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EVaR Indicator and Position SizingThe Problem: Financial markets consistently show "fat-tailed" distributions where extreme events occur with higher frequency than predicted by normal distributions (Gaussian or even log-normal). These fat tails manifest in sudden price crashes, volatility spikes, and black swan events that traditional risk measures like volatility can underestimate. Standard deviation and conventional VaR calculations assume normally distributed returns, leaving traders vulnerable to severe drawdowns during market stress. Cryptocurrencies and volatile instruments display particularly pronounced fat-tailed behavior, with extreme moves occurring 5-10 times more frequently than normal distribution models would predict. This reality demands a more sophisticated approach to risk measurement and position sizing. The Solution: Entropic Value at Risk (EVAR) EVaR addresses these limitations by incorporating principles from statistical mechanics and information theory through Tsallis entropy. This advanced approach captures the non-linear dependencies and power-law distributions characteristic of real financial markets. Entropy is more adaptive than standard deviations and volatility measures. I was inspired to create this indicator after reading the paper " The End of Mean-Variance? Tsallis Entropy Revolutionises Portfolio Optimisation in Cryptocurrencies " by by Sana Gaied Chortane and Kamel Naoui. Key advantages of EVAR over traditional risk measures: Superior tail risk capture: More accurately quantifies the probability of extreme market moves Adaptability to market regimes: Self-calibrates to changing volatility environments Non-parametric flexibility: Makes less assumptions about the underlying return distribution Forward-looking risk assessment: Better anticipates potential market changes (just look at the charts :) Mathematically, EVAR is defined as: EVAR_α(X) = inf_{z>0} {z * log(1/α * M_X(1/z))} Where the moment-generating function is calculated using q-exponentials rather than conventional exponentials, allowing precise modeling of fat-tailed behavior. Technical Implementation This indicator implements EVAR through a q-exponential approach from Tsallis statistics: Returns Calculation: Price returns are calculated over the lookback period Moment Generating Function: Approximated using q-exponentials to account for fat tails EVAR Computation: Derived from the MGF and confidence parameter Normalization: Scaled to for intuitive visualization Position Sizing: Inversely modulated based on normalized EVAR The q-parameter controls tail sensitivity—higher values (1.5-2.0) increase the weighting of extreme events in the calculation, making the model more conservative during potentially turbulent conditions. Indicator Components 1. EVAR Risk Visualization Dynamic EVAR Plot: Color-coded from red to green normalized risk measurement (0-1) Risk Thresholds: Reference lines at 0.3, 0.5, and 0.7 delineating risk zones 2. Position Sizing Matrix Risk Assessment: Current risk level and raw EVAR value Position Recommendations: Percentage allocation, dollar value, and quantity Stop Parameters: Mathematically derived stop price with percentage distance Drawdown Projection: Maximum theoretical loss if stop is triggered Interpretation and Application The normalized EVAR reading provides a probabilistic risk assessment: < 0.3: Low risk environment with minimal tail concerns 0.3-0.5: Moderate risk with standard tail behavior 0.5-0.7: Elevated risk with increased probability of significant moves > 0.7: High risk environment with substantial tail risk present Position sizing is automatically calculated using an inverse relationship to EVAR, contracting during high-risk periods and expanding during low-risk conditions. This is a counter-cyclical approach that ensures consistent risk exposure across varying market regimes, especially when the market is hyped or overheated. Parameter Optimization For optimal risk assessment across market conditions: Lookback Period: Determines the historical window for risk calculation Q Parameter: Controls tail sensitivity (higher values increase conservatism) Confidence Level: Sets the statistical threshold for risk assessment For cryptocurrencies and highly volatile instruments, a q-parameter between 1.5-2.0 typically provides the most accurate risk assessment because it helps capturing the fat-tailed behavior characteristic of these markets. You can also increase the q-parameter for more conservative approaches. Practical Applications Adaptive Risk Management: Quantify and respond to changing tail risk conditions Volatility-Normalized Positioning: Maintain consistent exposure across market regimes Black Swan Detection: Early identification of potential extreme market conditions Portfolio Construction: Apply consistent risk-based sizing across diverse instruments This indicator is my own approach to entropy-based risk measures as an alterative to volatility and standard deviations and it helps with fat-tailed markets. Enjoy!
Penunjuk Pine Script®
oleh HenriqueCentieiro
DIP BUYING by HAZEREAL BUY THE DIP - Educational Price Movement Indicator This technical indicator is designed for educational purposes to help traders identify potential price reversal opportunities in equity markets, particularly focusing on NASDAQ-100 index tracking instruments and technology sector ETFs. Key Features: Monitors price movements relative to recent highs over customizable lookback periods Identifies two distinct price decline thresholds: standard (5%+) and extreme (12.3%+) Visual signals with triangular markers and background color zones Real-time data table showing current metrics and status Customizable alert system with webhook-ready JSON formatting Clean overlay design that doesn't obstruct price action How It Works: The indicator tracks the highest price within a specified lookback period and calculates the percentage decline from that high. When price drops below the minimum threshold, it generates visual buy signals. The extreme threshold triggers enhanced alerts for more significant market movements. Best Use Cases: Educational analysis of market volatility patterns Identifying potential support levels during market corrections Studying historical price behavior around significant declines Risk management and position sizing education Important Note: This is a technical analysis tool for educational purposes only. All trading decisions should be based on comprehensive analysis and appropriate risk management. Past performance does not guarantee future results.
Penunjuk Pine Script®
oleh profitgang
我的策略 The specific implementation of the dominant_cycle function needs to be done using ta.ht_dominant_cycle_period or by calculating the rate of change of the phase, which requires detailed technical processing in actual coding. How to use the "Market Mathieu Oscillator": • Green background (stable zone): The market is likely to be in a consolidation or mean reversion state. Trend strategies are riskier, while range trading or option seller strategies may be more dominant. • Yellow background (warning zone): The market has entered a "flammable" state where resonance may occur. Counter-trend trading should be reduced, and preparations for potential breakthroughs should be started, tightening stops. • Red background (unstable/resonance zone): **Highest alert! ** This shows that the market is not only "flammable", but also has a "spark" (strong driving force). This is the stage where the trend is most likely to accelerate and sustain itself. Counter-trend operations should be strictly avoided, and trend-following strategies should be actively adopted. • Q Oscillator: • The rising q value means that emotions are moving to extremes and the "fuel" of the trend is increasing. • The q-value is falling, indicating that sentiment is returning to neutrality and the "fuel" of the trend is decreasing, which may indicate the exhaustion of the trend or the beginning of consolidation. • When the q-value exceeds the red threshold line, it indicates that the driving force is extremely strong, which is one of the necessary conditions for entering the red background. The "Market Mathieu Oscillator" is an innovative attempt to transform a profound physical and financial theory into an intuitive decision-making aid available on TradingView through a proxy and simplified approach. It cannot make precise quantitative predictions like theoretical models, but it provides a whole new dimension to observe the market: it no longer focuses solely on the price itself, but on the relationship between the "force" that drives the price and the "rhythm" of the market itself. Through this lens, traders can better understand when the market may turn from stability to turbulence, and make more strategic decisions.
Strategi Pine Script®
oleh gogptssss
Vùng đỉnh đáy chính theo phá vỡ (dùng line)Indicator Name: 🔺 Key Swing Zones Based on Breakouts (Line-Based) Short Description: This indicator automatically detects and visualizes key swing highs and lows based on the principle of candle close breaking the wick of the previous candle, then classifies the current market trend as uptrend, downtrend, or neutral. It draws horizontal lines representing key zones and adds visual labels to help traders analyze market structure more clearly. How It Works: 🔹 Reversal Signal Logic: In an uptrend, if a candle closes below the previous candle's low, it marks a swing low. In a downtrend, if a candle closes above the previous candle's high, it marks a swing high. 🔹 Structure Break Detection: Price breaking above a key high → confirms an uptrend. Price breaking below a key low → confirms a downtrend. If price breaks a zone but doesn't form a new high/low → switches to neutral. 🔹 Visual Display: Draws two horizontal lines: one at the key high, one at the key low. Adds labels "Key High" or "Key Low" at the breakout points. Zone color representation: 🟢 Green = Uptrend 🔴 Red = Downtrend ⚪ White = Neutral
Penunjuk Pine Script®
oleh tdv62509
Stochastic Money Flow IndexThe Stochastic Money Flow Index (or Stochastic MFI ), is a variation of the classic Stochastic RSI that uses the Money Flow Index (MFI) rather than the Relative Strength Index (RSI) in its calculation. While the RSI focuses solely on price momentum, the MFI is a volume-weighted indicator, meaning it incorporates both price and volume data. The Stochastic MFI is intended to provide a more precise and sensitive reading of the MFI by measuring the level of the MFI relative to its range over a specific period. Settings Stochastic Settings %K Length : The number of periods used to calculate the Stochastic. (Default: 14) %K Smoothing : The SMA length used to 'smooth' the %K line. (Default: 3) %D Smoothing : The SMA length used to 'smooth' the %D line. (Default: 1) Money Flow Index Settings MFI Length : The number of periods used to calculate the Money Flow Index. (Default: 14) MFI Source : The source used to calculate the Money Flow Index. (Default: close) Additional Settings Show Overbought/Oversold Gradients? : Toggle the display of overbought/oversold gradients. (Default: true)
Penunjuk Pine Script®
oleh iambrennanwalsh
VDN2 - SuperTrend + ADX + Stochastic StrategySuperTrend + ADX + Stochastic Overview:
A trend-following and momentum-confirmation strategy using SuperTrend, ADX (>20 filter), and Stochastic oscillator. Optimized for Gold (XAUUSD) on the 10-minute chart. Backtest Highlights (Last 1 Week): Win Rate: 83.3% (5 out of 6 trades) Net Profit: +56.35 USD (1 contract size) Avg Trade Duration: ~58 bars (~9.6 hours) Max Drawdown: 16.65 USD Avg Win: 9.24 USD, Avg Loss: 0.82 USD Largest Single Profit: 23.28 USD Profit Factor: ~11.27 Core Logic: Enter Long when: * SuperTrend is bullish * ADX > 20 * Stochastic %K > %D and %K < 80 Enter Short when: * SuperTrend is bearish * ADX > 20 * Stochastic %K < %D and %K > 20 No fixed TP/SL. Positions closed on signal reversal.
Strategi Pine Script®
oleh vidinozyer
Bollinger Bands ±2σ & ±3σBollinger Band 2 & 3 standard deviation, clubbed together, so that you can take trade on BKP & BKT. // This Pine Script plots Bollinger Bands with both ±2σ and ±3σ levels for enhanced volatility analysis. // Users can customize the moving average type, length, and standard deviation multipliers directly in the settings. // The indicator overlays a shaded ±2σ region and semi-transparent ±3σ bands to highlight extreme price movements.
Penunjuk Pine Script®
oleh SwastikPrakash
Greer Book Value Yield📘 Script Title Greer Book Value Yield – Valuation Insight Based on Balance Sheet Strength 🧾 Description Greer Book Value Yield is a valuation-focused indicator in the Greer Financial Toolkit, designed to evaluate how much net asset value (book value) a company provides per share relative to its current market price. This script calculates the Book Value Per Share Yield (BV%) using the formula: Book Value Yield (%) = Book Value Per Share ÷ Stock Price × 100 This yield helps investors assess whether a stock is trading at a discount or premium to its underlying assets. It dynamically highlights when the yield is: 🟢 Above its historical average (potentially undervalued) 🔴 Below its historical average (potentially overvalued) 🔍 Use Case Analyze valuation through asset-based metrics Identify buy opportunities when book value yield is historically high Combine with other scripts in the Greer Financial Toolkit: 📘 Greer Value – Tracks year-over-year growth consistency across six key metrics 📊 Greer Value Yields Dashboard – Visualizes multiple valuation-based yields 🟢 Greer BuyZone – Highlights long-term technical buy zones 🛠️ Inputs & Data Uses Book Value Per Share (BVPS) from TradingView’s financial database (Fiscal Year) Calculates and compares against a static average yield to assess historical valuation Clean visual feedback via dynamic coloring and overlays ⚠️ Disclaimer This tool is for educational and informational purposes only and should not be considered financial advice. Always conduct your own research before making investment decisions.
Penunjuk Pine Script®
oleh controllinghand
Random Coin Toss Strategy📌 Overview This strategy is a probability-based trading simulation that randomly decides trade direction using a coin-toss mechanism and executes trades with a customizable risk-reward ratio. It's designed primarily for testing entry frequency and risk dynamics, not predictive accuracy. 🎯 Core Concept Every N bars (configurable), the strategy performs a pseudo-random coin toss. Based on the result: If heads → Buy If tails → Sell Once a position is opened, it sets a Stop-Loss (SL) and Take-Profit (TP) based on a multiple of the current ATR (Average True Range) value. ⚙️ Configurable Inputs ATR Length Period for ATR calculation, determines volatility basis. SL Multiplier SL distance = ATR × multiplier (e.g., 1.0 means 1x ATR) . TP Multiplier TP distance = ATR × multiplier (e.g., 2.0 = 2x ATR) . Entry Frequency Bars to wait between each new coin toss decision. Show TP/SL Zones Toggle on/off for drawing visual TP and SL zones. Box Size Number of bars used to define the width of the TP/SL boxes. 🔁 Entry & Exit Logic Entry: Happens only when no current position exists and it's the correct bar interval. Entry direction is randomly decided. Exit: Positions exit at either: Take-Profit (TP) level Stop-Loss (SL) level Both are calculated using the configured ATR-based distances. 🖼️ Visual Features TP and SL zones: Rendered as shaded rectangles (boxes) only once per trade. Green box for TP zone, red box for SL zone. Automatically deleted and redrawn for each new trade to avoid chart clutter. ATR Display Table: A minimal info table at the top-right shows the current ATR value. Updates every few bars for performance. 🧪 Use Cases Ideal for risk-reward modeling, strategy prototyping, and understanding how volatility-based SL/TP behavior affects results. Great for backtesting frequency, RR tweaks (e.g., 2:5 or 3:1), and execution structure in random conditions. ⚠️ Disclaimer Since the trade direction is random, this script is not meant for predictive trading but serves as a powerful experiment framework for studying how SL, TP, and volatility interact with random chance in a controlled, repeatable system.
Strategi Pine Script®
oleh vineeth059
1
Momentum SNR VIP [3 TP + Max 50 Pip SL]//@version=6 indicator("Momentum SNR VIP ", overlay=true) // === Settings === pip = input.float(0.0001, "Pip Size", step=0.0001) sl_pip = 50 * pip tp1_pip = 40 * pip tp2_pip = 70 * pip tp3_pip = 100 * pip lookback = input.int(20, "Lookback for S/R", minval=5) // === SNR === pivotHigh = ta.pivothigh(high, lookback, lookback) pivotLow = ta.pivotlow(low, lookback, lookback) supportZone = not na(pivotLow) resistanceZone = not na(pivotHigh) plotshape(supportZone, title="Support", location=location.belowbar, color=color.blue, style=shape.triangleup, size=size.tiny) plotshape(resistanceZone, title="Resistance", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.tiny) // === Price Action === bullishEngulfing = close < open and close > open and close > open and open <= close bearishEngulfing = close > open and close < open and close < open and open >= close bullishPinBar = close < open and (low - math.min(open, close)) > 1.5 * math.abs(close - open) bearishPinBar = close > open and (high - math.max(open, close)) > 1.5 * math.abs(close - open) buySignal = supportZone and (bullishEngulfing or bullishPinBar) sellSignal = resistanceZone and (bearishEngulfing or bearishPinBar) // === SL & TP === rawBuySL = low - 10 * pip buySL = math.max(close - sl_pip, rawBuySL) buyTP1 = close + tp1_pip buyTP2 = close + tp2_pip buyTP3 = close + tp3_pip rawSellSL = high + 10 * pip sellSL = math.min(close + sl_pip, rawSellSL) sellTP1 = close - tp1_pip sellTP2 = close - tp2_pip sellTP3 = close - tp3_pip // === Plot Lines === plot(buySignal ? buySL : na, title="Buy SL", color=color.red, style=plot.style_line, linewidth=1) plot(buySignal ? buyTP1 : na, title="Buy TP1", color=color.green, style=plot.style_line, linewidth=1) plot(buySignal ? buyTP2 : na, title="Buy TP2", color=color.green, style=plot.style_line, linewidth=1) plot(buySignal ? buyTP3 : na, title="Buy TP3", color=color.green, style=plot.style_line, linewidth=1) plot(sellSignal ? sellSL : na, title="Sell SL", color=color.red, style=plot.style_line, linewidth=1) plot(sellSignal ? sellTP1 : na, title="Sell TP1", color=color.green, style=plot.style_line, linewidth=1) plot(sellSignal ? sellTP2 : na, title="Sell TP2", color=color.green, style=plot.style_line, linewidth=1) plot(sellSignal ? sellTP3 : na, title="Sell TP3", color=color.green, style=plot.style_line, linewidth=1) // === Floating Labels on Right Side === if buySignal label.new(x=bar_index + 50, y=buySL, text="SL", style=label.style_label_right, color=color.red, textcolor=color.white) label.new(x=bar_index + 50, y=buyTP1, text="TP1", style=label.style_label_right, color=color.green, textcolor=color.white) label.new(x=bar_index + 50, y=buyTP2, text="TP2", style=label.style_label_right, color=color.green, textcolor=color.white) label.new(x=bar_index + 50, y=buyTP3, text="TP3", style=label.style_label_right, color=color.green, textcolor=color.white) if sellSignal label.new(x=bar_index + 50, y=sellSL, text="SL", style=label.style_label_right, color=color.red, textcolor=color.white) label.new(x=bar_index + 50, y=sellTP1, text="TP1", style=label.style_label_right, color=color.green, textcolor=color.white) label.new(x=bar_index + 50, y=sellTP2, text="TP2", style=label.style_label_right, color=color.green, textcolor=color.white) label.new(x=bar_index + 50, y=sellTP3, text="TP3", style=label.style_label_right, color=color.green, textcolor=color.white) // === Signal Markers === plotshape(buySignal, title="Buy Signal", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY") plotshape(sellSignal, title="Sell Signal", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL") // === Alerts === alertcondition(buySignal, title="Buy Alert", message="🟢 BUY at Support Zone + Price Action") alertcondition(sellSignal, title="Sell Alert", message="🟡 SELL at Resistance Zone + Price Action")
Penunjuk Pine Script®
oleh shakalss7
Candles by Day, Time, Month + StatsThis Pine Script allows you to filter and display candles based on: 📅 Specific days of the week 🕒 Custom intraday time ranges (e.g., 9:15 to 10:30) 📆 Selected months 📊 Shows stats for each filtered block: 🔼 Range (High – Low) 📏 Average candle body size ⚙️ Key Features: ✅ Filter by day, time, and month 🎛 Toggle to show/hide the stats label 🟩 Candles are drawn only for selected conditions 📍 Stats label is positioned above session high (adjustable) ⚠️ Important Setup Instructions: ✅ 1. Use it on a blank chart To avoid overlaying with default candles: Open the chart of your preferred symbol Click on the chart type (top toolbar: "Candles", "Bars", etc.) Select "Blank" from the dropdown (this will hide all native candles) Apply this indicator This ensures only the filtered candles from the script are visible. Adjust for your local timezone This script uses a hardcoded timezone: "Asia/Kolkata" If you are in a different timezone, change it to your own (e.g. "America/New_York", "Europe/London", etc.) in all instances of: time(timeframe.period, "Asia/Kolkata") timestamp("Asia/Kolkata", ...) Use Cases: Opening range behavior on specific weekdays/months Detecting market anomalies during exact windows Building visual logs of preferred trade hours
Penunjuk Pine Script®
oleh country_flag_quiz