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eas-guide:monte-carlo

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eas-guide:monte-carlo [2025/09/11 08:27] – [Simulations] Miroslav Popoveas-guide:monte-carlo [2025/09/12 07:22] (current) – Corrected "Randomize start bar" Miroslav Popov
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 For example, if we start the test on a local performance high, then the following losing period may cause a significant drawdown. For example, if we start the test on a local performance high, then the following losing period may cause a significant drawdown.
  
-The opposite case is also possibleif we start the test on a local low, the subsequent gains may show overestimated results.+The opposite case is also possible if we start the test on a local low, the subsequent gains may show overestimated results.
  
-    * **Randomize backtest starting bar** - will randomize the starting bar of the test. +    * **Randomize backtest starting bar** - searches for a following opposite direction signal and starts the test from there. It causes the backtest to begin with an opposite trade. This simulation aims to identify cases where initiating with an opposite trade compromises strategy performance. If the count of the shadowed opposite orders is lower than the selected count of tests, Monte Carlo uses a random starting bar.
-    * **Skip to next shadowed opposite order** - searches a following opposite direction signal and starts the test from there. It causes the backtest to start with an opposite trade. This simulation aims to identify cases where initiating with an opposite trade compromises strategy performance.+
  
  
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 {{:eas-guide:monte-carlo-validation.jpg?nolink|}} {{:eas-guide:monte-carlo-validation.jpg?nolink|}}
  
-When running the [[eas-guide:reactor|Reactor]] or [[eas-guide:validator|the Validator]] Monte Carlo testing is present in the Robustness testing section. +When running the [[eas-guide:reactor|Reactor]] or [[eas-guide:validator|the Validator]]Monte Carlo testing is present in the Robustness testing section. 
  
 The **Validated tests** setting uses the **Validation** settings in the Monte Carlo tool here. The **Validated tests** setting uses the **Validation** settings in the Monte Carlo tool here.
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 These are very similar and work in the same way as the general [[eas-guide:acceptance-criteria|Acceptance Criteria]] for the [[eas-guide:collection|collection]] works. These are very similar and work in the same way as the general [[eas-guide:acceptance-criteria|Acceptance Criteria]] for the [[eas-guide:collection|collection]] works.
  
-In the above example a strategy will be considered to have passed the Monte Carlo validation only if at least 80% of the tests pass.+In the above examplea strategy will be considered to have passed the Monte Carlo validation only if at least 80% of the tests pass.
  
-~~DISQUS~~