====== Monte Carlo ======

===== Introduction =====

Monte Carlo is the best tool for testing the strategy robustness. When you create a strategy, you see its backtest statistics. However, there is a problem - the strategy might be over-optimized (curve fitted). The goal of the Monte Carlo tool is to verify that the strategy is not over-optimized. This tool allows you to apply random changes to the market data, the execution of the strategy and the numeric parameters of the strategy indicators.

If you make minor changes to the strategy and its environment, and the strategy continues to have good profits, this means that the strategy has a good chance to make money in the real market.

On the other hand – if you make some minor changes and the strategy profits crumble – it means that this strategy is over-optimized and thus, it is a bad choice to trade.

===== Simulations =====

Here you can choose the simulations that will be used in the Monte Carlo tests. You select optional parameters for each simulation from the **Options** tab.

  * **Market variations** - changes the market data in a certain range. It reflects on the indicators values.
  * **Execution problems** - Those are related to problems when executing the signals sent from the Expert Advisor to the broker.
  * **Strategy variations** - changes the indicator parameters and the strategy protections.

===== Simulations chart =====

By the default running the Monte Carlo tool will run 20 tests with randomized data. The randomization of the data will be done according to the **Simulations** checklist and the values in the **Options** tab.

Each of the tests will be drawn on the **Simulations chart** with a colored line. You can see how the lines are grouped and what is the end result of each backtest. This can easily show how robust the strategy was and how destructive for it the randomized environment and data turned out to be.

===== Confidence table =====

This table shows different statistics from the testing.

The first row shows the initial strategy (the one you are using the Monte Carlo tool on).

The first column shows the percentage of tests that showed results better than the current row. “Confidence” column shows the probability for the profit to be higher than the “Net Balance” value.

===== Options =====

  * **Count of tests** - choose how many tests you want to run.

All the options will apply to the tests **only** if they are enabled from the **Simulations** checklist.


===== Validation =====

The Validation criteria serve the valuate the results of the simulated backtests. The Reactor and the Validator use the count of the passed tests to allow a strategy to advance through the workflow.