Trade Growth Calculator

Realistic projection requires three inputs: win rate, average win/loss size ratio, and number of trades per period. Expected return per trade = (Win Rate × Avg Win%) − (Loss Rate × Avg Loss%). Compound that across trades, subtract fees, and you get a projected equity curve.

Most consistent retail day traders achieve 5–15% monthly returns before fees in good market conditions. Projections above 20%/month sustained over a full year are statistically rare and warrant skepticism.

Monte Carlo runs 1,000 randomized trade sequences using your win rate and R:R parameters to show the distribution of possible outcomes — the median path, the optimistic 90th percentile, and the pessimistic 10th percentile.

A single expected-value projection shows the mathematical average but ignores sequence risk: you might average +1.5R per trade yet still face ruin if 20 losses cluster at the start. Monte Carlo reveals the full probability space, including paths where even a genuine edge temporarily destroys an account.

Retail day trader win rates typically range from 40% to 60% per trade. A 50% win rate with a consistent 2:1 reward/risk ratio generates strong positive expected value: +0.5R per trade on average.

Scalping strategies can achieve 65–70% win rates with 1:1–1.5:1 R:R. Strategies above 70% sustained win rate usually carry occasional large losses that offset the high frequency of small winners. Both the win rate and the average win/loss ratio must be entered for projections to be meaningful.

With compounding enabled, each winning trade grows your account, which increases the dollar amount risked on the next trade — gains accelerate geometrically. With fixed sizing, you risk the same dollar amount regardless of account growth or loss.

Compounding amplifies both gains and drawdowns: 30 consecutive losses hit a compounding account far harder than a fixed-size account. Most professionals use fixed sizing until they have a verified edge across 200+ live trades, then consider a gradual compounding schedule.

Match the simulation to your actual trading frequency. An active day trader doing 5 round-trips daily runs 1,260 trades in a 252-day trading year. A selective trader doing 1–2 setups daily runs 250–500 trades per year.

Running the full annual count (rather than 50–100 trades) shows the statistical stabilization that large sample sizes produce. Short trade counts — under 50 — produce wildly variable outcomes even with a genuine edge, making the simulation misleading as a planning tool.

When you add a fixed deposit each trade, the account grows from both trading returns and capital injections. A $1,000 account that receives $500/trade deposits reaches $50,000 primarily from deposits, not from trading skill.

Reporting an annualized return in that scenario would massively overstate trading performance by attributing deposit growth to returns. The calculator hides the annualized return figure whenever contributions are active to prevent this misleading metric from appearing.