challenge_sim — monte-carlo — 120×32

whoami --strategy

Prop Challenge Pass-Probability Simulator

Monte-Carlo engine · win-rate × R:R against real prop-firm rules. Starts with the current FTMO 1-Step objectives; choose another preset or edit every rule.

challenge rules

FTMO 1-Step also applies the Best Day rule: the best profitable day must be no more than 50% of total positive-day profit.

PROFIT_TARGET 10%

MAX_LOSS 10%

DAILY_LOSS 3%

MAX_LOSS_MODE

MIN_TRADING_DAYS0

Best Day ≤ 50% of positive-day profit

your strategy

WIN_RATE 65%

REWARD : RISK 1 : 1

RISK_PER_TRADE 1.0%

FTMO's own guidance caps this near 1%. Slide down to see how sizing alone changes survival odds.

TRADES_PER_DAY 1

HORIZON (days) 30

Trading days simulated before a run is marked timeout — match to your challenge's time limit, if any.

SIM_RUNS

simulation output

Pass probability

—

hits target before any breach

Fail · max loss

—

equity ≤ max loss floor

Fail · daily loss

—

single day exceeds limit

Timeout

—

no breach, no target yet

sample equity paths (40 of N runs)

pass max loss daily loss timeout

./verdict.sh

Awaiting first run

Expectancy / trade —

Avg. days to target (passes only) —

Full-Kelly optimal risk (reference only) —

Assumptions: trades are independent Bernoulli outcomes; each simulated trade is opened and closed within the same modeled trading day. Daily loss is tested against start-of-day balance and includes simulated intraday equity. FTMO 1-Step max loss trails only from the highest end-of-day balance; FTMO 2-Step uses a static floor. Position risk stays fixed, with no compounding, slippage, spread, commission, swaps, or martingale. WMT NoPC–EU uses a fixed 4% floor and a 1% trade-idea cap; overnight equity and official payout approval are not modeled.

audit --weekly --closed-trades

Prop Firm Journey Audit

Upload your latest Myfxbook CSV once a week. The audit answers the right early-stage question: “Has this forward test breached the selected plan’s objectives?” Everything runs locally in your browser—no API, account login, or upload to a server.

Awaiting CSV · select evaluation rules and load a statement

Upload the latest cumulative Myfxbook statement.
The result will distinguish no failure found from fully verified.

Status language: “No failure found” means the imported closed-trade history has not crossed a calculated plan floor. “Cannot fully verify” means the file lacks tick-by-tick floating equity, so it is not proof of official compliance. “Failed” is shown only when the CSV itself contains a clear breach.

diagnose --closed-trades

Quant Trade Analysis

Deep diagnostics from the uploaded Myfxbook history. Measured facts and inferred behavior are separated so weak evidence is not presented as certainty.

likely trading style

Waiting for trade history

Style inference confidence

quant diagnosis

—

Kelly criterion · empirical sizing cross-check

Uses the imported closed trades—not the simulator inputs. Full Kelly maximizes theoretical long-run log growth under stable, independent outcomes; it is not a prop-firm risk recommendation.

WHAT IF · Kelly historical replay

Historical outcome order · selected prop firm audit rules

Replays the imported sequence using its observed average winner-to-loser payoff. A win earns Kelly fraction × observed payoff; a loss costs the Kelly fraction. Selected-plan outcome markers identify where a challenge would stop; later trades in the full-history view are hypothetical.

Risk amount based on Show

Equity paths

Indexed to 100

Drawdown paths

Peak-to-trough percentage

Strategy fingerprints

Pattern matches, not declarations of intent. Market-price context is not present in the CSV.

Trade-return distribution

Histogram + fitted normal curve

Observed tradesNormal modelMean and σ bands

Rolling edge

5-trade expectancy + cumulative P/L

Cumulative P/L5-trade expectancy

Drawdown underwater

Distance below prior closed-equity peak

Closed-trade drawdown

Lot size versus outcome

Risk sizing relationship

WinnerLoser

Holding time versus outcome

Exit-behavior relationship

WinnerLoser

MAE versus MFE

Trade pain, opportunity and exit capture

Winning closeLosing close1:1 excursion line

Edge and payoff structure

Return distribution and tail risk

Direction and holding behavior

Timing and session profile

Stability and regime checks

Risk behavior and sizing discipline

Deep insights

Advanced Quant Lab

Prop survival · edge stability · sequence and behavior stress

All modules recalculate from the uploaded closed-trade history. Simulated results are diagnostic ranges—not forecasts—and floating-equity breaches cannot be fully reconstructed from a closed-trade CSV.

Robustness checks · PyBroker-inspired

Does the edge survive clustered days, later periods and extra execution costs? All P/L metrics here use percentages of initial capital.

Trading-day block bootstrap

Consecutive 3-day blocks preserve within-day trade order and some local dependence. Intervals use percentile resampling of net closed P/L, not PyBroker’s per-bar BCa method. Positive-resample share is not the probability that your strategy has a true edge.

Chronological edge validation

First half of active closing days forms the initial baseline; the remaining days form three non-overlapping test periods. No model fitting or parameter selection occurs. Previously viewed history is not untouched out-of-sample evidence.

Execution-cost stress · selected evaluation rules

Extra cost per trade · % of initial capital

Compare recorded costs with this extra amount and double this amount. Each scenario replays the shared daily, total-loss, consistency and realized trade-idea rules; floating equity remains unavailable.

Monte Carlo survival

Bootstrap fan · 10th–90th percentile

Risk versus outcome

Pass and breach probabilities

Rolling edge stability

Rolling expectancy and win rate

Sequence dependency

Shuffled maximum-drawdown distribution

Outcome dependence

Conditional win rate and streak structure

Daily rule pressure

Closed-P/L consumption of daily limit

Prop survival scenarios

Confidence and sample quality

Outlier dependency stress

Time to target versus failure

Behavioral risk detector

Exposure concentration

MAE/MFE and exit efficiency

Best-day and rule management

Quant action board

whoami --position-size

XAU/USD Lot Size Calculator

Risk-based position sizing plus the survival math prop-firm evaluations actually hinge on: streak odds, Kelly cross-check, trading costs, and a derisk rule. Enter your numbers below.

Advanced mode Adds trading costs, win-rate/R:R edge, streak & Kelly math, DD type, portfolio exposure cap, risk step-down, and the pre-trade checklist.

account & risk

CURRENT_BALANCE

Closed-trade balance right now. Selecting an account-size button resets all live account-state fields to that starting value.

live account state

INITIAL_CAPITAL

CURRENT_EQUITY

DAY_START_BALANCE

HIGHEST_EOD_BALANCE

Equity includes floating P/L, commissions and swaps. FTMO resets at 00:00 CE(S)T.

MAX_BUFFER_USE_PER_TRADE20%

Veteran safety cap: one stopped trade may consume at most this share of the tighter remaining plan buffer.

RISK_PER_TRADE 0.5%

Keep this at or below your firm's per-trade risk guidance (often ~1%).

STOP_LOSS (pips) 1250

Distance from entry to stop, in pips (1 pip = $0.01 move on XAU/USD).

PIP_VALUE (per 0.01 lot) $0.01

Default matches the common XAU convention (0.01 lot × 1000 pips = $10). Check your broker's contract spec.

LOT_STEP

Minimum lot increment your broker allows. Result rounds down to this step.

trading costsadvanced

SPREAD (pips) 20

COMMISSION ($/lot) 0

Round-turn cost per 1.00 lot. A real stop-out costs stop distance + spread + commission — the sizer accounts for this so actual risk still lands on target.

strategy edgeadvanced

WIN_RATE 65%

REWARD : RISK 1 : 1

Used for the Kelly cross-check and streak-probability estimate below — not for lot sizing itself.

drawdown limits

FTMO 1-Step objectives

Profit target10%

Daily loss3%

Maximum loss10% · EOD trailing

Minimum daysNone

Best Day must be no more than 50% of total positive-day profit. Daily limits reset at 00:00 CE(S)T.

POSITIVE_DAYS_PROFIT

BEST_DAY_PROFIT

Used for 1-Step Best Day progress. Enter profitable-day totals only; losing days do not reduce Positive Days’ Profit.

DAILY_LOSS 3%

MAX_LOSS 10%

DD_TYPEadvanced

FTMO 1-Step: the floor is recalculated at 00:00 CE(S)T from the highest end-of-day balance and can only rise.

portfolio riskadvanced

MAX_CONCURRENT_RISK 2.0%

Total risk you'll allow open across all positions at once — caps correlated exposure (e.g. XAU + a correlated USD pair) instead of just one trade at a time.

risk step-down ruleadvanced

Cut risk after consecutive losses

AFTER (losses) 2

CUT BY 50%

A common prop-desk rule: halve size after 2 losers in a row. Stretches your daily/max DD budget considerably — see the output panel.

pre-trade checklistadvanced

No high-impact news in the next 30 min Risk % matches the plan, not "feel" Checked correlated/open exposure

position size output

Daily buffer remaining

—

floor —

Max-loss buffer remaining

—

floor —

Prop-safe risk cap

—

maximum lot —

Best Day progress

—

enter profits above

Recommended lot size

—

risking — per trade

risk budget vs. full kelly —

Set win rate & R:R above to compare your risk % against the theoretical optimum.

Losers before daily DD

—

at this risk %, in a row

Losers before max DD

—

at this risk %, in a row

P(that streak happens)

—

chance of hitting daily DD losers in a row, at your win rate

P(that streak happens)

—

chance of hitting max DD losers in a row, at your win rate

./calc.sh

Awaiting input

Risk per trade ($, incl. costs) —

Effective stop (pips, incl. spread) —

Daily buffer remaining ($) —

Max-loss buffer remaining ($) —

Profit target remaining (closed balance) —

$ value per pip at this lot size —

Recovery needed after daily DD hit —

Recovery needed after max DD hit —

Full-Kelly optimal risk (reference only) —

Concurrent trades allowed (exposure cap) —

Losers before daily DD, with step-down rule —

⚠ Rounded lot size is below your broker's minimum (0.01) — either widen the stop, raise risk %, or accept a slightly higher risk than targeted.

⚠ Your risk per trade exceeds full Kelly for this win-rate/R:R — that's oversized even by aggressive standards.

balance & recovery charts

balance decay by consecutive losers

fixed size

recovery needed vs. % lost

daily DD max DD

risk & survival chartsadvanced

P(N consecutive losses) at your win rate

daily DD count max DD count

kelly growth curve

growth rate g(f) your risk % full Kelly

cost drag: $ risk at this lot size by spread

Assumptions: lot size = (balance × risk%) ÷ (effective stop pips × pip value per standard lot), where effective stop = stop-loss + spread, rounded down to your lot step, with commission added on top so realized risk still lands on target. "Losers before DD" counts consecutive full-stop losses at fixed size and ignores anything beyond spread/commission (no slippage). Streak probability uses (1 − win rate)ⁿ as a simplified independent-Bernoulli estimate — it ignores any edge decay or correlation between trades. Kelly is the theoretical full-Kelly optimum (f* = W − (1−W)/R); most funded traders run at a fraction of it (¼–½ Kelly) because full Kelly has brutal variance. "Static" vs "trailing" DD only matters once winning trades occur — mid-losing-streak the two behave identically, since neither has moved the equity peak. This is a planning aid, not financial advice — verify every number against your own firm's actual rulebook before risking a real evaluation.

Prop Challenge Pass-Probability Simulator

Prop Firm Journey Audit

Monthly P/L calendar

Pass / failure race

Quant Trade Analysis

Waiting for trade history

—

Kelly criterion · empirical sizing cross-check ↗

WHAT IF · Kelly historical replay

Equity paths

Drawdown paths

Final balance by Kelly ratio

Balance change by Kelly ratio

Strategy fingerprints

Trade-return distribution

Rolling edge

Drawdown underwater

Lot size versus outcome

Holding time versus outcome

MAE versus MFE

Edge and payoff structure

Return distribution and tail risk

Direction and holding behavior

Timing and session profile

Stability and regime checks

Risk behavior and sizing discipline

Deep insights

Advanced Quant Lab

Trading-day block bootstrap

Chronological edge validation

Execution-cost stress · selected evaluation rules

Monte Carlo survival

Risk versus outcome

Rolling edge stability

Sequence dependency

Outcome dependence

Daily rule pressure

Prop survival scenarios

Confidence and sample quality

Outlier dependency stress

Time to target versus failure

Behavioral risk detector

Exposure concentration

MAE/MFE and exit efficiency

Best-day and rule management

Quant action board

XAU/USD Lot Size Calculator

Kelly criterion · empirical sizing cross-check