Module 5

The Numbers

Module 5 of 6

Eight years of real trades. No hypotheticals.

Every number below comes from backtesting the exact rules on ES daily data from 2018 through 2026. Commissions and slippage included. Numbers updated 2026-04-08 after a simulator audit found a trail-stop fill bug that had been inflating results.

The original numbers were wrong.

Until 2026-04-07, this page reported 113 trades, 67.3% WR, PF 5.86, $799 max DD. A Level 3 simulator audit (commit be6deeb) found that the SMA trailing stop in the H12 backtester was filling above the market on gap-down days, inflating the win rate and suppressing drawdown. Patched 2026-04-08.

The numbers below are from the patched simulator. The directional edge survives. The headline statistics don't.

85
Trades
42.4%
Win Rate
+28.6
Avg pts/trade
1.99
Profit Factor
$2,699
Max DD
42% win rate, but winners are 2.7x bigger than losers.

36 winners. 49 losers. The average winner is +136.2 pts ($681). The average loser is -50.4 pts ($252). Winners are 2.7x larger than losers.

That's where the edge comes from. The strategy loses more often than it wins, but when it wins it wins big. Profit factor 1.99 means every $1 risked returns approximately $2.

Trade P&L Distribution

0 Losers (49) Winners (36) -150 pts +790 pts +791 -176 Avg: -50 Avg: +136

Walk-Forward Validation

The strategy was tested on three separate time periods. Rules fixed in advance, no adjustments between periods.

Period Win Rate Profit Factor Max DD Result
2020 - 2021 50.0% 1.60 $1,169 PASS
2022 - 2023 27.3% 1.79 $1,321 PASS
2024 - 2026 34.6% 2.18 $1,755 PASS

3 out of 3. Bull, bear, and chop. All profitable.

2020-2021 was the post-COVID rally. 2022-2023 included the worst bear market since 2008. 2024-2026 was a choppy recovery. The strategy made money in all three windows even with the corrected fills. The directional edge survives across regimes. What changed post-audit is the per-period drawdown — windows that previously looked tame now show $1,100-$1,800 max DD.

Monte CarloA simulation technique that reshuffles the order of your 85 trades 1,000 times to see how drawdown changes under different luck scenarios. Tests whether the strategy survives bad sequencing. Simulation

1,000 resampled equity curves from the 85-trade set. How bad can it get?

P50 DD
~$2,480
Median case
P75 DD
~$1,930
Better quartile
P90 DD
~$1,570
Top decile
Actual
$2,699
Historical run

Position sizing from Monte Carlo: the median resampled drawdown is ~$2,480 per MES contract; the actual historical max DD is $2,699. Within a $3,000 personal-account drawdown budget, the strategy can only support 1 MES contract, and even then it would consume most of the buffer. This is the bug-correction story: pre-audit, the same strategy looked sizable at 2 MES against a $2,000 budget; post-audit, it barely fits at 1.

Parameter Robustness

All variants positive.

The trailing-stop buffer was swept across the full range from 3 to 20 points, well beyond a ±20% tolerance. Every variant remained profitable. Per-trade expectancy ranged from $110 to $145; max DD ranged from $2,045 to $2,743. The directional edge is not fragile to the exact buffer, but the DD envelope is large enough that every variant exceeds the personal-account budget.

Biggest Trades

Biggest Winners

PointsHold$ (1 MES)
+791.523 days$3,958
+436.539 days$2,183
+379.843 days$1,899
+367.048 days$1,835
+267.346 days$1,337

Top 5 total: $11,212 (92% of all profits). The strategy is heavily concentrated in a few big winners.

Biggest Losers

PointsHold$ (1 MES)
-176.31 day-$881
-110.81 day-$554
-105.31 day-$526
-95.313 days-$476
-94.66 days-$473

Without the top 5 winners, total PnL is $960 — barely breakeven. The whole edge is in the right tail.

The asymmetry is the strategy. Losers are small and fast (often 1 day). Winners are large and slow (23 to 48 days for the biggest). The SMA stop cuts losers quickly but gives winners room to run.

This is also the strategy's fragility. The top 5 winners account for 92% of all profits. Without those five trades the strategy is essentially breakeven. Multi-week trends like 2018-2019 and 2023-2026 produce them. Choppy years like 2021-2022 (combined: -$1,823) don't, because there's no sustained trend for the trail stop to follow.

What is Monte Carlo simulation?

Imagine you have 85 cards, each representing one trade's P&L. Monte Carlo takes those cards, shuffles them into a random order, and draws them one by one to build an equity curve. Then it does this 1,000 times.

Each shuffle produces a different sequence of wins and losses, and therefore a different maximum drawdown. By looking at the distribution of drawdowns across all 1,000 shuffles, you can estimate how bad things might get under different "luck" scenarios.

The median resampled drawdown is ~$2,480. The historical run came in worse at $2,699. That means the actual sequence the market produced was slightly unlucky relative to the trade-set's expectation, but not pathologically so. The MC distribution tightens the lesson: the drawdown is structural to the strategy's win-rate and R:R, not a quirk of trade ordering.

What does the buffer sweep show?

A common concern with backtesting: "What if the exact parameter is overfit?" The robustness test answers this by varying the trail-stop buffer across the full range.

Buffer values tested: 3, 5, 8, 12, 15, 20 points. If the strategy only works at buffer=12 and breaks at 10 or 14, that's overfitting — a narrow mathematical artifact rather than a real market behavior.

This strategy passes the directional test: every variant from $110 to $145 per trade. The edge exists across a wide range of buffer values because it captures a genuine phenomenon (multi-week equity trends), not a quirk of one specific number. But every variant also has max DD between $2,045 and $2,743 — so the DD constraint binds across the whole parameter neighborhood, not just at one setting.

What about the full-size ES contract?

Everything above uses MES (Micro E-mini), where each point is worth $5. The full-size ES contract is $50 per point. Same strategy, same rules, same edge. Everything scales by 10x.

MES (Micro) ES (Mini)
Dollar per point $5 $50
Margin required ~$1,500 ~$15,000
Total PnL (85 trades, 8yr) $12,172 $121,720
Per trade average $143 $1,432
Average winner $681 $6,810
Average loser -$252 -$2,520
Max drawdown (MtM) $2,699 $26,990
P50 DD (Monte Carlo) $2,480 $24,800
Biggest single loss $881 $8,810
Annual average $1,522 $15,215

Same strategy, same rules, same edge. The only difference is the dollar per point.

To trade ES you need a much larger account. Historical max DD on ES is $26,990 so you'd need at least $60,000-80,000 to absorb the worst case. ES margin alone is around $15,000.

This is the takeaway from the bug correction. The strategy still has a real edge ($143/trade after costs), but the DD makes it a poor fit for the $3,000 personal-account budget that motivated the original module. It belongs on the research bench, not the live roster. Module 6 covers what does belong on the live roster.

The lesson.

An $800 max DD strategy at 67% win rate is a different product from a $2,700 max DD strategy at 42% win rate. One bug, found by a Level 3 audit eight months after the original publication, turned the first into the second. This is why we have a 3-gate framework. This is also why we audit our own simulators.

Check your understanding

You've been running the strategy for 20 trades. Results: 6 winners, 14 losers (30% win rate). The historical average is 42.4%.

Should you stop trading the strategy?

B) Correct. A 42% win rate over 20 trades can easily produce 30% (or even lower) by random chance. The 2022-2023 walk-forward window actually ran at 27.3% WR for 22 trades and still cleared $2,938. Short samples deviate from the long-term average, especially for low-WR / high-R:R strategies where a few big winners do all the work. You need 100+ trades before drawing conclusions about whether the edge has changed.

The numbers were a story. The audit was a better one. Module 6 covers what the framework looks like when it works as intended — the strategies that are live on Topstep XFA today.

Module 6: Execution & Discipline →