Trading Risk Lab Risk of Ruin Calculator

Simulation Parameters

Monte Carlo simulation (simplified win/loss model) for drawdown distribution

Simulation Model

Simplified: fixed win size (+Avg Win R) and fixed loss size (−Avg Loss R) with a constant win rate. Useful for quick intuition, but it ignores variability between trades.

Monte Carlo (modeled): each trade is a win or loss by your Win Rate, but the size of wins/losses is randomly sampled around your averages (using your variability settings). Better for modeling dispersion and tail risk.

Historical: paste your real trade outcomes as R‑multiples. The simulator bootstraps by sampling from your list (with replacement). This keeps your real skew/outliers and is usually the most realistic mode.

Available Equity ($) Starting capital used only to convert simulated multipliers into $ terms. The simulation itself uses proportional returns; real results can differ due to fees, slippage, and changing position sizes.

Win Rate % Assumed win rate for the simplified model. Real win rates vary over time and depend on execution, market regime, and sample size.

Average Win (R) Assumed average win in R (reward relative to the amount risked). Real trades have dispersion; this tool uses a fixed average for simplicity.

Average Loss (R) Assumed average loss in R. Real losses can vary (slippage, gaps, partial fills). This tool uses a fixed average for simplicity.

Simplified model: fixed win size (+Average Win) and fixed loss size (-Average Loss) with a constant Win Rate.

Win Variability % Standard deviation as a % of Average Win. Example: Avg Win 2R and 50% variability implies SD≈1R (before min/max clamping). Higher values produce more dispersion and more tail outcomes.

Loss Variability % Standard deviation as a % of Average Loss. Many strategies have tighter losses (e.g., 10–30%) and wider wins.

Sampling Shape

Normal (resampled)
Log-normal (wins right-tail)

Min Win (R)

Max Win (R)

Max Loss (R)

Tip: If you don’t want variable losses, set Loss Variability to 0%. If your losses are hard-stopped near -1R, you can set Max Loss (R) to 1.0.

Historical Monte Carlo: paste your trade outcomes in R-multiples (one per line or comma-separated). Example: 2.1, -1, 0.4, -0.8, 3.6. The simulator bootstraps by sampling from this list with replacement.

Historical outcomes (R-multiples) Paste realized R outcomes (positive wins, negative losses). You can include partials (e.g., +0.3R) and oversized losses (e.g., -1.7R). The tool will compute win rate and average win/loss from your list.

Number of Trades (per iteration) Number of trades simulated per run. Results are sensitive to sample size; fewer trades means more uncertainty.

Iterations (higher = smoother) Number of Monte Carlo runs. Higher values smooth percentiles but do not make the model more realistic.

Risk Per Trade % (of equity) Percent of current equity risked per trade (compounded position sizing). Higher risk increases both growth potential and drawdown/ruin risk.

Ruin at Equity % (stop simulation) Equity level that ends a run if reached (counts as 'threshold hit'). This is a risk-control proxy, not a real broker liquidation model.

Comparison Mode

Comparison mode

Scenario B Inputs

Win Rate %

Average Win (R)

Average Loss (R)

Risk Per Trade %

Monte Carlo Visualizations

Equity Path Cloud

Many simulated equity paths (transparent) + median / 10–90% band (estimated from sampled paths)

Shows many simulated equity curves in dollars. The green line is the median path; the blue shading is the 10th–90th percentile band. If risk% is high, the chart may automatically switch to a log scale to stay readable.

Ruin Probability Curve

Cumulative chance of touching your ruin threshold by trade #

At each trade number, this shows the % of simulations that have already hit your “Ruin at Equity %” threshold at least once (cumulative). It helps you see *when* the risk tends to materialize over the trade horizon.

Max Drawdown Distribution

Histogram of worst peak-to-trough drawdowns per run

Histogram of the worst peak‑to‑trough drawdown (%) from each simulated run. This helps you see how often the strategy experiences deep drawdowns.

Final Equity Distribution

Histogram of ending equity ($) across runs

Histogram of ending account equity ($) across runs. A wide distribution means outcomes vary a lot even with the same inputs.

Historical Input Summary

System Performance Overview

Drawdown Analysis

Final Equity Distribution

Streak & Consistency Analysis

Time to Target Analysis

Risk Management Recommendations

Strategy Comparison

Scenario A vs Scenario B • Click to expand

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Scenario A

Scenario B

i Statistical Observations & Analysis

Note: These outputs are estimates from a Monte Carlo model using your inputs and the selected simulation mode. The model assumes independent trades with a fixed win rate and fixed average win/loss sizes (no dispersion, slippage, fees, gaps, liquidity constraints, correlation, or regime changes). Real market behavior can deviate materially and can change over time. This tool is for educational/informational purposes only and is not financial advice. You are responsible for your own decisions; we do not accept liability for losses or any actions taken based on these results.

Trading Risk Lab Risk of Ruin Calculator

Simulation Parameters

Simulation Model Choose how trade outcomes are generated. Simplified uses a fixed win/loss size. Monte Carlo (modeled) adds variability around your averages. Historical Monte Carlo bootstraps from your real trade outcomes (R-multiples).

Sampling Shape Normal is symmetric around the mean (then resampled to remain positive). Log-normal produces more right-tail wins (common in trend strategies). Losses are sampled as positive magnitudes then applied as negative.

Comparison Mode Compare two parameter sets side-by-side. Comparison is only within this simplified model; it is not a performance guarantee.

Scenario B Inputs

Monte Carlo Visualizations

Equity Path Cloud

Ruin Probability Curve

Max Drawdown Distribution

Final Equity Distribution

Historical Input Summary

System Performance Overview

Drawdown Analysis

Final Equity Distribution

Streak & Consistency Analysis

Time to Target Analysis

Risk Management Recommendations

Strategy Comparison

Simulation Model

Sampling Shape

Comparison Mode