100-Trade Simulation — What Different Systems Produce

Backtesting strategies on historical data is valuable, but it abstracts something important: what does trading a system actually feel like over 100 trades, and what does it produce on a R50,000 account? This page works through four realistic scenarios at different win rates and risk-reward ratios, showing the full 100-trade journey — drawdowns included.

The Simulation Parameters

All four scenarios assume:

Account: R50,000 starting balance
Risk per trade: 1% of current account balance (not fixed — recalculated each trade)
100 consecutive trades
Win/loss distribution is representative of the stated win rate (not perfectly alternating — includes losing streaks)

Scenario 1: Typical Beginner (High Win Rate, Poor R:R)

Win rate: 62% | Average winner: 0.8R | Average loser: 1.0R

Expectancy: (0.62 × 0.8R) − (0.38 × 1.0R) = 0.496 − 0.380 = +0.116R per trade

This looks profitable. But the actual account journey is erratic:

After 100 trades: approximately +R5,700 net (11.4% return)
Maximum drawdown during the period: approximately −14% (when the losing streak hits)
Probability of 5 consecutive losses at 38% loss rate: approximately 1.2% — happens roughly once per 80 trades

The problem: A 62% win rate feels like a skilled trader. But the psychology of this system is terrible: small wins (0.8R) feel unrewarding; losses (1.0R) feel disproportionate. Traders with this profile often move their stop-losses to avoid the full 1.0R loss — destroying what little edge exists.

Scenario 2: Balanced System (Moderate Win Rate, Standard R:R)

Win rate: 50% | Average winner: 2.0R | Average loser: 1.0R

Expectancy: (0.50 × 2.0R) − (0.50 × 1.0R) = 1.0 − 0.5 = +0.5R per trade

At R50,000 account, 1% risk:

Average profit per trade: R250 (0.5% of account)
After 100 trades: approximately +R27,600 net (55.2% return — compounded from growing account)
Maximum drawdown: approximately −13% (a typical losing streak of 7 in a row at 50% loss rate occurs roughly once per 100 trades)

The psychology: 50% win rate feels disappointing — "I'm wrong half the time." But the 2:1 R:R means each win more than covers two losses. This system is durable precisely because a 50% win rate is achievable without being selective about setups.

Scenario 3: Lower Win Rate, Higher R:R (Professional-Style)

Win rate: 40% | Average winner: 3.0R | Average loser: 1.0R

Expectancy: (0.40 × 3.0R) − (0.60 × 1.0R) = 1.2 − 0.6 = +0.6R per trade

At R50,000 account, 1% risk:

After 100 trades: approximately +R34,200 net (68.4% return, compounded)
Maximum drawdown: approximately −17% (more pronounced because 60% of trades lose; probability of 8 consecutive losses ≈ 1.7% — roughly once per 60 trades at 40% loss rate)

The challenge: A 40% win rate means you lose 6 out of every 10 trades. The losing streaks are longer (8–10 consecutive losses is not unusual) and more psychologically demanding. Most traders cannot execute this system because they abandon it during the inevitable extended losing streak — before the wins arrive to justify the approach.

This system requires a journal to survive: the trader needs to verify that losses are rule-following losses (valid setups that didn't work) not process failures, to maintain confidence through the streak.

Scenario 4: Negative Expectancy (Common Retail Pattern)

Win rate: 55% | Average winner: 0.6R | Average loser: 1.2R

Expectancy: (0.55 × 0.6R) − (0.45 × 1.2R) = 0.33 − 0.54 = −0.21R per trade

At R50,000 account, 1% risk:

After 100 trades: approximately −R9,400 net (−18.8%)
Account after 200 trades: approximately R32,400 (−35% from starting balance)
Account after 300 trades: approximately R20,800 (−58% from starting balance)

This looks like a winning system — 55% win rate. But the losses are 2× the size of the wins on average. This is the pattern documented in the 74–89% retail trader loss rate. The trader feels like they "just need a better strategy" while the actual problem is trade management: cutting winners short and letting losers run.

The Losing Streak Reality Check

Every system, regardless of win rate, produces extended losing streaks. Here is the probability of consecutive losses at different win rates:

Win rate (loss rate)	5 consecutive losses	7 consecutive losses	10 consecutive losses
40% win (60% loss)	7.8% per sequence	2.8%	0.6%
50% win (50% loss)	3.1% per sequence	0.8%	0.1%
60% win (40% loss)	1.0% per sequence	0.2%	<0.1%

These probabilities per individual sequence are low — but across 100 trades, the probability of experiencing at least one such streak becomes much higher. At 50% win rate, the probability of experiencing a 7-loss streak somewhere within 100 trades is approximately 40%.

Implication: A 7-trade losing streak at 1% risk = 7% drawdown. At 2% risk = 14% drawdown. At 3% risk = 21% drawdown. Position sizing determines whether a statistically inevitable losing streak is survivable or account-ending.

Key Takeaways

Positive expectancy is necessary but not sufficient. A positive expectancy system still produces drawdowns. Position sizing determines whether you survive them.

Lower win rates require more mental fortitude. A 40% win rate with 3:1 R:R outperforms a 60% win rate with 0.8:1 R:R — but feels worse to trade.

The difference between Scenario 1 (+11.4%) and Scenario 3 (+68.4%) is not better analysis. It is a different exit strategy: holding winners to 3R instead of 0.8R. Entries are identical in this simulation.

Negative expectancy systems compound losses — every trade slightly erodes the account. No number of "good trades" eventually fixes a negative expectancy; the math always wins over sufficient sample size.

All figures are simulated and illustrative only. Actual trading results depend on execution quality, market conditions, psychological factors and many other variables. This is general educational information, not financial advice. Trading forex carries a high level of risk.