I'm trying to understand how to interpret the results when running a Monte Carlo test using Basic Run mode on a limit-order system that includes NSF positions.
In the original backtest, I have:
~1140 actual positions
~70 NSF positions
However, after running the Monte Carlo test with Basic Run mode for multiple iterations, many of the simulations end up with only a few hundred positions (200-600, no NSF), which is significantly fewer than the original backtest.
From the documentation, my understanding is that Basic Run mode repeatedly re-runs the same backtest logic, but with a randomized sampling of the original trades.
My question is whether the following interpretation is correct:
- On a given day in the original backtest, there may be enough raw entry signals to fill (for example) 10 slots.
- In a Monte Carlo iteration, because only a subset of trades is randomly sampled, it’s possible that far fewer than 10 of those trades are present.
- As a result, many slots go unfilled in that iteration, which cascades into a much lower total number of positions over the full simulation.
Is this expected behavior in Basic Run mode, and is this the primary reason why some Monte Carlo simulations end up with far fewer positions than the original backtest? Thanks.
In the original backtest, I have:
~1140 actual positions
~70 NSF positions
However, after running the Monte Carlo test with Basic Run mode for multiple iterations, many of the simulations end up with only a few hundred positions (200-600, no NSF), which is significantly fewer than the original backtest.
From the documentation, my understanding is that Basic Run mode repeatedly re-runs the same backtest logic, but with a randomized sampling of the original trades.
My question is whether the following interpretation is correct:
- On a given day in the original backtest, there may be enough raw entry signals to fill (for example) 10 slots.
- In a Monte Carlo iteration, because only a subset of trades is randomly sampled, it’s possible that far fewer than 10 of those trades are present.
- As a result, many slots go unfilled in that iteration, which cascades into a much lower total number of positions over the full simulation.
Is this expected behavior in Basic Run mode, and is this the primary reason why some Monte Carlo simulations end up with far fewer positions than the original backtest? Thanks.
Rename
The Basic Run just runs the Strategy with the same settings many times. You'd only see a difference if 1) you have NSF positions, and, 2) the Strategy does not assign Transaction.Weight.
I can only guess that the big difference in number of Positions must be explained by something else random in the Strategy. I guess we'd have to see the Strategy to determine that without guessing.
I can only guess that the big difference in number of Positions must be explained by something else random in the Strategy. I guess we'd have to see the Strategy to determine that without guessing.
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