Walk Forward Optimization ( User Guide). You can find Expert Advisor Studio on our website: [ Ссылка ].

In this video, we will be discussing the Walk Forward testing and how to avoid over-optimization.

Now, Walk Forward testing represents sequential optimization of created strategies. It's also referred to as Walk Forward analysis or Walk Forward optimization.

Now, the reason that we came up with the name Walk Forward is because there is a moving window that gradually goes over the entire period of the historical data with preset steps.

To get to the Walk Forward, we select a strategy either from our collection or a strategy that we have created. We click on it, it takes us to the strategy window, and on the taskbar, we select Walk Forward.

Now, what you'll see is that there are a number of segments on the chart.
So the big segment on the left represents the In Sample part, and the 5 segments on the right represent the Out of Sample part.

When we run the Walk Forward optimization, all of the parameter variations are tested during the In Sample stage, and the most robust combinations that fulfill the Walk Forward optimization criteria is then used for the first Out of Sample segment.

The same process then repeats to the point where the Walk Forward optimization goes through the full data feed with preset defined steps in the options.

Then the Statistics tab displays the results of the Out of Sample analysis.

So what you can see now, it is running through all of the segments, and it is giving us the original as well as the after optimization settings. You can see the results on the right, and once it's complete, it will tell us whether the strategy is better, which in this case, it is, and the common Acceptance criteria is valid.

So essentially, what we can solve from the result of this Walk Forward optimization is that this is a well-performing strategy even in the Out of Sample part.

Now, running through the tabs that we have in the Walk Forward, we have the equity chart, and this obviously shows us our equity line after and before optimization.

We have the statistics, and here we can analyze the Walk Forward testing - we have a start date, end date, profit, drawdown, return, trades, and win and loss.

And below that, we have additional statistics.

The next tab is the parameters. This gives us the strategy parameters by segments, and in this section, you can also see the exact values of the indicators used for each segment for the Walk Forward testing.

Below that, we have the full backtest with the last parameters as well as the backtest metrics.

In the next tab, we have the settings, and there are several options here which you can experiment with. And this would be the number of segments, the Out of Sample, numeric value ranges, and Search best.

You can also select whether or not to optimize the Stop Loss and Take Profit or to optimize your preset indicators.

Lastly, we have the validation, and in this section, you can select the validation criteria for your In Sample or your Out of Sample part. You have a number of options available to you. You can add, you can modify, and you can remove them, and the same for the Out of Sample. Lastly, we have the Edit button.

Now, as you can see, it has turned green, and that means that the full backtest fulfills the common Acceptance criteria.

The optimized strategy outperforms the initial version according to the Search best option that we selected. And all of the segments of the strategy are valid.

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