distribution. Allocation Percentage – Represents the proportion of total capital assigned to each asset. This value is determined by the selected diversification method and helps traders understand how funds are distributed within the portfolio. Investment Amount – Converts the allocation percentage into a dollar value based on the total portfolio size. This shows the exact amount being invested in each asset. Cumulative Return – Tracks the total return of each asset over time, reflecting how well it has performed since the strategy began. Sharpe Ratio – Evaluates the asset’s return in relation to its risk by comparing excess returns to volatility. A higher Sharpe ratio suggests a more favorable risk-adjusted performance. Sortino Ratio – Similar to the Sharpe ratio, but focuses only on downside risk, making it more relevant for traders who prioritize minimizing losses. Omega Ratio – Compares the probability of achieving gains versus losses, helping to assess whether an asset provides an attractive risk-reward balance. Maximum Drawdown – Measures the largest percentage decline from an asset’s peak value to its lowest point. This metric helps traders understand the worst-case loss scenario. HODL Return Percentage – Displays the hypothetical return if the asset had been bought and held instead of traded actively, offering a direct comparison between passive accumulation and the active strategy. 3. Profit Table If the Profit Table is activated, it provides a summary of the actual dollar-based gains or losses for each asset and calculates the overall profit of the system. This table includes separate columns for profit excluding HODL and the combined total when HODL gains are included. As seen in the image below, this allows users to compare the performance of the active strategy against a passive buy-and-hold approach. The HODL profit percentage is derived from the Portfolio Value input, ensuring a clear comparison of accumulated returns. 4. Best Performing Asset Table Focuses on the single highest-returning or highest-profit asset at that moment. It highlights the symbol, the asset’s cumulative returns, risk metrics, and other relevant stats. This helps identify which asset is currently outperforming the rest. 5. Most Profitable Asset A simpler table that underscores the asset producing the highest absolute dollar profit across the portfolio. ------------------------------------------------------------------------ Multi Asset Selection You can include up to ten different assets (such as BTCUSDT, ETHUSDT, ADAUSDT, and so on) in this script. Each asset has two inputs: one to enable or disable its inclusion, and another to select its trading pair symbol. Once you enable an asset, the script requests the relevant market data from TradingView. ------------------------------------------------------------------------ Uniqness and Features 1. Multiple Data Fetches Each asset is pulled from the chart’s timeframe, along with various metrics such as RSI, volatility approximations, and trend indicators. 2. Various Risk and Performance Metrics The script internally keeps track of different measures, like Sharpe ratio (a measure of average return adjusted for risk), Sortino ratio (which focuses on downside volatility), Omega ratio, and maximum drawdown. These metrics feed into the strategy allocation table, helping you quickly assess the risk-and-return profile of each asset. 3. Real-Time Tables Instead of having to set up complex spreadsheets or external dashboards, the script updates all tables on every new bar. The color schemes in these tables are designed to draw attention to bullish or bearish signals, positive or negative returns, and so forth. 4. HODL Comparison You can visually compare the active strategy’s results to a separate continuous buy-on-dips accumulation strategy. This allows for insight into whether your dynamic approach truly beats a simpler, more patient method. 5. Locking Allocations The Use Fixed Allocation input is convenient for those who want to see how holding a fixed distribution of capital performs over time. It helps in distinguishing between constant rebalancing vs a fixed, set-and-forget style. ------------------------------------------------------------------------ How to use 1. Add the Script to Your Chart Once added, open the settings panel to configure your asset list, choose a trading system, and select the diversification approach. 2. Select Assets Pick up to ten symbols to monitor. Disable any you do not want included. Each included asset is then handled for signals, diversification, and performance metrics. 3. Choose Trading System Decide if you prefer RSI-based signals, a fair-value approach, or a percentile-based method, among others. The script will then flag assets as bullish, bearish, or neutral according to that selection. 4. Pick a Diversification Method For example, you might choose Trend-Following Indicators if you believe momentum stocks or cryptocurrencies will continue their trends. Or you could use the Omega Ratio approach if you want to reward assets that have had a favorable upside probability. 5. Set Portfolio Value and HODL Parameters Enter how much capital you want to allocate in total (for the dynamic strategy) and adjust HODL buy quantities and thresholds as desired. (HODL Profit % is calculated from the Portfolio Value) 6. Inspect the Tables On the chart, the script can display multiple tables showing your allocations, returns, risk metrics, and which assets are leading or lagging. Monitor these to make decisions about capital distribution or see how the strategy evolves. ------------------------------------------------------------------------ Additional Remarks This script aims to simplify multi-asset portfolio management in a single tool. It emphasizes user-friendliness by color-coding the data in tables, so you do not need extra spreadsheets. The script is also flexible in letting you lock allocations or compare dynamic updates. Always remember that no script can guarantee profitable outcomes. Real markets involve unpredictability, and real trading includes fees, slippage, and liquidity constraints not fully accounted for here. The script uses real-time and historical data for demonstration and educational purposes, providing a testing environment for various systematic strategies. Performance Considerations Due to the complexity of this script, users may experience longer loading times, especially when handling multiple assets or using advanced allocation methods. In some cases, calculations may time out if too many settings are adjusted simultaneously. If this occurs, removing and reapplying the indicator to the chart can help reset the process. Additionally, it is recommended to configure inputs gradually instead of adjusting all parameters at once, as excessive changes can extend the script’s loading duration beyond TradingView’s processing limits. ------------------------------------------------------------------------ Originality This script stands out by integrating multiple asset management techniques within a single indicator, eliminating the need for multiple scripts or external portfolio tools. Unlike traditional single-asset strategies, it simultaneously evaluates multiple assets, applies systematic allocation logic, and tracks risk-adjusted performance in real time. The script is designed to function within TradingView’s script limitations while still allowing for complex portfolio simulations, making it an efficient tool for traders managing diverse holdings. Additionally, its combination of systematic trading signals with allocation-based diversification provides a structured approach to balancing exposure across different market conditions. The dynamic interplay between adaptive trading strategies and passive accumulation further differentiates it from conventional strategy indicators that focus solely on directional signals without considering capital allocation. Conclusion Uptrick: Portfolio Allocation Diversification pulls multiple assets into one efficient workflow, where each asset’s signal, volatility, and performance is measured, then assigned a share of capital according to your selected diversification method. The script accommodates both dynamic rebalancing and a locked allocation style, plus an ongoing HODL simulation for passive accumulation comparison. It neatly visualizes the entire process through on-chart tables that are updated every bar. Traders and investors looking for ways to manage multiple assets under one unified framework can explore the different modules within this script to find what suits their style. Users can quickly switch among trading systems, vary the allocation approach, or review side-by-side performance metrics to see which method aligns best with their risk tolerance and market perspective.
Pine Script® göstergesi
Uptrick tarafından
Precious Metals & GSR (Zeiierman)█ Overview The Precious Metals & GSR (Zeiierman) is designed to provide traders and investors with a comprehensive view of the Gold-Silver Ratio (GSR) and other precious metal relationships. This tool helps evaluate the relative strength between different metals by analyzing their price ratios over historical periods, using quantile-based analysis and trend interpretation tables to highlight key insights. The Gold-Silver Ratio (GSR) is a widely utilized metric in precious metals trading, representing the number of silver ounces required to purchase one ounce of gold. Historically, this ratio has fluctuated, providing traders with insights into the relative value of these two metals. By analyzing the GSR, traders can identify potential trading opportunities based on historical patterns and market dynamics. By integrating customizable percentile bands, gradient coloring for performance visualization, and dynamic ratio analysis, this indicator assists in understanding how one metal is performing relative to another, making it useful for trend tracking, risk management, and portfolio allocation. █ How It Works The Precious Metals & GSR Indicator operates by fetching the latest prices of the selected precious metals in the user's chosen currency. It then calculates the ratio between two selected metals (Metal 1 and Metal 2) and analyzes this ratio over a specified period. By computing quantile bands and high/low bands, the indicator provides insights into the historical performance and current standing of the ratio. ⚪ Ratio Calculation The core of this indicator is the metal ratio, calculated by dividing the price of Metal 1 by Metal 2. A rising ratio means Metal 1 is outperforming Metal 2. A falling ratio means Metal 2 is outperforming Metal 1. The indicator automatically retrieves live market prices of Gold, Silver, Platinum, and Palladium to compute the ratio. ⚪ Quantile Ratio Bands The indicator calculates the highest (max) and lowest (min) ratio levels over a user-defined period. It also plots quantile bands at the 10th, 25th, 50th (median), 75th, and 90th percentiles, providing deeper statistical insights into how extreme or average the current ratio is. The median (Q50) acts as a reference level, showing whether the ratio is above or below its historical midpoint. ⚪ Interpretation Table The Ratio Interpretation Table provides a text-based summary of the ratio’s strength. It detects whether Metal 1 is at a historical high, low, or within common ranges. This helps traders and investors make informed decisions on whether the ratio is overextended, mean-reverting, or trending. ⚪ Precious Metals Table Displays live market prices for Gold, Silver, Platinum, and Palladium. Prices are shown in different units (oz, kg, grams, and troy ounces) based on user preferences. A color-coded system highlights price changes, making it easier to track market movements. ⚪ Physical Holding Calculator Users can enter their precious metal holdings to estimate their current value. The system adjusts calculations based on weight, purity (24K, 22K, etc.), and unit of measurement. The holding value is displayed in the selected currency (USD, EUR, GBP, etc.). █ How to Use ⚪ Trend Identification If the ratio is increasing, Metal 1 is gaining strength relative to Metal 2 → Possible Long Position on Metal 1 / Short on Metal 2 If the ratio is decreasing, Metal 2 is gaining strength relative to Metal 1 → Possible Short Position on Metal 1 / Long on Metal 2 ⚪ Mean Reversion Strategy When the ratio reaches the 90th percentile, Metal 1 is historically overextended (expensive) compared to Metal 2. Traders may look to sell Metal 1 and buy Metal 2, expecting the ratio to decline back toward its historical average. Example (Gold/Silver Ratio): If the GSR is above the 90th percentile, gold is very expensive relative to silver, suggesting a potential buying opportunity in silver and/or a selling opportunity in gold. When the ratio reaches the 10th percentile, Metal 1 is historically undervalued (cheap) compared to Metal 2. Traders may look to buy Metal 1 and sell Metal 2, expecting the ratio to rise back toward its historical average. Example (Gold/Silver Ratio): If the GSR is below the 10th percentile, gold is very cheap relative to silver, suggesting a potential buying opportunity in gold and/or a selling opportunity in silver. ⚪ Common Strategy Based on GSR Insights A common approach involves monitoring the ratio for extreme values based on historical data. When the ratio reaches historically high levels, it suggests that gold is expensive relative to silver, potentially indicating a buying opportunity for silver and/or a selling opportunity for gold. Conversely, when the ratio is at historically low levels, silver is expensive relative to gold, suggesting a potential buying opportunity for gold and/or selling opportunity for silver. This mean-reversion strategy relies on the tendency of the GSR to return to its historical average over time. ⚪ Hedging & Portfolio Diversification If Gold is strongly outperforming Silver, investors may shift allocations to balance risk. If Silver is rapidly gaining on Gold, it may indicate increased industrial demand or speculative interest. ⚪ Inflation & Economic Cycles A rising Gold-Silver ratio often correlates with economic downturns and increased risk aversion. A falling Gold-Silver ratio may signal stronger economic growth and higher inflation expectations. █ Settings Precious Metals Table Select which metals to display (Gold, Silver, Platinum, Palladium) Choose measurement units (oz, kg, grams, troy ounces) Ratio Analysis Select Metal 1 & Metal 2 for ratio calculation Set historical length for quantile calculations Interpretation Table Enable automated insights based on ratio levels Physical Holdings Calculator Enter metal weight, purity, and unit Select calculation currency ----------------- Disclaimer The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Pine Script® göstergesi
Zeiierman tarafından
5
Bollinger Bands + RSI [Uncle Sam Trading]The Bollinger Bands + RSI indicator combines two popular technical analysis tools, Bollinger Bands (BB) and the Relative Strength Index (RSI), into a unified framework designed to assess both market volatility and momentum. This indicator provides both visual signals on the chart, and allows you to set alerts. It is intended to help traders identify potential overbought/oversold conditions, trend reversals, and to refine trade entry and exit points. Key Features: Bollinger Bands: The indicator plots Bollinger Bands, which consist of a basis line (typically a 20-period Simple Moving Average), an upper band (basis + 2 standard deviations), and a lower band (basis - 2 standard deviations). The bands dynamically adjust to market volatility, widening during periods of increased volatility and contracting during periods of decreased volatility. Relative Strength Index (RSI): The RSI, a momentum oscillator, is plotted in a separate pane below the price chart. It measures the magnitude of recent price changes to evaluate overbought or oversold conditions in the price of a stock or other asset. Traditional interpretation uses 70 and 30 as overbought and oversold levels, respectively.   Overbought/Oversold Zones Highlighting: This indicator uniquely highlights overbought and oversold zones directly on the price chart based on the RSI values. When the RSI is above the overbought level (default 70), a red-shaded area is displayed. When the RSI is below the oversold level (default 30), a green-shaded area is displayed. These visual cues enhance the identification of potential trend reversals. Buy and Sell Signals: The indicator generates buy signals when the price crosses above the lower Bollinger Band and the RSI is below the oversold level (if the RSI filter is enabled). Sell signals are generated when the price crosses below the upper Bollinger Band and the RSI is above the overbought level (if the RSI filter is enabled). These signals are plotted as green upward-pointing triangles (buy) and red downward-pointing triangles (sell) on the chart. Customizable Parameters: Users can adjust various settings, including: Bollinger Bands Length: The number of periods used to calculate the moving average and standard deviation. Bollinger Bands Standard Deviation: The multiplier used to determine the distance of the upper and lower bands from the basis. RSI Length: The number of periods used to calculate the RSI. RSI Overbought/Oversold Levels: The threshold values that define overbought and oversold conditions for the RSI. Use RSI Filter for Signals: Enable/disable the RSI filter for buy and sell signals. Colors: The colors of the Bollinger Bands, RSI, overbought/oversold levels, and zone highlights can be customized to suit user preferences. Alerts: The indicator supports customizable alerts for various conditions, including: Buy Signal: Triggered when a buy signal is generated. Sell Signal: Triggered when a sell signal is generated. Price Crossed Upper BB: Triggered when the price crosses above the upper Bollinger Band. Price Crossed Lower BB: Triggered when the price crosses below the lower Bollinger Band. RSI Overbought: Triggered when the RSI crosses above the overbought level. RSI Oversold: Triggered when the RSI crosses below the oversold level. How to Use: The Bollinger Bands + RSI indicator can be used in various ways, including: Identifying Potential Trend Reversals: Price crosses above the lower band coupled with an oversold RSI (and highlighted zone) may signal a bullish reversal. Conversely, a price cross below the upper band with an overbought RSI (and highlighted zone) may indicate a bearish reversal. Confirming Trend Strength: In an uptrend, the price may "ride" the upper band, while in a downtrend, it may "ride" the lower band. Exit Signals: Crossing the opposite band while in a trade, particularly with confirming RSI signals, is often used to identify potential exit points. Combined with Other Analysis: This indicator works well in conjunction with other technical analysis tools, such as trend lines, support/resistance levels, chart patterns, and moving average-based strategies. Disclaimer: This indicator is for educational and informational purposes only and should not be considered as financial advice. Trading involves risk, and past performance is not indicative of future results. Always conduct thorough research and consider your risk tolerance before making any trading decisions.
Pine Script® göstergesi
UncleSamTrading tarafından
Futuristic Indicator v3 - Enhanced Glow & Strength MetersTo ensure candles are display by script go to trading view settings and uncheck default Candle, Body and Wick to prevent them from plotting over your modified candles. Futuristic Indicator v3 - Enhanced Glow & Strength Meters: Detailed Breakdown This Modern styled Pine Script indicator is designed to enhance technical analysis by providing a visually striking OLED-style dashboard with multiple market insights. It integrates trend detection, momentum analysis, volatility tracking, and strength meters into a single, streamlined interface for traders. 1️⃣ Customizable Features for Flexibility The indicator offers multiple user-configurable settings, allowing traders to adjust the display based on their trading strategy and preferences. Users can toggle elements such as strength meters, volatility indicators, trend arrows, moving averages, and buy/sell alerts. Additionally, background and candle colors can be customized for better readability. 🔹 Why is this useful? Traders can customize their charts to focus on the data they care about. Reduces chart clutter by allowing users to toggle features on or off. 2️⃣ Trend Detection Using EMAs This indicator detects market trends using two Exponential Moving Averages (EMA): A "Fast" EMA (shorter period) for quick trend shifts. A "Slow" EMA (longer period) to confirm trends. Comparison of the two EMAs determines if the trend is bullish (uptrend) or bearish (downtrend). The indicator colors the trend lines accordingly and adds a trend arrow 📈📉 for quick visual cues. 🔹 Why is this useful? EMA crossovers are widely used to identify trend reversals. Provides clear visual cues for traders to confirm entry & exit points. 3️⃣ RSI-Based Momentum Analysis The indicator integrates the Relative Strength Index (RSI) to gauge market momentum. The momentum value changes color dynamically based on whether it's in bullish (>50) or bearish (<50) territory. 🔹 Why is this useful? RSI helps identify overbought and oversold conditions. Detects trend strength by measuring the speed of price movements. 4️⃣ Bullish & Bearish Strength Meters The indicator quantifies bullish and bearish market strength based on RSI and converts it into a percentage-based meter: Bullish Strength (Long Strength) Bearish Strength (Short Strength) Strength meters are displayed using OLED-styled bars, dynamically changing in real-time. 🔹 Why is this useful? Allows traders to visually gauge market sentiment at a glance. Helps confirm if a trend has strong momentum or is losing strength. 5️⃣ Market Volatility Indicator (ATR-Based) The indicator includes a volatility tracker using the Average True Range (ATR): ATR is scaled up to provide easier readability. Higher ATR values indicate higher market volatility. 🔹 Why is this useful? Helps traders identify potential breakout or consolidation phases. Allows better risk management by understanding price fluctuations. 6️⃣ Trend Strength Calculation The indicator calculates trend strength based on the difference between the EMAs: A higher trend strength value suggests a stronger directional trend. Displayed as a percentage for better clarity. 🔹 Why is this useful? Helps traders differentiate between strong and weak trends. Reduces the likelihood of entering weak or choppy markets. 7️⃣ OLED-Style Dashboard for Market Data A futuristic OLED-styled table is used to display critical market data in a visually appealing way: Trend direction (Bullish/Bearish with an arrow 📈📉). Current price. Momentum value. Strength meters (Bullish/Bearish). Trend strength percentage. Volatility Meter The dashboard uses high-contrast colors and neon glow effects, making it easier to read against dark backgrounds. 🔹 Why is this useful? Provides a centralized view of key trading metrics. Eliminates the need to manually calculate trend strength. 8️⃣ Modern Style Neon Glow Effects To enhance visibility, the indicator applies glowing effects to: Moving Averages (EMAs): Highlighted with layered glow effects. Candlesticks: Borders and wicks dynamically change color based on trend direction. 🔹 Why is this useful? Improves readability in low-contrast or dark-mode charts. Helps traders spot trends faster without reading numerical data. 9️⃣ Automated Buy & Sell Alerts The script triggers alerts when momentum crosses key levels: Above 55 → Potential Long Setup Below 45 → Potential Short Setup. 🔹 Why is this useful? Alerts help traders react quickly without constantly monitoring the chart. Reduces the risk of missing critical trade opportunities. 🔹 Final Summary: Why is This Indicator Useful? This futuristic cyberpunk-styled trading tool enhances traditional market analysis by combining technical indicators with high-visibility visuals. 🔹 Key Benefits: ✅ Customizable Display – Toggle elements based on trading needs. ✅ Trend Detection – EMAs highlight uptrends & downtrends. ✅ Momentum Tracking – RSI-based momentum gauge identifies strong moves. ✅ Strength Meters – Bullish/Bearish power is clearly visualized. ✅ Volatility Insights – ATR-based metric highlights market turbulence. ✅ Trend Strength Analysis – Quantifies trend intensity. ✅ Dashboard – Provides a centralized, easy-to-read data panel. ✅ Cyberpunk Neon Glow – Enhances clarity with stylish aesthetics. ✅ Real-Time Alerts – Helps traders react to key opportunities. This indicator is designed to be both functional and visually appealing, making market analysis more intuitive and efficient. 🚀
Pine Script® göstergesi
Brian_Heady tarafından
9
Volatility Footprint CandlesVolatility Footprint is an innovative volume profile indicator that dynamically adapts to real-time market conditions, providing traders with a powerful tool to visualize and interpret market structure, order flow, and potential areas of support and resistance. At its core, Volatility Footprint combines the concepts of market profile, volume analysis, and volatility measurement to create a unique and adaptive charting experience. The indicator intelligently adjusts its display based on the current market volatility, ensuring that traders always have a clear and readable chart, regardless of the instrument or timeframe they are analyzing. The footprint chart is composed of a series of color-coded boxes, each representing a specific price level. The color of the box indicates whether there is a net buying or selling pressure at that level, while the opacity reflects the relative strength of the volume. This intuitive visualization allows traders to quickly identify areas of high and low volume, as well as potential imbalances in order flow. In addition to the individual box volumes, Volatility Footprint also calculates and displays the cumulative volume delta. This running total of buy and sell volumes across all price levels provides valuable insight into the overall market sentiment and potential trends. One of the key features of Volatility Footprint is its ability to identify and highlight the Point of Control (POC). The POC represents the price level with the highest volume concentration and serves as a key reference point for potential support or resistance. By drawing attention to this crucial level, the indicator helps traders make more informed decisions about potential entry and exit points. Volatility Footprint is designed to be highly customizable, allowing traders to tailor the appearance of the footprint chart to their specific preferences. Users can easily modify the colors, opacity, and size of the boxes, labels, and POC marker to enhance readability and clarity. The indicator's versatility makes it suitable for a wide range of trading styles and strategies. Whether you are a scalper looking for short-term opportunities or a swing trader aiming to identify potential trend reversals, Volatility Footprint can provide valuable insights into market dynamics. By combining Volatility Footprint with other forms of analysis, such as price action, key levels, and technical indicators, traders can gain a more comprehensive understanding of market behavior and make better-informed trading decisions. Volatility Footprint's adaptive approach to volume profile analysis sets it apart from traditional fixed-resolution volume profile indicators. By dynamically adjusting to the unique characteristics of each instrument and timeframe, the indicator ensures that traders always have a clear and meaningful representation of market structure and order flow. Volatility Footprint is a powerful tool that traders can incorporate into their market analysis and decision-making process. By providing a dynamic, visual representation of volume and order flow at different price levels, this indicator offers valuable insights into market structure, sentiment, and potential areas of support and resistance. Let's explore how traders might effectively utilize Volatility Footprint in their trading approach. 1. Identifying Key Levels: One of the primary uses of Volatility Footprint is to identify key price levels where significant trading activity has occurred. The color-coded boxes allow traders to quickly spot areas of high volume concentration, which may indicate potential support or resistance zones. For example, if a trader notices a cluster of boxes with high opacity at a specific price level, they may interpret this as a strong support or resistance area, depending on the prevailing market context. By paying attention to these key levels, traders can make more informed decisions about potential entry and exit points, as well as placement of stop-loss orders and profit targets. 2. Assessing Market Sentiment: The cumulative volume delta feature of Volatility Footprint provides traders with a valuable gauge of overall market sentiment. By analyzing the running total of buy and sell volumes across all price levels, traders can gain insight into the dominant market forces at play. If the cumulative delta is significantly positive, it may suggest a bullish sentiment, as buying pressure has been consistently outpacing selling pressure. Conversely, a negative cumulative delta may indicate a bearish sentiment. Traders can use this information to confirm or question their bias and adjust their trading plan accordingly. 3. Confirming Breakouts and Trend Reversals: Volatility Footprint can be particularly useful in confirming the strength and validity of breakouts and potential trend reversals. When a price level is breached, traders can refer to the footprint chart to assess the volume and order flow characteristics around that level. If the breakout is accompanied by a surge in volume and a clear imbalance between buying and selling pressure, it may suggest a strong and sustainable move. On the other hand, if the volume is relatively low or evenly distributed, the breakout may be less reliable. By using Volatility Footprint to confirm breakouts, traders can make more informed decisions about whether to enter or exit a trade, or to adjust their position size. 4. Detecting Imbalances and Potential Reversals: Imbalances between buying and selling pressure at specific price levels can often precede significant market moves or reversals. Volatility Footprint makes it easy for traders to spot these imbalances visually. For instance, if a trader observes a price level with a significantly larger number of sell boxes compared to buy boxes, it may indicate a potential exhaustion point for a bullish trend, and a reversal might be imminent. Traders can use this information in conjunction with other technical analysis tools, such as trendlines, moving averages, or momentum oscillators, to identify high-probability trading opportunities. 5. Adapting to Market Conditions: One of the key strengths of Volatility Footprint is its ability to dynamically adapt to the unique volatility characteristics of different instruments and timeframes. This adaptability ensures that the indicator remains relevant and informative across a wide range of market conditions. Traders can use Volatility Footprint to gauge the relative volatility and volume of a particular instrument or timeframe, and adjust their trading approach accordingly. For example, in a highly volatile market, traders may opt for wider stop-loss levels and smaller position sizes to account for the increased risk. Incorporating Volatility Footprint into a trading strategy requires a combination of technical analysis, market understanding, and risk management. Traders should use this indicator as part of a comprehensive approach, combining it with other forms of analysis, such as price action, key levels, and technical indicators. By doing so, traders can gain a more complete picture of market dynamics and make better-informed trading decisions. It's important to note that while Volatility Footprint provides valuable insights, it should not be relied upon as a standalone trading signal. Traders should always consider the broader market context, their risk tolerance, and their overall trading plan when making decisions based on the information provided by this indicator. In conclusion, Volatility Footprint offers traders a dynamic and visually intuitive way to analyze market structure, volume, and order flow. By identifying key levels, assessing market sentiment, confirming breakouts, detecting imbalances, and adapting to market conditions, traders can leverage this powerful tool to make more informed and confident trading decisions. As with any technical analysis tool, Volatility Footprint should be used in conjunction with sound risk management principles and a well-defined trading strategy to maximize its effectiveness.
Pine Script® göstergesi
TerminalChillness tarafından
3
Trend Or Range ?Are you uncertain whether the market is trending or stuck in a range? The "Trend or Range?" indicator is here to eliminate the guesswork by providing a structured, data-driven analysis of market conditions. How It Works: This indicator doesn't rely on a single metric; instead, it analyzes five core components of market behavior to provide two actionable scores: Trend Score and Range Score. Here's how each component is calculated and integrated: 1. NATR (Normalized ATR) Purpose: Measures volatility relative to the current price. Higher values indicate active, trending markets, while lower values suggest quieter, range-bound conditions. NATR = ATR / Close ATR is the Average True Range over 14 periods (default setting). 2. ADX (Average Directional Index) Purpose: Measures the strength of the trend. A higher ADX value indicates a stronger trend. Explanation: ADX is calculated based on directional movement (+DI and -DI). It highlights the strength of the trend, regardless of direction. 3. Slope Purpose: Tracks the rate of change in price over a fixed period (14 by default) to identify momentum strength. A steeper slope indicates stronger trends. Slope = abs((Close - Close ) / 14) This measures the absolute price change over 14 bars, normalized by time. 4. RSI Stability Purpose: Measures the consistency of the RSI (Relative Strength Index) over time, highlighting mean-reverting behavior. RSI Stability = stdev(RSI, 14) This calculates the standard deviation of RSI values over 14 periods. 5. Deviation Index Purpose: Quantifies the price's deviation from its 14-period simple moving average (SMA). This highlights overextension, which is common in range-bound markets. Deviation Index = (Close - SMA(14)) / SMA(14) Positive values indicate price above the SMA, while negative values show it below. Scoring System Trend Score Calculation The Trend Score is a weighted sum of metrics that favor trending markets: 30% NATR: High volatility is a hallmark of trends. 30% ADX: A proven measure of trend strength. 40% Slope: Directly measures momentum. Trend Score = (0.3 * NATR) + (0.3 * ADX) + (0.4 * Slope) Range Score Calculation The Range Score emphasizes mean-reverting behavior: 40% RSI Stability: Captures consistent RSI values common in ranges. 40% Inverse NATR: Low volatility favors range-bound markets. 20% Deviation Index: Measures overextension from the mean. Range Score = (0.4 * RSI Stability) + (0.4 * (1 / NATR)) + (0.2 * Deviation Index) What You See on the Chart Table Display: A user-friendly table appears on the chart, showing: Real-time values of all five metrics. Calculated Trend and Range Scores. Color-coded signals: Green for dominant Trend Score. Red for dominant Range Score. Data Plots: Each metric is plotted in the data window for further analysis.
Pine Script® göstergesi
cyatophilum tarafından
2
Trend IdentifierThe “Trend Identifier” indicator is designed to help traders quickly identify trending and sideways market conditions, allowing them to adapt their strategies based on the prevailing market sentiment. By combining several technical analysis tools—ATR (Average True Range), ADX (Average Directional Index), EMA (Exponential Moving Average), and RSI (Relative Strength Index)—this script provides insights into the market’s strength, direction, and volatility to improve trade decision-making. How It Works 1. ATR (Average True Range): • ATR measures market volatility. In this script, ATR is used in combination with a moving average to identify periods of rising or falling volatility, which helps differentiate between trending and non-trending conditions. 2. ADX (Average Directional Index): • ADX is a key component in identifying the strength of a trend. The script uses a threshold system to classify market conditions: • If ADX is low (below a specified threshold plus a buffer) and ATR indicates low volatility, the market is likely in a sideways condition. • If ADX is high (above a threshold minus a buffer) with increasing ATR, the market is likely in a trending condition. 3. EMA (Exponential Moving Average): • A 20-period EMA is used instead of a simple moving average to enhance trend detection speed. The close price’s position relative to the EMA helps identify bullish or bearish trends when combined with ADX and ATR data. 4. RSI (Relative Strength Index): • RSI acts as a confirmation tool for trend strength. A bullish trend is confirmed if RSI is above 50 and the price is above the EMA, whereas a bearish trend is confirmed if RSI is below 50 and the price is below the EMA. Market Condition Signals • Sideways Signal: • When ADX and ATR indicate a low-volatility, sideways market, the indicator changes the background color to gray, signaling potential low-trend movement or consolidation. A “S” symbol appears above the bars, making it easier to spot this condition. • Bullish Trend: • When conditions favor a strong upward trend, the background changes to green. A “B” symbol is displayed below the bar, indicating the onset of a bullish market condition. • Bearish Trend: • Conversely, if conditions indicate a downward trend, the background color changes to red. A “S” symbol is displayed below the bar, showing a bearish trend condition. Using the Indicator This indicator helps traders understand the current market structure in a glance: • Sideways (Gray): Low-volatility consolidation period, ideal for range-bound strategies or waiting for a breakout. • Bullish (Green): Confirmed uptrend, potentially suitable for buying or long entries. • Bearish (Red): Confirmed downtrend, ideal for short selling or exiting long positions. The “Trend Identifier” is a powerful tool for traders who seek a clear view of the market structure, using a balanced approach of volatility, trend strength, and momentum. By combining the power of ATR, ADX, EMA, and RSI, this indicator provides a nuanced picture of the market’s behavior, assisting traders in making more informed decisions.
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TradeTechanalysis tarafından
XAUUSD Multi-Timeframe Trend AnalyzerOverview The "XAUUSD Multi-Timeframe Trend Analyzer" is an advanced script designed to provide a comprehensive analysis of the XAUUSD (Gold/US Dollar) trend across multiple timeframes simultaneously. By combining several key technical indicators, this tool helps traders quickly assess the market direction and trend strength for M15, M30, H1, H4, and D1 timeframes. Multi-Timeframe Analysis: Displays the trend direction and strength across M15, M30, H1, H4, and D1 timeframes, allowing for a complete overview in a single glance. Comprehensive Indicator Blend: Utilizes six popular technical indicators to determine the trend—Moving Averages, RSI, MACD, Bollinger Bands, DMI, and Parabolic SAR. Trend Strength Scoring: Provides a numerical trend strength score (from -6 to 6) based on the alignment of the indicators, with positive values indicating uptrends and negative values for downtrends. Visual Table Display: Displays results in a color-coded table (green for uptrend, red for downtrend, yellow for neutral) with a strength score for each timeframe, helping traders quickly assess market conditions. How It Works This script calculates the overall trend and its strength for each selected timeframe by analyzing six widely-used technical indicators: Moving Averages (MA): The script uses a Fast and a Slow Moving Average. When the Fast MA crosses above the Slow MA, it indicates an uptrend. When the Fast MA crosses below, it signals a downtrend. Relative Strength Index (RSI): The RSI is used to assess momentum. An RSI value above 50 suggests bullish momentum, while a value below 50 suggests bearish momentum. Moving Average Convergence Divergence (MACD): MACD measures momentum and trend direction. When the MACD line crosses above the signal line, it signals bullish momentum; when it crosses below, it signals bearish momentum. Bollinger Bands: These measure price volatility. When the price is above the middle Bollinger Band, the script considers the trend to be bullish, and when it's below, bearish. Directional Movement Index (DMI): The DMI compares positive directional movement (DI+) and negative directional movement (DI-). A stronger DI+ over DI- signals an uptrend and vice versa. Parabolic SAR: This indicator is used for determining potential trend reversals and setting stop-loss levels. If the price is above the Parabolic SAR, it indicates an uptrend, and if below, a downtrend. Trend Strength Calculation The script calculates a trend strength score for each timeframe: Each indicator adds or subtracts 1 to the score based on whether it aligns with an uptrend or a downtrend. A score of 6 indicates a Strong Uptrend, with all indicators aligned bullishly. A score of -6 indicates a Strong Downtrend, with all indicators aligned bearishly. Intermediate scores (e.g., 2 or -2) indicate Weak Uptrend or Weak Downtrend, suggesting that not all indicators are in agreement. A score between 1 and -1 indicates a Neutral trend, suggesting uncertainty in the market. How to Use Assess Trend Direction and Strength: The table provides an easy-to-read summary of the trend and its strength on different timeframes. Look for timeframes where the strength is high (either 6 for a strong uptrend or -6 for a strong downtrend) to confirm the market’s overall direction. Use in Conjunction with Other Strategies: This indicator is designed to provide a comprehensive view of the market. Traders should combine it with other strategies, such as price action analysis or candlestick patterns, to further confirm their trades. Trend Reversal or Continuation: A weak trend (e.g., a strength of 2 or -2) could signal a possible reversal or a trend that has lost momentum. Strong trends (with a strength of 6 or -6) indicate higher confidence in trend continuation. Multiple Timeframe Confirmation: Look for alignment across multiple timeframes to confirm the strength and direction of the trend before entering trades. For example, if M15, M30, and H1 are all showing a strong uptrend, it suggests a higher probability of the trend continuing. Customization Options - Adjustable Indicators: Users can modify the length and parameters of the Moving Averages, RSI, MACD, Bollinger Bands, DMI, and Parabolic SAR to suit their trading style. - Flexible Timeframes: You can toggle between different timeframes (M15, M30, H1, H4, D1) to focus on the intervals most relevant to your strategy. Ideal For - Traders looking for a detailed, multi-timeframe trend analysis tool for XAUUSD. - Traders who rely on trend-following strategies and need confirmation across multiple timeframes. - Those who prefer a multi-indicator approach to avoid false signals and improve the accuracy of their trades. Disclaimer This indicator is for informational and educational purposes only. It is recommended to combine this with proper risk management strategies and your own analysis. Past performance does not guarantee future results. Always perform your own due diligence before making trading decisions.
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LexAurum tarafından
3
TASC 2024.11 Ultimate Strength Index█ OVERVIEW This script implements the  Ultimate Strength Index (USI)  indicator, introduced by John Ehlers in his article titled "Ultimate Strength Index (USI)" from the  November 2024 edition of TASC's Traders' Tips . The USI is a modified version of Wilder's original Relative Strength Index (RSI) that incorporates Ehlers' UltimateSmoother lowpass filter to produce an output with significantly reduced lag. █ CONCEPTS Many technical indicators, including the RSI, lag due to their heavy reliance on historical data. John Ehlers reformulated the RSI to substantially reduce lag by applying his UltimateSmoother filter to upward movements ( strength up - SU ) and downward movements ( strength down - SD ) in the time series, replacing the standard process of smoothing changes with rolling moving averages (RMAs). Ehlers' recent works, covered in our recent script publications, have shown that the UltimateSmoother is an effective alternative to other classic averages, offering notably less lag in its response. Ehlers also modified the RSI formula to produce an index that ranges from -1 to +1 instead of 0 to 100. As a result, the USI indicates bullish conditions when its value moves above 0 and bearish conditions when it falls below 0. The USI retains many of the strengths of the traditional RSI while offering the advantage of reduced lag. It generally uses a larger lookback window than the conventional RSI to achieve similar behavior, making it suitable for trend trading with longer data lengths. When applied with shorter lengths, the USI's peaks and valleys tend to align closely with significant turning points in the time series, making it a potentially helpful tool for timing swing trades. █ CALCULATIONS The first step in the USI's calculation is determining each bar's strength up (SU) and strength down (SD) values. If the current bar's close exceeds the previous bar's, the calculation assigns the difference to SU. Otherwise, SU is zero. Likewise, if the current bar's close is below the previous bar's, it assigns the difference to SD. Otherwise, SD is zero. Next, instead of the RSI's typical smoothing process, the USI's calculation applies the UltimateSmoother to the short-term average SU and SD values, reducing high-frequency chop in the series with low lag. Finally, this formula determines the USI value: USI = ( Ult (SU) − Ult (SD)) / ( Ult (SU) + Ult (SD)), where Ult (SU) and Ult (SD) are the smoothed average strength up and strength down values.
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PineCodersTASC tarafından
5
Momentum Nexus Oscillator [UAlgo]The "Momentum Nexus Oscillator " indicator is a comprehensive momentum-based tool designed to provide traders with visual cues on market conditions using multiple oscillators. By combining four popular technical indicators—RSI (Relative Strength Index), VZO (Volume Zone Oscillator), MFI (Money Flow Index), and CCI (Commodity Channel Index)—this heatmap offers a holistic view of the market's momentum. The indicator plots two lines: one representing the current chart’s combined momentum score and the other representing a higher timeframe’s (HTF) score, if enabled. Through smooth gradient color transitions and easy-to-read signals, the Momentum Nexus Heatmap allows traders to easily identify potential trend reversals or continuation patterns. Traders can use this tool to detect overbought or oversold conditions, helping them anticipate possible long or short trade opportunities. The option to use a higher timeframe enhances the flexibility of the indicator for longer-term trend analysis. 🔶 Key Features Multi-Oscillator Approach: Combines four popular momentum oscillators (RSI, VZO, MFI, and CCI) to generate a weighted score, providing a comprehensive picture of market momentum. Dynamic Color Heatmap: Utilizes a smooth gradient transition between bullish and bearish colors, reflecting market momentum across different thresholds. Higher Timeframe (HTF) Compatibility: Includes an optional higher timeframe input that displays a separate score line based on the same momentum metrics, allowing for multi-timeframe analysis. Customizable Parameters: Adjustable RSI, VZO, MFI, and CCI lengths, as well as overbought and oversold levels, to match the trader’s strategy or preference. Signal Alerts: Built-in alert conditions for both the current chart and higher timeframe scores, notifying traders when long or short entry signals are triggered. Buy/Sell Signals: Displays visual signals (▲ and ▼) on the chart when combined scores reach overbought or oversold levels, providing clear entry cues. User-Friendly Visualization: The heatmap is separated into four sections representing each indicator, providing a transparent view of how each contributes to the overall momentum score. 🔶 Interpreting Indicator: Combined Score The indicator generates a combined score by weighing the individual contributions of RSI, VZO, MFI, and CCI. This score ranges from 0 to 100 and is plotted as a line on the chart. Lower values suggest potential oversold conditions, while higher values indicate overbought conditions. Color Heatmap The indicator divides the combined score into four distinct sections, each representing one of the underlying momentum oscillators (RSI, VZO, MFI, and CCI). Bullish (greenish) colors indicate upward momentum, while bearish (grayish) colors suggest downward momentum. Long/Short Signals When the combined score drops below the oversold threshold (default is 26), a long signal (▲) is displayed on the chart, indicating a potential buying opportunity. When the combined score exceeds the overbought threshold (default is 74), a short signal (▼) is shown, signaling a potential sell or short opportunity. Higher Timeframe Analysis If enabled, the indicator also plots a line representing the combined score for a higher timeframe. This can be used to align lower timeframe trades with the broader trend of a higher timeframe, providing added confirmation. Signals for long and short entries are also plotted for the higher timeframe when its combined score reaches overbought or oversold levels. 🔶Purpose of Using Multiple Technical Indicators The combination of RSI, VZO, MFI, and CCI in the Momentum Nexus Heatmap provides a comprehensive approach to analyzing market momentum by leveraging the unique strengths of each indicator. This multi-indicator method minimizes the limitations of using just one tool, resulting in more reliable signals and a clearer understanding of market conditions. RSI (Relative Strength Index) RSI contributes by measuring the strength and speed of recent price movements. It helps identify overbought or oversold levels, signaling potential trend reversals or corrections. Its simplicity and effectiveness make it one of the most widely used indicators in technical analysis, contributing to momentum assessment in a straightforward manner. VZO (Volume Zone Oscillator) VZO adds the critical element of volume to the analysis. By assessing whether price movements are supported by significant volume, VZO distinguishes between price changes that are driven by real market conviction and those that might be short-lived. It helps validate the strength of a trend or alert the trader to potential weakness when price moves are unsupported by volume. MFI (Money Flow Index) MFI enhances the analysis by combining price and volume to gauge money flow into and out of an asset. This indicator provides insight into the participation of large players in the market, showing if money is pouring into or exiting the asset. MFI acts as a volume-weighted version of RSI, giving more weight to volume shifts and helping traders understand the sustainability of price trends. CCI (Commodity Channel Index) CCI contributes by measuring how far the price deviates from its statistical average. This helps in identifying extreme conditions where the market might be overextended in either direction. CCI is especially useful for spotting trend reversals or continuations, particularly during market extremes, and for identifying divergence signals. 🔶 Disclaimer Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals. Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator. Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies. Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses. No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
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UAlgo tarafından
9
RSI 15/60 and ADX PlotIn this script, the buy and sell criteria are based on the Relative Strength Index (RSI) values calculated for two different timeframes: the 15-minute RSI and the hourly RSI. These timeframes are used together to check signals when certain thresholds are crossed, providing confirmation across both short-term and longer-term momentum. Buy Criteria: Condition 1: Hourly RSI > 60: This means the longer-term momentum shows strength. 15-minute RSI crosses above 60: This shows that the shorter-term momentum is catching up and confirms increasing strength. Condition 2: 15-minute RSI > 60: This indicates that the short-term trend is already strong. Hourly RSI crosses above 60: This confirms that the longer-term trend is also gaining strength. Both conditions aim to capture the moments when the market shows increasing strength across both short and long timeframes, signaling a potential buy opportunity. Sell Criteria: Condition 1: Hourly RSI < 40: This indicates that the longer-term trend is weakening. 15-minute RSI crosses below 40: The short-term momentum is also turning down, confirming the weakening trend. Condition 2: 15-minute RSI < 40: The short-term trend is already weak. Hourly RSI crosses below 40: The longer-term trend is now confirming the weakness, indicating a potential sell. These conditions work to identify when the market is showing weakness in both short-term and long-term timeframes, signaling a potential sell opportunity. ADX Confirmation : The Average Directional Index (ADX) is a key tool for measuring the strength of a trend. It can be used alongside the RSI to confirm whether a buy or sell signal is occurring in a strong trend or during market consolidation. Here's how ADX can be integrated: ADX > 25: This indicates a strong trend. Using this threshold, you can confirm buy or sell signals when there is a strong upward or downward movement in the market. Buy Example: If a buy signal (RSI > 60) is triggered and the ADX is above 25, this confirms that the market is in a strong uptrend, making the buy signal more reliable. Sell Example: If a sell signal (RSI < 40) is triggered and the ADX is above 25, it confirms a strong downtrend, validating the sell signal. ADX < 25: This suggests a weak or non-existent trend. In this case, RSI signals might be less reliable since the market could be moving sideways. Final Approach: The RSI criteria help identify potential overbought and oversold conditions in both short and long timeframes. The ADX confirmation ensures that the signals generated are happening during strong trends, increasing the likelihood of successful trades by filtering out weak or choppy market conditions. This combination of RSI and ADX can help traders make more informed decisions by ensuring both momentum and trend strength align before entering or exiting trades.
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deepakks444 tarafından
Volume-Price PercentileDescription: The "Volume-Price Percentile Live" indicator is designed to provide real-time analysis of the relationship between volume percentiles and price percentiles on any given timeframe. This tool helps traders assess market activity by comparing how current volume levels rank relative to historical volume data and how current price movements (specifically high-low ranges) rank relative to historical price data. The indicator visualizes the ratio of volume percentile to price percentile as a histogram, allowing traders to gauge the relative strength of volume against price movements in real time. Functionality: Volume Percentile: Calculates the percentile rank of the current volume within a user-defined rolling period (default is 30 bars). This percentile indicates where the current volume stands in comparison to historical volumes over the specified period. Price Percentile: Calculates the percentile rank of the current candle's high-low difference within a user-defined rolling period (default is 30 bars). This percentile reflects the current price movement's strength relative to past movements over the specified period. Percentile Ratio (VP Ratio): The indicator plots the ratio of the volume percentile to the price percentile. This ratio helps identify periods when volume is significantly higher or lower relative to price movement, providing insights into potential market imbalances or strength. Real-Time Data: By fetching data from a lower timeframe (e.g., 1-minute), the indicator updates continuously within the current timeframe, offering live, intra-candle updates. This ensures that traders can see the histogram change in real-time as new data becomes available, without waiting for the current candle to close. How to Use: Adding the Indicator: To use this indicator, add it to your chart on TradingView by selecting it from the Indicators list once it is published publicly. Setting Parameters: Volume Period Length: This input sets the rolling window length for calculating the volume percentile (default is 30). You can adjust it based on the desired sensitivity or historical period relevance. Candle Period Length: This input sets the rolling window length for calculating the price percentile based on the high-low difference of candles (default is 30). Adjust this to match your trading style or analysis period. Interpreting the Histogram: The histogram represents the volume percentile divided by the price percentile. Above 1: A value greater than 1 indicates that volume is relatively strong compared to price movement, which may suggest high activity or potential accumulation/distribution phases. Below 1: A value less than 1 suggests that price movement is relatively stronger than volume, indicating potential weakness in volume relative to price moves. Near 1: Values close to 1 suggest a balanced relationship between volume and price movement. Application: Use this indicator to identify potential breakout or breakdown scenarios, assess the strength of price movements, and confirm trends. When volume percentile consistently leads price percentile, it might signal sustained interest and support for the current price trend. Conversely, if volume percentile lags significantly, it might warn of potential trend weakness. Best Practices: Multiple Timeframe Analysis: While the indicator provides real-time updates on any timeframe, consider using it alongside higher timeframe analysis to confirm trends and volume behavior across different periods. Customization: Adjust the period lengths based on the asset’s typical volume and price behavior, as well as your trading strategy (e.g., short-term scalping vs. long-term trend following). Complement with Other Indicators: Use this indicator in conjunction with other volume-based tools, trend indicators, or momentum oscillators to gain a comprehensive view of market dynamics.
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orkhanrustamov tarafından