Monte Carlo Equity Curve Simulator
A Monte Carlo equity simulator checks a pasted list or selected CSV return column, then resamples those percentage returns into 5,000 reproducible paths. It charts terminal-equity bands, drawdown and horizon/floor sensitivity under one conditional model; it does not forecast future performance.
Paste returns or import one CSV column
Use 10 to 1,000 same-basis percentage returns. Keep frequency, costs, strategy definition and observation selection consistent; 1 means 1%, not 0.01%.
A positive starting amount used only to scale the hypothetical paths.
Choose a plain number list or one explicit column from CSV/TSV rows.
For CSV/TSV only: enter the 1-based column containing signed percentage returns.
The entered horizon. The sensitivity table also evaluates half and double this horizon within the 1,000-trade cap.
The primary floor. Sensitivity also checks 10 percentage points below and above it, within the valid range.
Plain list: commas, new lines, tabs or semicolons. CSV/TSV: select the explicit return column. A trailing % sign is accepted.
- Choose the format, paste returns or import a local file, then check the sample.
Conditional path distribution
Monte Carlo Analysis 1.1.0 · sample parser 1.0.0.
Seeded equity percentile fan
Path percentiles at up to 21 trade checkpoints through the entered horizon.
The terminal table stays two-column on mobile. Sensitivity tables can be scrolled horizontally when needed.
| Terminal percentile | Equity |
|---|
Horizon sensitivity
Same seeded path prefixes at the shorter, entered and longer trade counts.
| Scenario | Trades | P5 equity | Median | P95 equity | P95 max DD | Floor hit |
|---|
Floor sensitivity
Entered-horizon path minima checked at three displayed equity thresholds.
| Floor (% of start) | Floor equity | Paths touching floor |
|---|
How the Monte Carlo equity paths are calculated
Drawdown = (Running peak − Current equity) ÷ Running peak × 100
Each trade draws one entered return with replacement
Analysis version 1.1.0 derives a deterministic seed from the normalized inputs and a separate deterministic seed for each path. A Mulberry32 generator selects one index from the checked return sample for every simulated trade. Because selection is with replacement, an observation can appear repeatedly or not at all.
Every path compounds from the same entered starting equity. The engine records path-equity checkpoints through the entered horizon, retains each path’s deepest running-peak drawdown and applies disclosed Type-7 linear interpolation to the 5,000 sorted values.
Shorter, entered and longer horizon rows reuse the same path prefixes. Floor sensitivity rechecks each entered-horizon path minimum at the displayed thresholds. These comparisons isolate the selected horizon or floor inside this model; they do not measure parameter uncertainty or future risk.
Worked example from the audited fixture
The audited constant-return fixture starts at 1,000, enters ten observations of +10%, samples three trades per entered path and uses a 50% floor.
- Every draw is +10%, so the one-, three- and six-trade median sensitivity values are 1,100, 1,331 and 1,771.561. At the entered three-trade horizon, every terminal percentile is 1,331.
- Equity never falls below its running peak, so both maximum-drawdown percentiles are 0%. No entered-horizon path ends below start or touches the displayed 40%, 50% or 60% floors.
Reproduce it: select “Load audited example” above. The engine retains full precision and rounds only visible output.
How to interpret the result
- The median terminal value is the middle of the 5,000 seeded endpoints, not the most likely future account value.
- The 5th and 95th terminal percentiles show the central 90% span of this simulated set. They are not a confidence interval for actual future equity.
- The fan chart joins discrete path percentiles at up to 21 checkpoints. It does not show individual account paths or a continuous probability surface.
- Horizon and floor sensitivity change one displayed assumption at a time inside the same seeded path-prefix set. They do not identify an optimal horizon or safe floor.
- The 95th-percentile maximum drawdown is exceeded by about 5% of these simulated path maxima under this seed and model. It is not the maximum possible loss.
- A zero floor-hit percentage means none of the 5,000 modeled paths touched the entered floor. It does not prove that a real account cannot do so.
Assumptions and limits
- Sampling individual returns with replacement does not preserve autocorrelation, volatility clustering, trade grouping or regime order.
- The CSV/TSV checker validates the selected cells and basic counts only; it cannot detect omitted, duplicated, cherry-picked or misclassified trades.
- The model does not add spread, commission, financing, slippage or gaps unless those effects are already represented consistently in every entered return.
- A selected or incomplete sample can make every output misleading even when the arithmetic is correct.
- Five thousand seeded paths produce a reproducible finite estimate, not an exhaustive probability distribution.
- No risk fraction, position size, optimal setting, profitability forecast, quality grade, signal or recommendation is produced.
Monte Carlo vs bootstrap vs walk-forward efficiency
These tools answer separate questions. Monte Carlo summarizes hypothetical resampled paths, bootstrap estimates uncertainty around one entered statistic, and walk-forward efficiency compares entered IS and OOS rates. None substitutes for audited records, a documented test design or execution evidence.
| Measure | Evidence entered | Question answered | Main boundary |
|---|---|---|---|
| Monte Carlo equity | Entered percentage returns | Seeded terminal-equity and drawdown path distribution | Not a forecast or exhaustive loss boundary. |
| Bootstrap expectancy | Entered signed outcomes | Percentile interval for resampled arithmetic means | Not a next-trade prediction interval. |
| Walk-forward efficiency | Entered IS and OOS window results | Aggregate OOS result rate divided by aggregate IS result rate | Not an optimisation or robustness verdict. |
| Risk of ruin | Assumed win rate, payoff and fixed risk | Finite-horizon threshold-hit estimate | A separate parametric two-outcome model. |
Frequently asked questions
- It checks 10 to 1,000 entered percentage returns, samples them with replacement, compounds 5,000 seeded hypothetical paths and summarizes terminal equity, maximum drawdown and sensitivity results.
- No. The output is conditional on the entered sample, horizon, seed and resampling method and is not a real-world forecast.
- Yes. Choose CSV or TSV column mode and enter the one-based column containing signed percentage returns. The checker can skip one text header, validates every selected cell and processes imported files locally in the browser.
- The page reports rows used, positive, negative and breakeven counts, distinct values, range, mean, blank rows and basic warnings. It cannot detect omitted, duplicated, selected or misclassified trades.
- Analysis version 1.1.0 hashes normalized inputs into a fixed 32-bit analysis seed and derives one seed per path, so identical inputs reproduce the same 5,000 paths and sensitivity rows.
- Every simulated trade draws one observation from the entered return pool, and the same observation can appear repeatedly or not at all in one path.
- It is the Type-7 95th percentile of the 5,000 path-level maximum drawdown values, not the maximum possible future loss.
- It means none of the 5,000 modeled paths reached the entered equity floor; it does not prove a real account cannot reach it.
- Use the rows to see how the same conditional model changes at half, entered and double trade horizons and at nearby floor thresholds. They do not identify an optimal horizon or safe floor.
- No. Individual-return resampling does not preserve original ordering, serial dependence, trade groups or changing market regimes.
- No. Risk of Ruin is a separate parametric fixed-fraction two-outcome model; this page resamples an empirical percentage-return pool.
Sources and methodology
- Trading Blox — Monte Carlo simulations — Documents equity-curve reordering and sampling-with-replacement methods.
- CFTC — Commodity trading systems — Official warning about the inherent limitations of hypothetical trading results.
The immutable implementation contract fixes the seed, resampling count, quantile convention, duration weighting, invalid states and permanent exclusions so later copy or layout edits cannot silently alter the arithmetic.
Continue the path-risk review
Verify the execution records behind your sample
Before treating any return, outcome or window result as net and comparable, confirm which spread, commission, financing, conversion and execution conventions apply to the broker entity and account used. These browser calculations do not retrieve statements or certify that entered records are complete.
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