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Genetic Algorithm

Hi, I'm fairly new to QuantConnect's algo lab but it looks preferable to MQL5/metatrader. So my question is, how am i supposed to write a GA using this platform when it does not appear to support such an idea. Am I going to have to create 'pseudo' trades and flag them instead of actually placing the trades? For example, if I create a population of 100 individuals which each possess different values (when to enter/exit based on the value of certain parameters), how is this going to work if Oanda, for example, won't let you properly hedge? If one individual decides to buy the EUR/USD and at the same time another individual decides to sell the EUR/USD...this is going to mess everything up because Oanda will just liquidate the original trade, which means I would never be able to score the fitness.

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You will need to manually track positions to fully hedge positions as QuantConnect aggregates the whole portfolio so its an average of your past trades. 

It might be worth looking into QuantConnect's Algorithm Framework as opposed to a classic algorithm, whose modular framework allows for the creation of multiple alphas within one algorithm. The alpha model provides insights, or a single prediction for an asset. These can be thought of as actionable trading signals; indicating the asset direction, magnitude, and confidence in the near future. When backtesting the direction and magnitude accuracy of the predictions will be tested as well. Multiple alphas can be added into the framework using the Composite Alpha model, which helps pass all the emitted insights through a Portfolio Construction model. If properly implemented it is possible to create a GA using this framework.

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