PPP – Info Table (Anchor + Corr/Alpha/Beta) v3PPP – Info Table (Anchor + Corr/Alpha/Beta)
- By P3 Analytics, run by Puranam Pradeep Picasso Sharma
🔎 Overview
This indicator creates a clean, dynamic information table on your chart that lets you quickly analyze how your chosen asset is performing relative to BTC, ETH, or any other benchmarks.
With a single glance, you can see:
% change from today’s open (for the anchor asset, BTC, and ETH)
Previous day % change (self + benchmarks)
Correlation, Beta, and Alpha statistics for the selected window (1W, 1M, 1Y)
Anchor values at any bar you choose (via Bars Back or Anchor Time)
Perfect for traders who want to measure coin strength vs benchmarks and make better rotation, risk, or hedging decisions.
📊 Key Metrics
Correlation (Corr): How closely the asset moves with the benchmark.
+1 = moves together, 0 = no relation, -1 = moves opposite.
Beta (β): Sensitivity of returns vs the benchmark.
β = 1 → moves 1:1 with BTC.
β > 1 → more volatile (amplifies BTC moves).
β < 1 → less volatile (defensive).
Alpha (α): Excess return beyond what Beta predicts.
Positive α = outperforming benchmark-adjusted expectation.
Negative α = underperforming.
⚙️ Features
Flexible Anchor Mode:
Bars Back → quickly step through bars.
Time → pin analysis to a specific historical candle.
Customizable Benchmarks: Default BTC & ETH (futures), but replaceable with any ticker.
Adjustable Stats Window:
1 Week, 1 Month, 1 Year (auto-scales if using chart timeframe).
Compact Mode for a smaller table layout.
Dark/Light Theme, font size, corner placement, transparency, and decimal control.
Runs efficiently with minimal chart clutter.
🧑💻 About P3 Analytics
This indicator is developed under P3 Analytics, a research & trading technology initiative led by Puranam Pradeep Picasso Sharma.
P3 Analytics builds tools that merge machine learning, statistics, and trading strategy into accessible products for traders across crypto, equities, forex, and commodities.
✅ How to Use
Add indicator to your chart.
In settings:
Pick your benchmarks (default = BTCUSDT.P, ETHUSDT.P).
Choose your anchor (Bars Back or Time).
Set window length for correlation/alpha/beta.
Read the table:
Left side = your asset.
Right side = benchmarks.
Colors: Green = positive % change, Red = negative.
🚀 Why Use This?
Quickly compare your asset vs BTC/ETH without juggling multiple charts.
Spot whether a coin is truly leading or just following BTC.
Identify outperformance (alpha) coins for rotation or trend plays.
Manage risk by knowing which assets are high beta (high leverage-like moves).
✦ Indicator by P3 Analytics
✦ Created & published by Puranam Pradeep Picasso Sharma
Educational
FVG valid MTF (Fair Value Gaps across Multiple Timeframes)This indicator automatically detects and displays Fair Value Gaps (FVGs) across multiple timeframes (1D, 4H, 1H, 30M, 15M, 5M).
✨ Features:
Detects valid FVGs only when they appear after three consecutive candles in the same direction (bullish or bearish).
Each gap is color-coded by direction (bullish / bearish) and changes color once mitigated.
Automatic timeframe label inside each FVG box.
Fully customizable:
Minimum & maximum FVG size (in ticks),
Extension length of boxes into the future (bars),
Maximum number of FVGs displayed per timeframe.
After mitigation, FVGs are visually updated, making it easy to see whether the market has respected the imbalance zone.
📊 Practical Use:
Identify areas of imbalance where strong price reactions often occur.
Monitor FVGs across multiple timeframes – from daily charts down to intraday.
Useful for defining support/resistance zones, entry levels, or trade exits.
⚙️ Settings:
Adjustable FVG colors for bullish, bearish, and mitigated states.
Independent limit on how many FVGs are displayed for each timeframe.
Optimized for clarity and chart performance.
GOLD – Dan Toma Patterns + Market Structure/OB [by Dragos] v3.2GOLD – Dan Toma Patterns + Market Structure/OB v3.2
(Panel x3 • Last R:R • Logical SL • HTF Filter)
All-in-one XAUUSD tool blending Dan Toma patterns (P1–P4) with Internal/External Market Structure, Order Blocks, fixed liquidity (PDH/PDL & sessions), breakout short, dip-buy on trend, a live signals panel, and auto-draw Entry/SL/TP for the last signal. Includes an HTF EMA filter (with slope) and logical Stop Loss to keep signals disciplined.
What it does
P1 – Trend Reverse SELL: structure shift (BOS down) + Supply rejection (wick/engulf) and/or RSI overbought.
P2 – Liquidity: hunts fixed liquidity: PDH/PDL and Asia/London/NY session highs/lows + wick rejection confirmation. BUY at PDL/session Lows, SELL at PDH/session Highs.
P3 – Breakout Short: tight range (ATR/ATRma below threshold) + break under range LL with volume spike.
P4 – Dip Buy: uptrend (EMA) + Demand + pullback to 61.8% (configurable) + RSI oversold.
Market Structure + OB: marks CHoCH/BOS on Internal/External and draws Order Blocks from the last opposite candle at the break (box cap & custom colors).
Auto R:R (last signal only): draws Entry/SL/TP1/TP2 (1.5R / 3R) for the most recent signal to keep the chart clean.
Logical SL: choose Pivot, SD Box, or %ATR and force correct placement (BUY: SL below entry / SELL: SL above entry).
HTF Filter: confirm direction with HTF EMA (custom TF/length), optional slope requirement (rising for BUY / falling for SELL).
Panel x3: compact panel with the last N signals (time, pattern, side, entry, SL, TP1, TP2); place it in any corner.
Quick workflow
HTF context: enable HTF filter (e.g., EMA 200 on H4) to lock a clean bias.
Structure & zones: let MS/OB mark CHoCH/BOS and Supply/Demand; look for confluence with PDH/PDL & session HLs.
Triggers:
SELL: P1/P2/P3 confluencing with Supply, BOS down, wick up, breakout volume.
BUY: P2/P4 in Demand, uptrend, pullback near 0.618, RSI OS.
Execution & management: confirm on bar close (optional repaintSafe), use logical SL, follow auto Entry/SL/TP lines of the last signal.
Panel: monitor fresh events (timestamp + details) for quick validation/journaling.
Key settings
General: XAU/GOLD filter, close-bar confirmation, optional candle labels, show Entry/SL/TP for the last signal only.
HTF: timeframe, EMA length, Need Slope toggle.
Structure/OB: Internal/External/Both/Off, swing lengths, OB lookback, max OB boxes.
Supply/Demand: pivot length (HH/LL) + wick fraction for imbalance detection.
Liquidity: PDH/PDL on/off, sessions (Asia/London/NY) and session HLs.
Breakout Short: range lookback, ATR/ATRma threshold, volume spike multiplier.
Dip Buy: EMA trend length, target Fibo retracement.
RSI/Volume: RSI length + OB/OS thresholds.
SL/TP: Pivot / SD Box / %ATR, ATR length & multiplier, forceLogicalSL.
Alerts (ready to use)
P1 – Trend Reverse SELL
P2 – Liquidity Short
P2 – Liquidity Buy
P3 – Breakout Short
P4 – Dip Buy
(Messages include current price; for auto-execution use your own bridge/automation.)
Recommendations
Timeframes: M5/M15 for entries, H1/H4 for context.
Look for 2–3 confluences (MS, OB, PDH/PDL/sessions, RSI/volume) before validating a signal.
Avoid flat, low-volume ranges or thin-liquidity periods.
Disclaimer
This is an analysis tool, not financial advice. Trading involves risk. Use strict risk management (risk < 1%/trade, R:R ≥ 1:2, mandatory SL) and test on demo/backtest before going live.
GOLD – OB Clean + Internal/External Market Structure [Dragos]GOLD – OB Clean + Internal/External Market Structure
All-in-one tool for XAUUSD that combines:
Clean Order Blocks (Supply/Demand) derived from the last opposite candle after a BOS (break of structure)
Internal & External Market Structure (CHoCH/BOS) with lines and labels
Visual zone management: right extension, mitigation (first touch), invalidation (close beyond), and 50% midline
How it works
Structure & BOS
Finds pivots (HH/LL) via Pivot len.
Triggers BOS when price crosses the last confirmed swing.
Order Blocks
On BOS, scans the last N bars for the opposite candle (bear for BOS up / bull for BOS down) and draws the OB:
Green = Demand, Red = Supply
Optional: use wicks (high/low) or just the body (open/close).
Mitigation: on first touch the zone fades or hides (per settings).
Invalidation: if price closes beyond the zone, it turns gray or gets removed (per settings).
Midline: 50% line for refined management (partial entries, R/R, etc.).
Internal / External Structure
Two structure layers: Internal (micro, shorter swing) and External (macro, longer swing).
Displays CHoCH/BOS with labels; External lines can be dashed for clarity.
Choose to show Internal, External, or Both.
Key Settings
Structure
Pivot len (swing HH/LL) — pivot sensitivity.
Order Blocks
Lookback N bars for the opposite candle
Use wicks — if on, zone uses high/low; otherwise just the body.
Zone Management
Extend zones to the right
Hide zone after mitigation (touch)
Fade zone after mitigation
Remove zone when invalidated
Show 50% line
Max zones stored
Colors: fill/border for Demand/Supply, 50% line color, Mitigated/Invalidated colors.
General
Only on XAU/GOLD (optional) — restricts execution to symbols containing “XAU”/“GOLD”.
Market Structure (tab)
Internal Swing Length / External Swing Length
Show Internal/External Market Structure (Both / Internal / External)
Colors for bullish/bearish MS
Usage Guide
Recommended timeframes: M5/M15 for entries, H1 for context.
Workflow:
Determine External (macro) direction.
Look for BOS and OB in the same direction on Internal.
Wait for mitigation (touch) inside the OB; the 50% line can be used for conservative entries.
Good confluences: sessions (killzones), volume spikes, extreme RSI, MAs (add as separate indicators if needed).
Visual Conventions
Demand: green; Supply: red.
Mitigated: faded yellow (or hidden if chosen).
Invalidated: gray (or removed).
50% line: gray.
Notes & Limits
Pine v6. Object caps follow TradingView limits (max_* = 500). On long histories, increase “Max zones stored” carefully.
BOS is computed when price crosses the last confirmed swing; some traders prefer “close-only” confirmation (can be customized if desired).
This tool does not auto-generate BUY/SELL signals; it’s a context & zones assistant.
Risk disclaimer: Trading involves risk. This tool is for educational analysis and does not guarantee profit. Use strict risk management (fixed SL, R:R ≥ 1:2, risk < 1% per trade).
Dow Theory Indicator## 🎯 Key Features of the Indicator
### 📈 Complete Implementation of Dow Theory
- Three-tier trend structure: primary trend (50 periods), secondary trend (20 periods), and minor trend (10 periods).
- Swing point analysis: automatically detects critical swing highs and lows.
- Trend confirmation mechanism: strict confirmation logic based on consecutive higher highs/higher lows or lower highs/lower lows.
- Volume confirmation: ensures price moves are supported by trading volume.
### 🕐 Flexible Timeframe Parameters
All key parameters are adjustable, making it especially suitable for U.S. equities:
Trend analysis parameters:
- Primary trend period: 20–200 (default 50; recommended 50–100 for U.S. stocks).
- Secondary trend period: 10–100 (default 20; recommended 15–30 for U.S. stocks).
- Minor trend period: 5–50 (default 10; recommended 5–15 for U.S. stocks).
Dow Theory parameters:
- Swing high/low lookback: 5–50 (default 10).
- Trend confirmation bar count: 1–10 (default 3).
- Volume confirmation period: 10–100 (default 20).
### 🇺🇸 U.S. Market Optimizations
- Session awareness: distinguishes Regular Trading Hours (9:30–16:00 EST) from pre-market and after-hours.
- Pre/post-market weighting: adjustable weighting factor for signals during extended hours.
- Earnings season filter: automatically adjusts sensitivity during earnings periods.
- U.S.-optimized default parameters.
## 🎨 Visualization
1. Trend lines: three differently colored trend lines.
2. Background fill: green (uptrend) / red (downtrend) / gray (neutral).
3. Signal markers: arrows, labels, and warning icons.
4. Swing point markers: small triangles at key turning points.
5. Info panel: real-time display of eight key metrics.
## 🚨 Alert System
- Trend turning to up/down.
- Strong bullish/bearish signals (dual confirmation).
- Volume divergence warning.
- New swing high/low formed.
## 📋 How to Use
1. Open the Pine Editor in TradingView.
2. Copy the contents of dow_theory_indicator.pine.
3. Paste and click “Add to chart.”
4. Adjust parameters based on trading style:
- Long-term investing: increase all period parameters.
- Swing trading: use the default parameters.
- Short-term trading: decrease all period parameters.
## 💡 Parameter Tips for U.S. Stocks
- Large-cap blue chips (AAPL, MSFT): primary 60–80, secondary 25–30.
- Mid-cap growth stocks: primary 40–60, secondary 18–25.
- Small-cap high-volatility stocks: primary 30–50, secondary 15–20.
CAP - KC/AC 2.20462 Converter// ───────────────────────────────────────────────────────────────────────────────
// Purpose: Conversion Indicator for ICE “C” (KC) and “C Metric” (AC) Contracts
//
// Background:
// - The Intercontinental Exchange (ICE) is phasing out the legacy Coffee “C” contract (symbol: KC),
// which has been quoted in U.S. cents per pound, and replacing it with the new Coffee “C Metric” contract (symbol: AC),
// quoted in U.S. dollars per metric ton :contentReference {index=0}.
// - The final KC futures expire in March 2028; AC contracts begin trading in September 2025 and use modern specifications
// including pricing per metric ton and flexible bulk delivery formats :contentReference {index=1}.
//
// Why this script matters:
// - Traders are accustomed to the KC pricing format (¢/lb); the AC contract’s USD/MT may create confusion.
// - This indicator visually converts the current chart price—whether from KC or AC contracts—directly into its equivalent unit,
// helping traders quickly assess parity and compare trends across both contract types.
// - It simplifies head-to-head comparison during this transition period, improving clarity on chart price behavior.
//
// Usage instructions:
// - If the symbol starts with "KC", the script divides the price by 2.20462 to convert from ¢/lb to approximate ¢/kg.
// - If the symbol starts with "AC", the script multiplies the price by 2.20462 to reverse the conversion.
// - The results (converted values) are displayed in a table for immediate visual clarity.
// ───────────────────────────────────────────────────────────────────────────────
Top Catcher | QRTop Catcher | QuantumResearch
The Top Catcher indicator is designed to help traders spot areas where markets may be forming local tops. Instead of relying on simple overbought measures like RSI or Bollinger Bands, it combines percentile-based price extremes with a volatility-adjusted filter. This approach helps highlight situations where price has stretched unusually far and then shows signs of weakness.
🔍 How It Works (Principle)
Percentile Analysis: The script measures whether price has reached an extreme compared to its recent distribution (very high percentile).
Volatility Confirmation: It checks if price fails to sustain above a volatility-adjusted upper boundary.
Signal Generation: Only when both conditions align does the script mark a potential Top with a visual triangle above the bar.
This dual-layer approach aims to reduce false signals often triggered in strong trends by single-metric tools.
🎯 Key Features
Top Signals: Plots a clear triangle above candles when potential exhaustion is detected.
Dynamic Adaptation: Works across different assets and timeframes by adjusting to each market’s own volatility.
Visual Overlay: Signals are plotted directly on the chart for intuitive reading.
Alert Ready: Built-in alerts let traders get notified as soon as a new Top signal is generated.
📈 How To Use
Trend Traders: Use signals to tighten stops or take partial profits in extended runs.
Swing Traders: Watch for reversal setups at local highs.
Multi-Timeframe Approach: Combine higher timeframe signals with intraday charts for confirmation.
The script is not meant to predict exact tops, but rather to provide an early warning of distribution zones where risk increases.
⚠️ Disclaimer
This tool is provided for educational and research purposes only. It is not financial advice. Past performance does not predict or guarantee future results. Always combine this tool with your own analysis and risk management.
Artharjan ADXArtharjan ADX (AADX) by Rrahul Desai @Artharjan
📌 Overview
The Artharjan ADX (AADX) is an advanced implementation of the Average Directional Index (ADX) with customizable moving averages, momentum thresholds, and visually intuitive grading of bullish and bearish strength.
Unlike the standard ADX indicator that only shows trend strength, AADX adds graded bullish/bearish conditions, alerts, smoothed DI signals, histogram visualizations, and background color fills to help traders quickly interpret market conditions.
It is designed for traders who want early detection of trend strength, clean visual cues, and automated alert triggers for both bullish and bearish momentum setups.
⚙️ Key Features
🔹 Customizable Calculations
DI Length (default 13) – controls sensitivity of directional indicators.
+/- DI Smoothing – smooths DI signals with user-selected MA.
Multiple Moving Average Types – SMA, EMA, WMA, RMA, VWMA, ALMA, Hull, SWMA, SMMA, TMA.
ADX Smoothing – define how smooth/fast the ADX reacts.
🔹 Flexible Display
Toggle between line plots or histogram view.
Adjustable plot thickness.
Option to plot averages of ADX, +DI, -DI for confirmation.
Configurable background fills:
ADX above/below momentum threshold.
ADX rising/falling color shading.
Trend-grade based color intensity.
🔹 Momentum & Thresholds
Momentum Level (default 25) → defines “strong trend” zone.
Crossover Threshold (default 15) → helps detect early DI crossovers.
Color-coded histogram bars for +DI vs -DI difference:
Above/below zero.
Rising/falling momentum.
🔹 Bullish & Bearish Grading System
The indicator assigns grades from 1 to 5 for both bullish and bearish setups, based on DI and ADX conditions:
Bullish Grades
Grade 1 → Very Weak Bullish
Grade 2 → Weak Bullish
Grade 3 → Moderate Bullish
Grade 4 → Strong Bullish
Grade 5 → Very Strong Bullish
Bearish Grades
Grade 1 → Very Weak Bearish
Grade 2 → Weak Bearish
Grade 3 → Moderate Bearish
Grade 4 → Strong Bearish
Grade 5 → Very Strong Bearish
Labels are automatically plotted above bars to indicate the active grade.
🔹 Alerts
Bullish Alert → when +DI crosses above its average below the threshold OR bullish conditions are met.
Bearish Alert → when -DI crosses above its average below the threshold OR bearish conditions are met.
These alerts make it possible to automate trading signals for scalping, intraday, and swing trading.
📊 Use Cases
Trend Strength Measurement
Spot when markets shift from range-bound to trending.
Confirm the reliability of breakouts with strong ADX readings.
Bullish vs Bearish Control
Compare +DI vs -DI strength to gauge trend direction.
Identify trend reversals early with DI slope changes.
Momentum Confirmation
Use ADX rising + DI grades to validate trade entries.
Filter false breakouts with weak ADX.
Trade Grading System
Enter aggressively on Grade 4–5 signals.
Stay cautious on Grade 1–2 signals.
Automated Alerts & Screening
Combine AADX alerts with strategy rules.
Build scanners to highlight strong ADX setups across multiple stocks.
🎯 Trader’s Advantage
More powerful than standard ADX → Adds slope, grading, alerts, and visualization.
Adaptable to any style → Works for intraday scalping, swing trading, and positional analysis.
Visual clarity → Color fills, histograms, and labels simplify decision-making.
Customizable smoothing → Adjusts to fast or slow markets.
✅ Closing Note
The Artharjan ADX (AADX) transforms the traditional ADX into a complete trend and momentum analyzer. It helps traders detect, confirm, and act on directional strength with clarity and confidence.
With Thanks,
Rrahul Desai
@Artharjan
Rolling Performance Toolkit (Returns, Correlation and Sharpe)This script provides a flexible toolkit for evaluating rolling performance metrics between any asset and a benchmark.
Features:
Library-based: Built on a custom utilities library for consistent return and statistics calculations.
Rolling Window Control: Choose the lookback period (in days) to calculate metrics.
Multiple Modes: Toggle between Rolling Returns, Rolling Correlation, and Rolling Sharpe Ratio.
Benchmark Comparison: Compare your selected ticker against a benchmark (default: S&P 500 / SPX), but you can easily switch to any symbol.
Risk-Free Rate Options: Choose from zero, a constant annual % rate, or a proxy symbol (default: US03M – 3-Month Treasury Yield).
Annualized Sharpe: Sharpe ratios are annualized by default (×√252) for intuitive interpretation.
This tool is useful for traders and investors who want to monitor relative performance, diversification benefits, or risk-adjusted returns over time.
Stock Fundamentals Health Map
I came up with this script because, like a lot of us, I was always bugging AI about every ticker under the sun—asking for breakdowns, forecasts, you name it. But then it hit me: wouldn't it be way faster if I could just glance at the stock chart and get a quick snapshot of the company's financial guts right there?. Also, i didnt bother looking up another indicator script because i want it that way.
This "Stock Fundamentals Health Map" is basically your jumping-off point before you go full detective mode on the fundamentals. It's not meant to be the end-all-be-all, just a smart way to spot red flags or green lights without wasting hours.
Here's the deal: TradingView has this treasure of financial stats for stocks—stuff like margins, ratios, growth numbers, and more—pulled from their database after earnings drops. The script grabs 40 of those for your chosen period (Fiscal Year, Quarter, Half, or Trailing Twelve Months—you pick in the settings, and 40 because your broke boy doesnt have a premium TV sub).
But raw numbers? Meh, they're just digits. So, we grade 'em. Think of it like a report card for the company: Excellent (or "Great" in some spots), Good, Fair, Poor, or Weak (I called it "Pathetic" in my head at first, but toned it down).
How do we grade? Based on thresholds for each metric. For instance, a Gross Margin over 60%? Excellent, baby—that's premium efficiency. 40-60%? Solid Good. Down to under 10%? Weak, might wanna think twice. Same logic for everything else: Altman Z-Score (bankruptcy risk—higher is safer), Beneish M-Score (earnings manipulation detector—lower is cleaner), ROE, EV/EBITDA, you get the idea. But hey, maybe you disagree with my defaults. No sweat—the settings let you tweak every single threshold. Want to be stricter on Debt-to-Equity? Crank it up. Think Dividend Yield needs a higher bar for "Excellent"? Go for it. It's your world; I'm just scripting in it.
Dont know what all those metrics mean? Use the tool tip. Still dont understand? Keep the defaults.
Once graded, we don't stop there. Each metric gets a weight (default is 1, for equal love), but if you're obsessed with Free Cash Flow Margin over, say, Asset Turnover, bump its weight to 2, 5, or even 100. FFT FAFO. The script multiplies grades by weights, adds 'em up, and spits out an overall score and grade for the stock. Excellent if it's crushing it (90%+), down to Weak if it's wheezing. Plus, it categorizes the stock type—Growth, Value, Quality, Dividend, Momentum—based on how it scores in those buckets. Handy for knowing if it's a high-flyer or a dead divi.
And because not all stocks are created equal, it throws in sector-specific smarts. REITs get FFO and AFFO grades (funds from operations—key for real estate trusts). Tech and Healthcare? R&D Intensity to check if they're innovating or slacking. Energy folks get Capex-to-Sales (lower is better for efficiency in that capital-hungry world). Utilities? Debt Service Coverage to see if they can handle the bills. If your ticker doesn't fit those, it skips 'em—no junk data. You dont see all that because TV might have that data with N/A entered in it.
The output? A clean table slapped on your chart (top-right by default and cant move it around, because being at the top and being right is all you need). Columns for metrics, values + grades, all color-coded: green for Excellent, lime for Good, yellow Fair, orange Poor, red Weak. Headers in blue, text customizable—pick your colors, transparency, sizes. It's overlay=true, so it vibes with your price action without cluttering.
Sure, these numbers are just what TradingView's crack team inputs post-earnings—could be off, or laggy, or whatever. They don't predict the future; markets are wild. But it's a lot better than panic-buying on a hunch. Gives you that quick financial health map to ponder before you leap into a trade that could change your life... or your portfolio's. ;)
If you need the source code, ask Grok AI. I got it from there. Too lazy to do that? Follow me on X and i'll dm you after you prove that you are not a bot.
RSI+MA by RAThis Indicator generates buy and sell signal on the crossover of RSI and MA, HTF RSI is also plotted for HTF trend.
Gann Squares + Midpoints It gives Gann Square and a midpoint closest to the price which act as support and resistance
Supertrend Long/Short with Adjustable R:R by JJThis script is a Supertrend-based trading tool with:
Long/Short trade signals
Risk/reward calculation
Position sizing based on risk, capital, and max shares
Visual labels for entries, targets, and stops
Checkmarks (✔) for successful trades and crosses (❌) for stopped trades
Alerts for trade entries
It’s designed for visual analysis on charts, helping you see trades, their targets, and whether they hit profit or stop-loss.
High For Loop | MisinkoMasterThe High For Loop is a new Trend Following tool designed to give traders smooth and fast signals without being too complex, overfit or repainting.
It works by finding how many bars have a higher high than the current high, how many have a lower high, and scores it based on that. This provides users with easy and accurate signals, allowing for gaining a large edge in the market.
It is pretty simple but you can still play around with it pretty well and improve uppon your strategies.
For any backtests using strategies, I left many comments and tried to make it as easy as possible to backtest.
Enjoy G´s
Machine Learning : Neural Network Prediction -EasyNeuro-Machine Learning: Neural Network Prediction
— An indicator that learns and predicts price movements using a neural network —
Overview
The indicator “Machine Learning: Neural Network Prediction” uses price data from the chart and applies a three-layer Feedforward Neural Network (FNN) to estimate future price movements.
Key Features
Normally, training and inference with neural networks require advanced programming languages that support machine learning frameworks (such as TensorFlow or PyTorch) as well as high-performance hardware with GPUs. However, this indicator independently implements the neural network mechanism within TradingView’s Pine Script environment, enabling real-time training and prediction directly on the chart.
Since Pine Script does not support matrix operations, the backpropagation algorithm—necessary for neural network training—has been implemented entirely through scalar operations. This unique approach makes the creation of such a groundbreaking indicator possible.
Significance of Neural Networks
Neural networks are a core machine learning method, forming the foundation of today’s widely used generative AI systems, such as OpenAI’s GPT and Google’s Gemini. The feedforward neural network adopted in this indicator is the most classical architecture among neural networks. One key advantage of neural networks is their ability to perform nonlinear predictions.
All conventional indicators—such as moving averages and oscillators like RSI—are essentially linear predictors. Linear prediction inherently lags behind past price fluctuations. In contrast, nonlinear prediction makes it theoretically possible to dynamically anticipate future price movements based on past patterns. This offers a significant benefit for using neural networks as prediction tools among the multitude of available indicators.
Moreover, neural networks excel at pattern recognition. Since technical analysis is largely based on recognizing market patterns, this makes neural networks a highly compatible approach.
Structure of the Indicator
This indicator is based on a three-layer feedforward neural network (FNN). Every time a new candlestick forms, the model samples random past data and performs online learning using stochastic gradient descent (SGD).
SGD is known as a more versatile learning method compared to standard gradient descent, particularly effective for uncertain datasets like financial market price data. Considering Pine Script’s computational constraints, SGD is a practical choice since it can learn effectively from small amounts of data. Because online learning is performed with each new candlestick, the indicator becomes a little “smarter” over time.
Adjustable Parameters
Learning Rate
Specifies how much the network’s parameters are updated per training step. Values between 0.0001 and 0.001 are recommended. Too high causes divergence and unstable predictions, while too low prevents sufficient learning.
Iterations per Online Learning Step
Specifies how many training iterations occur with each new candlestick. More iterations improve accuracy but may cause timeouts if excessive.
Seed
Random seed for initializing parameters. Changing the seed may alter performance.
Architecture Settings
Number of nodes in input and hidden layers:
Increasing input layer nodes allows predictions based on longer historical periods. Increasing hidden layer nodes increases the network’s interpretive capacity, enabling more flexible nonlinear predictions. However, more nodes increase computational cost exponentially, risking timeouts and overfitting.
Hidden layer activation function (ReLU / Sigmoid / Tanh):
Sigmoid:
Classical function, outputs between 0–1, approximates a normal distribution.
Tanh:
Similar to Sigmoid but outputs between -1 and 1, centered around 0, often more accurate.
ReLU:
Simple function (outputs input if ≥ 0, else 0), efficient and widely effective.
Input Features (selectable and combinable)
RoC (Rate of Change):
Measures relative price change over a period. Useful for predicting movement direction.
RSI (Relative Strength Index):
Oscillator showing how much price has risen/fallen within a period. Widely used to anticipate direction and momentum.
Stdev (Standard Deviation, volatility):
Measures price variability. Useful for volatility prediction, though not directional.
Optionally, input data can be smoothed to stabilize predictions.
Other Parameters
Data Sampling Window:
Period from which random samples are drawn for SGD.
Prediction Smoothing Period:
Smooths predictions to reduce spikes, especially when RoC is used.
Prediction MA Period:
Moving average applied to smoothed predictions.
Visualization Features
The internal state of the neural network is displayed in a table at the upper-right of the chart:
Network architecture:
Displays the structure of input, hidden, and output layers.
Node activations:
Shows how input, hidden, and output node values dynamically change with market conditions.
This design allows traders to intuitively understand the inner workings of the neural network, which is often treated as a black box.
Glossary of Terms
Feature:
Input variables fed to the model (RoC/RSI/Stdev).
Node/Unit:
Smallest computational element in a layer.
Activation Function:
Nonlinear function applied to node outputs (ReLU/Sigmoid/Tanh).
MSE (Mean Squared Error):
Loss function using average squared errors.
Gradient Descent (GD/SGD):
Optimization method that gradually adjusts weights in the direction that reduces loss.
Online Learning:
Training method where the model updates sequentially with each new data point.
Artharjan High Volume Zones v2Artharjan High Volume Zones (AHVZ)
The Artharjan High Volume Zones (AHVZ) indicator is designed to identify, highlight, and track price zones formed during exceptionally high-volume bars. These levels often act as critical support and resistance zones, revealing where institutions or large players have shown significant interest.
By combining both short-term (ST) and long-term (LT) high-volume zones, the tool enables traders to align intraday activity with broader market structures.
Core Purpose
Markets often leave behind footprints in the form of high-volume bars. The AHVZ indicator captures these footprints and projects their influence forward, allowing traders to spot zones of liquidity, accumulation, or distribution where future price reactions are likely.
Key Features
🔹 Short-Term High Volume Zones (ST-ZoI)
Identifies the highest-volume bar within a short-term lookback period (default: 22 bars).
Draws and maintains:
Upper & Lower Bounds of the high-volume candle.
Midpoint Line (M-P) as the zone’s equilibrium.
Buffer Zones above and below for intraday flexibility (percentage-based).
Highlights these zones visually for quick intraday decision-making.
🔹 Long-Term High Volume Zones (LT-ZoI)
Scans for the highest-volume bar in a long-term lookback period (default: 252 bars).
Similar plotting structure as ST-ZoI: Upper, Lower, Midpoint, and Buffers.
Useful for identifying institutional footprints and multi-week/month accumulation zones.
🔹 Dynamic Buffering
Daily/Weekly/Monthly charts: Adds a fixed percentage buffer above and below high-volume zones.
Intraday charts: Uses price-range based buffers, scaling zones more adaptively to volatility.
🔹 Visual Customization
Independent color settings for ST and LT zones, mid-range lines, and buffers.
Adjustable plot thickness for clarity across different chart styles.
How It Helps
Intraday Traders
Use ST zones to pinpoint short-term supply/demand clusters.
Trade rejections or breakouts near these high-volume footprints.
Swing/Positional Traders
Align entries with LT zones to stay on the side of institutional flows.
Spot areas where price may stall, reverse, or consolidate.
General Market Structure Analysis
Understand where volume-backed conviction exists in the chart.
Avoid trading into hidden walls of liquidity by recognizing prior high-volume zones.
Closing Note
The Artharjan High Volume Zones indicator acts as a volume map of the market, giving traders a deeper sense of where meaningful battles between buyers and sellers took place. By combining short-term noise filtering with long-term structural awareness, it empowers traders to make more informed, disciplined decisions.
With Thanks,
Rrahul Desai @Artharjan
Clean Zone + SL/TP (Latest Only)📌 Description
Clean Zone + SL/TP (Latest Only) is an indicator designed to highlight the most recent supply or demand zone based on pivot highs/lows, and automatically plot entry, stop loss, and multiple take profit levels.
🔹 Automatic Direction Detection
The script can auto-detect trade direction (Long/Short) using pivot logic, or you can override manually.
🔹 Zone Drawing
Only the latest valid supply (red) or demand (green) zone is displayed.
Zones are extended to the right for a customizable number of bars.
🔹 Entry / SL / TP Levels
Entry, Stop Loss, and TP1/TP2/TP3 levels are plotted automatically.
Targets can be calculated either by zone size or by ATR-based multiples.
Risk/Reward ratios are fully adjustable.
🔹 Customizable Display
Toggle visibility for zones (box), entry/SL/TP lines, and price labels.
Labels show only on the latest bar for a clean chart look.
🎯 Use Case
This tool helps traders quickly identify the cleanest and most recent supply/demand setup and manage trades with predefined risk/reward targets. It’s especially useful for price action traders and those who prefer simple, uncluttered charts.
Artharjan NSE Sectors Relative Strength DashboardArtharjan NSE Sectors Relative Strength Dashboard
This script provides a comprehensive dashboard for analyzing the relative strength of NSE sectors compared to a benchmark index (default: NIFTY). It is designed to give traders and investors a consolidated snapshot of sector performance, momentum, and short-term trend strength — all in one visual table.
Core Purpose
The goal is to simplify sector rotation analysis by combining relative strength, rate of change, momentum, and trend classification into a sortable, color-coded dashboard. Instead of scanning multiple charts, users can rely on this single panel for quick decision-making.
Key Features
Benchmark Comparison
Every sector is measured against the benchmark index (default: NIFTY). This allows users to spot outperforming or underperforming sectors relative to the market.
Multiple Performance Metrics
LTP % Change: Last traded price percentage change from the prior close.
RS Score: Relative strength score over a user-defined lookback.
Momentum (ROC Difference): Convergence/divergence between two ROC values for added confirmation.
ROC1 / ROC2: Short- and medium-term rate-of-change measures.
Trend Classification Engine
Each sector is tagged as Ultra Bullish, Bullish Breakout, Strong/Moderate Bullish, Neutral, Moderate/Strong Bearish, Bearish Breakdown, or Ultra Bearish. This classification is based on sectoral price behavior and candlestick relationships.
Sorting & Customization
Users can sort the dashboard by any metric (e.g., RS Score, % Change, Momentum), in ascending or descending order, to highlight what matters most for their strategy.
Table Presentation
Adjustable text size, thickness, and positioning on the chart.
Optional color-coded cells for visual cues — green shades for strength, red shades for weakness, neutral shades for sideways trends.
“Last Updated” timestamp for clarity on when the snapshot was generated.
How It Helps
This tool reduces the noise of flipping through individual sector charts. Traders can identify sector leadership, monitor momentum shifts, and catch early signs of rotation without leaving a single chart window. It acts as both a macro lens (sector overview) and a micro tool (spotting exact strength/weakness transitions).
Closing Note
This dashboard was built with a simple goal: to bring clarity to complex sectoral movements. Use it as a guiding compass while respecting your broader trading or investing framework.
With Thanks,
Rrahul Desai
@Artharjan
Artharjan Heiken Ashi Super TrendArtharjan Heiken Ashi SuperTrend (AHAST)
The Artharjan Heiken Ashi SuperTrend (AHAST) indicator is a refined version of the classic SuperTrend tool, designed for traders who wish to blend trend-following logic with the smoothing effects of Heiken Ashi candles. This script not only highlights market trends but also introduces multi-timeframe filtering, visual cues, and alerts for sharper decision-making.
🔑 Key Features
Heiken Ashi Integration
Option to calculate trends using standard candles or Heiken Ashi candles.
Provides smoother visualization, reducing noise.
Flexible ATR Calculation
Choose between RMA (default) and SMA for ATR computation.
Option to switch between traditional ATR and Heiken Ashi-based ATR.
Customizable Inputs
ATR length, multiplier factor, trend colors, and higher-timeframe filters are all user-configurable.
Debug mode available for internal verification.
Visual Enhancements
Dynamic background highlighting to clearly distinguish bullish vs bearish phases.
Fill plots that emphasize ongoing trends.
Buy and Sell signal markers with optional on/off toggle.
Multi-Timeframe (MTF) Filter
Fetches higher timeframe (e.g., Weekly) Heiken Ashi values.
Detects bullish and bearish flips on higher timeframe trends.
Overlay highlights to align lower timeframe trades with broader market direction.
Alerts & Automation
Alerts available for:
Buy / Sell triggers
Direction changes
Higher timeframe bullish or bearish flips
Compatible with TradingView alerts for automated workflows.
⚙️ How It Works
Core Trend Logic
The script calculates the median price of Heiken Ashi highs and lows.
SuperTrend bands (up and dn) are adjusted using ATR.
A bullish or bearish state is determined based on price closing above or below these bands.
Signal Generation
Buy Signal: Trend flips from bearish (-1) to bullish (+1).
Sell Signal: Trend flips from bullish (+1) to bearish (-1).
Signals can be plotted as circles, labels, or both depending on configuration.
MTF SuperTrend
Parallel SuperTrend calculation on a higher timeframe (user-selected).
Detects bullish flip (HTF ↑) or bearish flip (HTF ↓).
Highlights the chart background with higher timeframe color filters when enabled.
Debug Mode
Turns on background shading to indicate whether Heiken Ashi or regular candles are in use.
Helps verify internal logic for advanced users.
🎨 Visualization Example
Green Highlight / Fill → Active bullish trend
Red Highlight / Fill → Active bearish trend
Light Blue / Gray Highlights → Higher timeframe bullish / bearish alignment
Buy / Sell Labels → Clear entry or exit cues, aligned with the trend
🚨 Practical Usage
Swing Traders: Use higher timeframe filters (e.g., Weekly) to align intraday signals with broader market direction.
Intraday Traders: Focus on Heiken Ashi smoothing to avoid whipsaws in volatile sessions.
Options Traders: Combine bullish/bearish flips with option strategies (e.g., Calls/Puts) to gain directional exposure.
✅ Final Thoughts
The Artharjan Heiken Ashi SuperTrend (AHAST) is not just another SuperTrend indicator—it’s a versatile trading companion. By merging classic ATR-based logic with Heiken Ashi smoothing and multi-timeframe confirmation, this tool equips traders with early signals, trend clarity, and strong alignment across timeframes.
Use it with discipline, combine it with your trading framework, and let it sharpen your edge in the markets.
With Thanks,
Rrahul Desai
@Artharjan
Artharjan Intraday Trading ZonesArtharjan Intraday Trading Zones (AITZ)
Overview
The AITZ indicator is designed to visually mark intraday trading zones on a chart by using the current day’s High (DH) and Low (DL) as reference points. It creates three distinct market zones:
Bullish Zone: Near the daily high, suggesting strength.
Bearish Zone: Near the daily low, suggesting weakness.
Neutral / No-Trade Zone: Between the bullish and bearish thresholds, where price movement is less directional.
These zones are highlighted with color-fills for quick visual identification, and the indicator automatically resets at the start of each new trading day.
Key Features
Daily Reference Levels: Automatically fetches Day High, Day Low, and uses them to calculate intraday zones.
Configurable Zone Depth: Traders can set the percentage distance from High/Low to define bullish and bearish zones.
Conditional Zone Coloring: Option to highlight zones only when price is actively trading inside them.
Dynamic Updates: Zone coloring adjusts in real time as the day progresses.
Customizable Appearance: Line thickness and zone colors can be adjusted to match chart preferences.
Inputs
Parameter Type Default Description
Level Thickness Integer 1 Thickness of all plotted levels (1–10).
(DH-DL)% below Day High Float 25 Distance from daily high (as % of DH–DL range) to define bullish threshold.
(DH-DL)% above Day Low Float 25 Distance from daily low (as % of DH–DL range) to define bearish threshold.
Plot Zone Colors (Conditional)? Boolean true If enabled, zones are colored only when price trades inside them. Otherwise, they remain visible regardless of price position.
Bullish Zone Color Color Teal (90% transparent) Fill color for bullish zone.
Neutral Zone Color Color Blue (90% transparent) Fill color for neutral/no-trade zone.
Bearish Zone Color Color Maroon (90% transparent) Fill color for bearish zone.
Core Calculations
Zones:
Bullish Zone = between DH and LTL
Bearish Zone = between DL and STL
Neutral Zone = between LTL and STL
Reset Behavior: At the start of each new daily session, old lines are deleted and fresh ones are drawn.
Usage Example
A trader sets:
(DH–DL)% below High = 20%
(DH–DL)% above Low = 20%
If today’s DH = 1000 and DL = 900 (Range = 100):
Bullish threshold = 1000 – (100 × 20%) = 980
Bearish threshold = 900 + (100 × 20%) = 920
Zones:
Bullish Zone: 980 → 1000
Neutral Zone: 920 → 980
Bearish Zone: 900 → 920
This creates clear trade zones for scalpers or intraday directional traders.
Practical Application
Trend Confirmation: If price sustains in the bullish zone, bias stays long.
Weakness Detection: Price falling into the bearish zone signals short opportunities.
Neutral Play: Avoid trades or expect sideways action inside the neutral zone.
Limitations
Works on instruments with clear daily highs/lows (equities, futures, FX).
May repaint levels intraday until the daily high/low is confirmed.
Zones depend on daily volatility—very narrow ranges may cause zones to overlap.
Price Grid (Base/Step/Levels)Price Grid (Base/Step/Levels) is a simple yet powerful tool for visual traders. It automatically draws a customizable grid of horizontal price levels on your chart.
You choose a base price, a grid step size, and the number of levels to display above and below. The indicator then plots evenly spaced lines around the base, helping you:
Spot round-number zones and psychological levels
Plan entries, exits, and stop-loss placements
Visualize support/resistance clusters
Build grid or ladder trading strategies
The base line is highlighted so you always know your anchor level, while the other levels are styled separately for clarity.
⚙️ Inputs
Base price → anchor level (set 0 to use current close price)
Grid step → distance between levels
Number of levels → lines drawn above & below base
Line style / width / colors → full customization
✅ Notes
Works on any market and timeframe
Automatically respects the symbol’s minimum tick size
Lightweight & non-repainting
Martingale Strategy Simulator [BackQuant]Martingale Strategy Simulator
Purpose
This indicator lets you study how a martingale-style position sizing rule interacts with a simple long or short trading signal. It computes an equity curve from bar-to-bar returns, adapts position size after losing streaks, caps exposure at a user limit, and summarizes risk with portfolio metrics. An optional Monte Carlo module projects possible future equity paths from your realized daily returns.
What a martingale is
A martingale sizing rule increases stake after losses and resets after a win. In its classical form from gambling, you double the bet after each loss so that a single win recovers all prior losses plus one unit of profit. In markets there is no fixed “even-money” payout and returns are multiplicative, so an exact recovery guarantee does not exist. The core idea is unchanged:
Lose one leg → increase next position size
Lose again → increase again
Win → reset to the base size
The expectation of your strategy still depends on the signal’s edge. Sizing does not create positive expectancy on its own. A martingale raises variance and tail risk by concentrating more capital as a losing streak develops.
What it plots
Equity – simulated portfolio equity including compounding
Buy & Hold – equity from holding the chart symbol for context
Optional helpers – last trade outcome, current streak length, current allocation fraction
Optional diagnostics – daily portfolio return, rolling drawdown, metrics table
Optional Monte Carlo probability cone – p5, p16, p50, p84, p95 aggregate bands
Model assumptions
Bar-close execution with no slippage or commissions
Shorting allowed and frictionless
No margin interest, borrow fees, or position limits
No intrabar moves or gaps within a bar (returns are close-to-close)
Sizing applies to equity fraction only and is capped by your setting
All results are hypothetical and for education only.
How the simulator applies it
1) Directional signal
You pick a simple directional rule that produces +1 for long or −1 for short each bar. Options include 100 HMA slope, RSI above or below 50, EMA or SMA crosses, CCI and other oscillators, ATR move, BB basis, and more. The stance is evaluated bar by bar. When the stance flips, the current trade ends and the next one starts.
2) Sizing after losses and wins
Position size is a fraction of equity:
Initial allocation – the starting fraction, for example 0.15 means 15 percent of equity
Increase after loss – multiply the next allocation by your factor after a losing leg, for example 2.00 to double
Reset after win – return to the initial allocation
Max allocation cap – hard ceiling to prevent runaway growth
At a high level the size after k consecutive losses is
alloc(k) = min( cap , base × factor^k ) .
In practice the simulator changes size only when a leg ends and its PnL is known.
3) Equity update
Let r_t = close_t / close_{t-1} − 1 be the symbol’s bar return, d_{t−1} ∈ {+1, −1} the prior bar stance, and a_{t−1} the prior bar allocation fraction. The simulator compounds:
eq_t = eq_{t−1} × (1 + a_{t−1} × d_{t−1} × r_t) .
This is bar-based and avoids intrabar lookahead. Costs, slippage, and borrowing costs are not modeled.
Why traders experiment with martingale sizing
Mean-reversion contexts – if the signal often snaps back after a string of losses, adding size near the tail of a move can pull the average entry closer to the turn
Behavioral or microstructure edges – some rules have modest edge but frequent small whipsaws; size escalation may shorten time-to-recovery when the edge manifests
Exploration and stress testing – studying the relationship between streaks, caps, and drawdowns is instructive even if you do not deploy martingale sizing live
Why martingale is dangerous
Martingale concentrates capital when the strategy is performing worst. The main risks are structural, not cosmetic:
Loss streaks are inevitable – even with a 55 percent win rate you should expect multi-loss runs. The probability of at least one k-loss streak in N trades rises quickly with N.
Size explodes geometrically – with factor 2.0 and base 10 percent, the sequence is 10, 20, 40, 80, 100 (capped) after five losses. Without a strict cap, required size becomes infeasible.
No fixed payout – in gambling, one win at even odds resets PnL. In markets, there is no guaranteed bounce nor fixed profit multiple. Trends can extend and gaps can skip levels.
Correlation of losses – losses cluster in trends and in volatility bursts. A martingale tends to be largest just when volatility is highest.
Margin and liquidity constraints – leverage limits, margin calls, position limits, and widening spreads can force liquidation before a mean reversion occurs.
Fat tails and regime shifts – assumptions of independent, Gaussian returns can understate tail risk. Structural breaks can keep the signal wrong for much longer than expected.
The simulator exposes these dynamics in the equity curve, Max Drawdown, VaR and CVaR, and via Monte Carlo sketches of forward uncertainty.
Interpreting losing streaks with numbers
A rough intuition: if your per-trade win probability is p and loss probability is q=1−p , the chance of a specific run of k consecutive losses is q^k . Over many trades, the chance that at least one k-loss run occurs grows with the number of opportunities. As a sanity check:
If p=0.55 , then q=0.45 . A 6-loss run has probability q^6 ≈ 0.008 on any six-trade window. Across hundreds of trades, a 6 to 8-loss run is not rare.
If your size factor is 1.5 and your base is 10 percent, after 8 losses the requested size is 10% × 1.5^8 ≈ 25.6% . With factor 2.0 it would try to be 10% × 2^8 = 256% but your cap will stop it. The equity curve will still wear the compounded drawdown from the sequence that led to the cap.
This is why the cap setting is central. It does not remove tail risk, but it prevents the sizing rule from demanding impossible positions
Note: The p and q math is illustrative. In live data the win rate and distribution can drift over time, so real streaks can be longer or shorter than the simple q^k intuition suggests..
Using the simulator productively
Parameter studies
Start with conservative settings. Increase one element at a time and watch how the equity, Max Drawdown, and CVaR respond.
Initial allocation – lower base reduces volatility and drawdowns across the board
Increase factor – set modestly above 1.0 if you want the effect at all; doubling is aggressive
Max cap – the most important brake; many users keep it between 20 and 50 percent
Signal selection
Keep sizing fixed and rotate signals to see how streak patterns differ. Trend-following signals tend to produce long wrong-way streaks in choppy ranges. Mean-reversion signals do the opposite. Martingale sizing interacts very differently with each.
Diagnostics to watch
Use the built-in metrics to quantify risk:
Max Drawdown – worst peak-to-trough equity loss
Sharpe and Sortino – volatility and downside-adjusted return
VaR 95 percent and CVaR – tail risk measures from the realized distribution
Alpha and Beta – relationship to your chosen benchmark
If you would like to check out the original performance metrics script with multiple assets with a better explanation on all metrics please see
Monte Carlo exploration
When enabled, the forecast draws many synthetic paths from your realized daily returns:
Choose a horizon and a number of runs
Review the bands: p5 to p95 for a wide risk envelope; p16 to p84 for a narrower range; p50 as the median path
Use the table to read the expected return over the horizon and the tail outcomes
Remember it is a sketch based on your recent distribution, not a predictor
Concrete examples
Example A: Modest martingale
Base 10 percent, factor 1.25, cap 40 percent, RSI>50 signal. You will see small escalations on 2 to 4 loss runs and frequent resets. The equity curve usually remains smooth unless the signal enters a prolonged wrong-way regime. Max DD may rise moderately versus fixed sizing.
Example B: Aggressive martingale
Base 15 percent, factor 2.0, cap 60 percent, EMA cross signal. The curve can look stellar during favorable regimes, then a single extended streak pushes allocation to the cap, and a few more losses drive deep drawdown. CVaR and Max DD jump sharply. This is a textbook case of high tail risk.
Strengths
Bar-by-bar, transparent computation of equity from stance and size
Explicit handling of wins, losses, streaks, and caps
Portable signal inputs so you can A–B test ideas quickly
Risk diagnostics and forward uncertainty visualization in one place
Example, Rolling Max Drawdown
Limitations and important notes
Martingale sizing can escalate drawdowns rapidly. The cap limits position size but not the possibility of extended adverse runs.
No commissions, slippage, margin interest, borrow costs, or liquidity limits are modeled.
Signals are evaluated on closes. Real execution and fills will differ.
Monte Carlo assumes independent draws from your recent return distribution. Markets often have serial correlation, fat tails, and regime changes.
All results are hypothetical. Use this as an educational tool, not a production risk engine.
Practical tips
Prefer gentle factors such as 1.1 to 1.3. Doubling is usually excessive outside of toy examples.
Keep a strict cap. Many users cap between 20 and 40 percent of equity per leg.
Stress test with different start dates and subperiods. Long flat or trending regimes are where martingale weaknesses appear.
Compare to an anti-martingale (increase after wins, cut after losses) to understand the other side of the trade-off.
If you deploy sizing live, add external guardrails such as a daily loss cut, volatility filters, and a global max drawdown stop.
Settings recap
Backtest start date and initial capital
Initial allocation, increase-after-loss factor, max allocation cap
Signal source selector
Trading days per year and risk-free rate
Benchmark symbol for Alpha and Beta
UI toggles for equity, buy and hold, labels, metrics, PnL, and drawdown
Monte Carlo controls for enable, runs, horizon, and result table
Final thoughts
A martingale is not a free lunch. It is a way to tilt capital allocation toward losing streaks. If the signal has a real edge and mean reversion is common, careful and capped escalation can reduce time-to-recovery. If the signal lacks edge or regimes shift, the same rule can magnify losses at the worst possible moment. This simulator makes those trade-offs visible so you can calibrate parameters, understand tail risk, and decide whether the approach belongs anywhere in your research workflow.
