TRADE EXPECTANCY CALCULATOR

Use the sliders below to calculate trade expectancy, compounding potential, and simulated equity curve outcomes.
Win Rate %
%
Avg Win R
R
Avg Loss R
R
Risk / Trade %
%
Compounding Path
Capital
Used to convert the % and R-based model into dollar values.
Broker Commission / Trade (R)
Subtracted as fixed R cost per trade from expectancy and compounding.
Trades / Month
Used only for the time estimate. Change it to match your actual pace.
Target
2x Capital
39
1.95 months
Target balance: $20,000
Target
10x Capital
130
6.50 months
Target balance: $100,000
Trade Expectancy
0.90R
Net edge in R after commission
Profit / Trade
$180
Net return: 1.80% per trade
Expected Monthly Return
42.94%
$42,940 / month
Expected Yearly Return
—
— / year
Profit Factor
1.90
Gross wins ÷ gross losses including commission
Break-Even Win Rate
25.00%
Minimum win rate needed to avoid losing money
Chance of 5 Losses in a Row
3.13%
Within next 100 trades
Recovery After 5 Losses
+8.95%
After a -8.21% drawdown from 5 consecutive losses
Chance of 10 Losses in a Row
0.10%
Within next 100 trades
Recovery After 10 Losses
+18.76%
After a -15.79% drawdown from 10 consecutive losses

Equity Curve Simulation

Randomized trade path using your current win rate, avg win/loss, risk, commission, and capital.
simulated equity
2x target
10x target
clean expectancy path
starting capital
Final Balance
$0
Best Winning Streak
—
Worst Losing Streak
—
Max Drawdown
0%
2x Hit
—
2x Hit Time
—
10x Hit
—
10x Hit Time
—

Full Matrix

Win rate, avg loss, and commission stay fixed. Avg win changes across columns. Risk % changes across rows.
Net trade expectancy = (win rate × avg win) − (loss rate × avg loss) − commission R. Net return / trade = net trade expectancy × risk %. Monthly return is a pure compounding projection using your trades-per-month setting. The equity curve is a randomized simulation and changes when you refresh it; commission is treated as fixed R per trade; the 5-loss and 10-loss probabilities estimate the chance of at least one such streak within the next 100 trades, assuming each trade is independent and the win rate stays constant. Recovery after 5 losses assumes each losing trade costs (avg loss × risk %) + commission %.
Equity simulation formula: each simulated trade randomly becomes a win or loss using the selected win rate. Winning trade return = (avg win R − commission R) × risk %. Losing trade return = −(avg loss R + commission R) × risk %. Balance is compounded after each trade. The dashed line shows the clean expectancy path using net trade expectancy × risk % per trade, where net trade expectancy includes commission as fixed R. This is a simplified Monte Carlo-style path, not a guarantee.
Reflection

Expectancy Is Probabilistic, Not Linear

One of the most underestimated aspects of trading is how heavily random trade distribution can influence short and medium-term results, even when a trading strategy has positive expectancy.

Many traders assume that if a system has a statistical edge, the equity curve should naturally look relatively smooth over time. In reality, two traders using the exact same strategy, risk management, and execution quality can still experience completely different outcomes across the same sample size.

This becomes very clear when running repeated equity curve simulations using identical parameters:

  • same win rate
  • same average win
  • same average loss
  • same risk per trade
  • same commission structure

Despite identical expectancy, the resulting paths can vary significantly.

Some simulations produce smooth compounding with shallow drawdowns. Others experience prolonged losing streaks, aggressive volatility, or long periods of stagnation before the edge begins expressing itself properly.

The underlying expectancy remains unchanged. The distribution of outcomes does not.

This is one of the main reasons many traders struggle psychologically during statistically normal drawdowns. Human pattern recognition naturally expects progress to appear relatively linear:

  • profitable strategy = consistent growth
  • losing strategy = consistent decline

Markets rarely behave that cleanly.

Losses cluster.

Winning streaks cluster.

Variance compounds emotionally as much as financially.

A strategy can remain statistically profitable while still producing uncomfortable sequences of outcomes over meaningful periods of time.

This is also why risk management plays such a critical role in long-term survivability. When risk per trade becomes too aggressive, otherwise normal variance can become psychologically and financially destabilizing. The issue is often not expectancy itself, but the trader’s ability to survive the distribution of outcomes long enough for that expectancy to fully materialize.

The Trade Expectancy Calculator and Equity Curve Simulator above were designed to visualize this concept more clearly through probability-based modeling rather than idealized linear projections.

The objective is not to predict future performance with certainty. The objective is to better understand:

  • trade expectancy
  • compounding behavior
  • drawdown dynamics
  • streak probabilities
  • variance
  • survivability
  • and the probabilistic nature of trading performance.

One useful exercise is to run the simulator multiple times using the exact same parameters and compare how different the resulting equity curves can become. In many cases, the emotional experience of the path differs far more than traders initially expect, even while the underlying edge remains mathematically identical.