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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.
Pine Script® strategy
by vineeth059
1
FULLY FUNCTIONAL INDICATOR TESTER🎯 Purpose: A comprehensive strategy testing framework designed to evaluate custom indicators and trading signals with professional-grade risk management and signal detection capabilities. ✨ Key Features: Multiple Signal Detection Methods - Value changes, crossovers, threshold-based triggers Advanced Confluence Filtering - Multi-source confirmation system with lookback periods Professional Risk Management - Static TP/SL, break-even functionality, position sizing Custom Exit Signals - Independent exit logic for refined strategy testing Visual Feedback System - Clear signal plots and real-time status monitoring Flexible Input Sources - Connect any custom indicator or built-in study 🔧 How to Use: Connect your indicator outputs to the Entry/Exit source inputs Select appropriate signal detection method for your indicator type Configure risk parameters (TP/SL/Break-even) Enable confluence filters if needed for additional confirmation Backtest and analyze results with built-in performance metrics 📈 Signal Detection Options: Value Change: Detects when indicator values change Crossover Above/Below: Traditional crossover signals Threshold Triggers: Value-based entry/exit levels ⚙️ Technical Specifications: Compatible with Pine Script v6 Overlay strategy with position tracking Real-time performance monitoring table Configurable margin requirements Full backtesting compatibility ⚠️ Important Notes: This is a testing framework - not financial advice Always validate signals in demo environment first Past performance does not guarantee future results Use proper risk management in live trading 🔄 Updates: Enhanced signal detection algorithms Improved confluence logic Added break-even functionality Visual debugging tools Perfect for traders and developers looking to systematically tes
Pine Script® strategy
by profitgang
My script//@version=5 indicator("MA + OI + Volume Breakout", overlay=true) // === MA Parameters === ma_type = input.string("EMA", title="MA Type", options= ) ma(src, len, type) => type == "SMA" ? ta.sma(src, len) : type == "EMA" ? ta.ema(src, len) : ta.wma(src, len) ma5 = ma(close, 5, ma_type) ma21 = ma(close, 21, ma_type) ma50 = ma(close, 50, ma_type) ma100 = ma(close, 100, ma_type) plot(ma5, "5-day MA", color=color.yellow, linewidth=2) plot(ma21, "21-day MA", color=color.orange, linewidth=2) plot(ma50, "50-day MA", color=color.fuchsia, linewidth=2) plot(ma100, "100-day MA", color=color.blue, linewidth=2) // === Trend Signal === bullish_trend = ma5 > ma21 and ma21 > ma50 and ma50 > ma100 bearish_trend = ma5 < ma21 and ma21 < ma50 and ma50 < ma100 bgcolor(bullish_trend ? color.new(color.green, 85) : bearish_trend ? color.new(color.red, 85) : na) // === Volume Breakout === vol_avg = ta.sma(volume, 20) vol_breakout = volume > 1.5 * vol_avg plotshape(vol_breakout, title="Volume Breakout", location=location.belowbar, style=shape.circle, color=color.aqua, size=size.tiny) // === Open Interest Overlay (assumes OI data via external input or future integration) === // Placeholder: simulate OI input (replace with `request.security(syminfo.tickerid, ..., ...)` if available) oi = input.float(na, title="Open Interest (external feed)") oi_avg = ta.sma(oi, 20) oi_breakout = oi > 1.2 * oi_avg plotshape(not na(oi) and oi_breakout, title="OI Spike", location=location.belowbar, style=shape.diamond, color=color.purple, size=size.tiny) plot(oi, title="Open Interest", color=color.gray, display=display.none) // Optional: hidden line for alerts // === Composite Signal === strong_long = bullish_trend and vol_breakout and oi_breakout plotshape(strong_long, title="Strong Long Signal", location=location.belowbar, style=shape.labelup, text="LONG", size=size.small, color=color.lime) // === Screener Logic === // Use `strong_long` as your filter condition in a screener or dashboard output
Pine Script® indicator
by nikhilkapadia
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")
Pine Script® indicator
by shakalss7
VWAP SlopePositive (green) bars mean today’s (or this interval’s) VWAP is higher than the prior one → volume‐weighted average price is drifting up → bullish flow. Negative (red) bars mean VWAP is lower than before → volume is skewed to sellers → bearish flow. Bar height shows how much VWAP has shifted, so taller bars = stronger conviction. Why it’s useful: It gives you a real-time read on whether institutions are consistently buying at higher prices or selling at lower prices. Use it as a bias filter: for shorts you want to see red bars (VWAP down-slope) at your entry, and for longs green bars (VWAP up-slope). Because it updates tick-by-tick (or per bar), you get a live snapshot of volume-weighted momentum on top of your price‐action and oscillator signals.
Pine Script® indicator
by ahmedfarhatx22
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 Buy/Sell Signal 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") // === Plot SL & TP lines plot(buySignal ? buySL : na, title="Buy SL", color=color.red, style=plot.style_linebr, linewidth=1) plot(buySignal ? buyTP1 : na, title="Buy TP1", color=color.green, style=plot.style_linebr, linewidth=1) plot(buySignal ? buyTP2 : na, title="Buy TP2", color=color.green, style=plot.style_linebr, linewidth=1) plot(buySignal ? buyTP3 : na, title="Buy TP3", color=color.green, style=plot.style_linebr, linewidth=1) plot(sellSignal ? sellSL : na, title="Sell SL", color=color.red, style=plot.style_linebr, linewidth=1) plot(sellSignal ? sellTP1 : na, title="Sell TP1", color=color.green, style=plot.style_linebr, linewidth=1) plot(sellSignal ? sellTP2 : na, title="Sell TP2", color=color.green, style=plot.style_linebr, linewidth=1) plot(sellSignal ? sellTP3 : na, title="Sell TP3", color=color.green, style=plot.style_linebr, linewidth=1) // === Labels if buySignal label.new(x=bar_index, y=buySL, text="SL : " + str.tostring(buySL, "#.0000"), style=label.style_label_down, color=color.red, textcolor=color.white) label.new(x=bar_index, y=buyTP1, text="TP1 : " + str.tostring(buyTP1, "#.0000"), style=label.style_label_up, color=color.green, textcolor=color.white) label.new(x=bar_index, y=buyTP2, text="TP2 : " + str.tostring(buyTP2, "#.0000"), style=label.style_label_up, color=color.green, textcolor=color.white) label.new(x=bar_index, y=buyTP3, text="TP3 : " + str.tostring(buyTP3, "#.0000"), style=label.style_label_up, color=color.green, textcolor=color.white) if sellSignal label.new(x=bar_index, y=sellSL, text="SL : " + str.tostring(sellSL, "#.0000"), style=label.style_label_up, color=color.red, textcolor=color.white) label.new(x=bar_index, y=sellTP1, text="TP1 : " + str.tostring(sellTP1, "#.0000"), style=label.style_label_down, color=color.green, textcolor=color.white) label.new(x=bar_index, y=sellTP2, text="TP2 : " + str.tostring(sellTP2, "#.0000"), style=label.style_label_down, color=color.green, textcolor=color.white) label.new(x=bar_index, y=sellTP3, text="TP3 : " + str.tostring(sellTP3, "#.0000"), style=label.style_label_down, color=color.green, textcolor=color.white) // === 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")
Pine Script® indicator
by shakalss7
Momentum SNR VIP [INDICATOR ONLY]//@version=6 indicator("Momentum SNR VIP ", overlay=true) // === Inputs === lookback = input.int(20, "Lookback for S/R", minval=5) rr_ratio = input.float(2.0, "Risk-Reward Ratio", minval=0.5, step=0.1) // === SNR Detection === 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 === buySL = low - 10 buyTP = close + (close - buySL) * rr_ratio sellSL = high + 10 sellTP = close - (sellSL - close) * rr_ratio // === Plot Signals 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") plot(buySignal ? buySL : na, title="Buy SL", color=color.red, style=plot.style_linebr, linewidth=1) plot(buySignal ? buyTP : na, title="Buy TP", color=color.green, style=plot.style_linebr, linewidth=1) plot(sellSignal ? sellSL : na, title="Sell SL", color=color.red, style=plot.style_linebr, linewidth=1) plot(sellSignal ? sellTP : na, title="Sell TP", color=color.green, style=plot.style_linebr, linewidth=1) // === Labels (Fixed) if buySignal label.new(x=bar_index, y=buySL, text="SL : " + str.tostring(buySL, "#.00"), style=label.style_label_down, color=color.red, textcolor=color.white) label.new(x=bar_index, y=buyTP, text="TP 1 : " + str.tostring(buyTP, "#.00"), style=label.style_label_up, color=color.green, textcolor=color.white) if sellSignal label.new(x=bar_index, y=sellSL, text="SL : " + str.tostring(sellSL, "#.00"), style=label.style_label_up, color=color.red, textcolor=color.white) label.new(x=bar_index, y=sellTP, text="TP 1 : " + str.tostring(sellTP, "#.00"), style=label.style_label_down, color=color.green, textcolor=color.white) // === 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")
Pine Script® indicator
by shakalss7
Repeating Trend HighlighterThis custom indicator helps you see when the current price trend is similar to a past trend over the same number of candles. Think of it like checking whether the market is repeating itself. You choose three settings: • Lookback Period: This is how many candles you want to measure. For example, if you set it to 10, it looks at the price change over the last 10 bars. • Offset Bars Ago: This tells the indicator how far back in time to look for a similar move. If you set it to 50, it compares the current move to what happened 50 bars earlier. • Tolerance (%): This is how closely the moves must match to be considered similar. A smaller number means you only get a signal if the moves are almost the same, while a larger number allows more flexibility. When the current price move is close enough to the past move you picked, the background of your chart turns light green. This makes it easy to spot repeating trends without studying numbers manually. You’ll also see two lines under your chart if you enable them: a blue line showing the percentage change of the current move and an orange line showing the change in the past move. These help you compare visually. This tool is useful in several ways. You can use it to confirm your trading setups, for example if you suspect that a strong rally or pullback is happening again. You can also use it to filter trades by combining it with other indicators, so you only enter when trends repeat. Many traders use it as a learning tool, experimenting with different lookback periods and offsets to understand how often similar moves happen. If you are a scalper working on short timeframes, you can set the lookback to a small number like 3–5 bars. Swing traders who prefer daily or weekly charts might use longer lookbacks like 20–30 bars. Keep in mind that this indicator doesn’t guarantee price will move the same way again—it only shows similarity in how price changed over time. It works best when you use it together with other signals or market context. In short, it’s like having a simple spotlight that tells you: “This move looks a lot like what happened before.” You can then decide if you want to act on that information. If you’d like, I can help you tweak the settings or combine it with alerts so it notifies you when these patterns appear.
Pine Script® indicator
by SupertradeOfficial
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!
Pine Script® indicator
by HenriqueCentieiro