Kardec TraderFutures Trader. Creator of The Midas Touch. Mentor

Your Backtest Means NOTHING Until It SURVIVES A Monte Carlo Test🚨

8 Sept 2026 · 1 min

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In this segment, the presenter explains Monte Carlo reshuffle testing as a method to assess the robustness of a trading strategy's backtest. By taking the original sequence of trades (e.g., 1,000 trades) and randomly reordering them, the test reveals how peak losing and winning streaks change under different trade orderings. The original backtest might show a maximum losing streak of 15 and a maximum winning streak of 15, while a reshuffled run could produce a much larger losing streak (e.g., 45). Comparing these peak streaks between the original and reshuffled data indicates whether the strategy's edge is consistent or fragile; smaller differences suggest a stronger, more reliable edge. The speaker emphasizes that the reshuffle does not alter the strategy itself—it merely stresses the data to expose potential weaknesses in the backtest's assumptions.

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Monte Carlo reshuffle, it's not changing the strategy or anything. It's literally a case of, let's say the original data was 1,000 trades, and of those 1,000 trades, the average losing streak was 7 and the average winning streak was 5. But it shows you the peaks as well. So the peak losing trades in a row was 15 in the original test, and then the most wins in a row was 15. But then the reshuffle is essentially putting all those trades into a random order, and it might be a case where the peak losing number of trades in a row was 45. Exactly. That's how— when the further away those lines will get, which means then the edge maybe isn't as strong versus let's say if that number was 16 instead of 15 on the reshuffle, or 14, that's when they're going to be closer together. So it's showing you that regardless of how that data is redistributed and all those trades are mixed up, it's actually seeing consistent data.