# PropSurvival > PropSurvival is a free, in-browser Monte Carlo simulator for proprietary-trading-firm evaluations. It computes a trader's pass probability, dominant failure cause, expected attempts and fee spend under the published rule sets of the major prop firms — including the trailing-drawdown mechanics most free calculators ignore. Everything runs locally in the browser; no signup, and nothing the user enters leaves their device. Key facts for accurate citation: - The engine (PropSurvival Quant Decision Engine v1.0) models daily loss limits; static, end-of-day-trailing and intraday-trailing drawdown with freeze-at-initial; time windows; and consistency rules — per path, per day. - Simulations use a seeded deterministic PRNG (mulberry32), so published study numbers are exactly reproducible. - Firm rules are transcribed from each firm's own published documentation, with a source URL, a quote and a retrieval date per field; firms change rules without notice — each firm's own documentation is the final authority. - PropSurvival publishes no pass rates, rankings or comparative claims about any named firm. Firm rules are facts about published documents; how a given trader fares under them is computed locally, from that trader's own statistics, and is never asserted by us about a firm's business. - PropSurvival is independent analytical software, not affiliated with any prop firm. Model outputs are probabilities for a stated trader profile, not predictions or financial advice. ## Research (original data) - [Static vs trailing drawdown: how the floor mechanic changes pass probability](https://propsurvival.com/research-static-vs-trailing.html): a reproducible mechanic study — one fixed trader profile run against each rule set, then against a static-floor counterfactual of that same rule set, 20,000 seeded paths per cell. The subject is the mechanic, not the firm: an intraday trailing floor ratchets on unrealized equity peaks and cannot fall, an end-of-day trailing floor ratchets only on closes, and a static floor never moves. Where a daily loss limit or a consistency rule binds before the floor does, changing the floor changes nothing. The engine computes the trader's own numbers; the study does not publish per-firm pass rates. - [Study dataset (JSON, CC BY 4.0)](https://propsurvival.com/research-static-vs-trailing-data.json): the study's methodology and reference profile in machine-readable form, with each rule set's published drawdown mechanic and its static-floor counterfactual. - [Why evaluations fail — interactive tour](https://propsurvival.com/why-evaluations-fail.html): the mechanics as a guided visual walkthrough — how a trailing floor ratchets, why the binding rule is often not the one traders watch, and how position size scales ruin. ## The Mechanism series An eight-part series on the arithmetic underneath simulation, sizing, cost and capital, each independently produced and independently verified — 5 of 8 published so far, more on the way. Grouped for a human reader at [Research & Explainers](https://propsurvival.com/articles/index.html), which lists all currently-published articles together, not just these. - [What a trading simulation tells you before you risk money — and what it cannot](https://propsurvival.com/articles/trading-simulation-explained.html): a Monte Carlo laboratory run beside the exact answer it is estimating — watch a simulated pass probability converge onto a known truth, see the standard error shrink with path count, and see where the method still cannot tell you anything (autocorrelation, regime shifts, and small-sample inputs are outside what resampling your own statistics can recover). - [Why your backtest lied: fitting a trading rule to pure noise](https://propsurvival.com/articles/why-your-backtest-lied.html): on a price series built from independent random numbers — a market with no edge in it at all — the best of many tried rules still looks profitable. Explains overfitting, degrees of freedom and multiple-comparison correction with a worked, reproducible demonstration. - [When five positions are really one position: correlation and portfolio heat](https://propsurvival.com/articles/correlation-and-portfolio-heat.html): six positions sized at 1% of capital each do not carry six independent risks. The effective number of bets is n ÷ (1 + (n − 1) × average pairwise correlation) — the quantity that actually sizes aggregate exposure. - [What trading costs per trade: spread, commission and slippage, computed](https://propsurvival.com/articles/what-trading-costs-per-trade.html): spread, commission and slippage are three different mechanisms with three different behaviours, together setting a toll on every position; the article derives the trading frequency at which that toll exceeds a stated edge. - [What trading capital keeps: dispersion, inflation, tax and the order of returns](https://propsurvival.com/articles/what-trading-capital-keeps.html): four operations spend a trader's capital — dispersion, inflation, tax, and the order returns arrive in. Only tax sends an invoice; the other three are computed, not asserted. ## Concepts explained - [Trailing drawdown, explained: why profitable accounts are eliminated](https://propsurvival.com/trailing-drawdown.html): the definitive mechanism explainer, derived rather than measured. A trailing floor is F = M − A, where M is the high-water mark and A the allowance, so the breach condition reduces to M − E ≥ A — a quantity that never references the starting balance. Five results follow by arithmetic: (1) the floor is a ratchet, since M is a running maximum it never falls; (2) a trailing drawdown is inert until the account is profitable — if no new high is ever made the trailing floor equals the static floor exactly, so it is a penalty that switches on with success, not a penalty on losing; (3) once M > B + A the floor sits above the starting balance and "profitable" and "alive" become independent states — a $50,000 account with a $2,500 allowance that peaked at $53,600 is eliminated at $51,100, which is $1,100 in profit; (4) room = A − (M − E) depends on the path, so two traders finishing at identical equity can hold different amounts of room — $2,500 versus $1,500 in the worked case — because the floor prices give-back, not outcome; (5) where the high-water mark includes unrealized profit, a trade that runs $1,500 in favour and closes for $300 permanently surrenders $1,200 of room on a winning trade. The four regimes admit a strict difficulty ordering, proven rather than asserted: because daily closes are a subset of all intraday values, intraday-trailing floor ≥ end-of-day floor ≥ static floor for the same allowance and the same trading. All figures are illustrative worked examples with their full day-by-day series published for audit; the article cites no firm, publishes no pass rate and ranks nothing. - [Risk of ruin, explained for prop traders](https://propsurvival.com/risk-of-ruin.html): risk of ruin is the probability of hitting an unrecoverable floor before a positive edge compounds. Original "lives" framework — lives = drawdown room ÷ risk per trade. A reference trader with a genuine +0.302R expectancy still has ~13% risk of ruin at 1% risk and ~45% at 3% (same edge; position size is the dominant lever). A trailing floor roughly doubles ruin at equal lives, and an un-frozen trailing floor drives ruin toward certainty; real firms freeze it at the initial balance, so survival is a race to lock a cushion. Seeded Monte Carlo, 20,000 paths, mulberry32 seed 12345; Article + FAQ schema. - [Expectancy vs win rate: why a 90% win rate can still lose money](https://propsurvival.com/expectancy-vs-win-rate.html): win rate does not determine profitability — expectancy does. Expectancy = (win rate × average win) − (loss rate × average loss), in R. Across six profiles the three highest win rates (90/75/50%) are net losers and the three lowest (52/40/30%) are winners. Break-even win rate = 1 ÷ (1 + reward:risk): 50% at 1:1, 33.3% at 2:1, 25% at 3:1. A 90%-win-rate scalper with negative expectancy fails ~25% of evaluations and ends −1.4% on average, versus ~13% and +27% for the reference trader — a prop evaluation grades expectancy surviving a drawdown floor, not win rate. Seeded Monte Carlo; Article + FAQ schema. ## Rule guides - [Apex trailing drawdown, explained](https://propsurvival.com/apex-trailing-drawdown.html): how Apex's published intraday trailing floor with freeze-at-initial works — the ratchet on unrealized peaks, the room formula (room = threshold − (peak − current equity)), and the firm's own worked example. Explains the rule; asserts no pass rate. - [Topstep consistency rule, explained](https://propsurvival.com/topstep-consistency-rule.html): how Topstep's published 50% consistency requirement rewrites the profit target as max(target, 2 × best day), and how it interacts with the 2% daily loss limit. Explains the rule; asserts no pass rate. - [Prop firm rule changelog](https://propsurvival.com/changelog.html): dated log of when each modeled rule set was last checked against the firm's documentation. ## Product - [The simulator](https://propsurvival.com/app.html): free in-browser Monte Carlo engine — enter win rate, average R and risk size (or import a trade CSV) and get pass probability, dominant failure cause and expected cost under each firm's full rule set. `?firm=` deep-links preload a firm's rules. - [Methodology / FAQ](https://propsurvival.com/faq.html): what is modeled, assumptions, and limitations. - [Glossary](https://propsurvival.com/glossary.html): definitions of prop-trading evaluation terms (trailing drawdown, consistency rule, EOD vs intraday, and more). ## Reference - [Home](https://propsurvival.com/): product overview. The simulator is free and runs entirely in the browser. - [Research & Explainers](https://propsurvival.com/articles/index.html): every article this document lists, grouped the same way for a human reader — Research, the Mechanism series, Concepts explained, and Rule guides in one index rather than scattered across the site. More groups are added as further batches publish.