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Multiple Model Machine Learning

Found out that more than one random forest model can be generated in the same algorithm so I made separate models for price and volume using the machine learning example in the other thread. Seems like it would also be possible to create multiple models using the same variables and then make a buy or sell decision based on the majority prediction. This is based on the machine learning example and the backtest is relatively fast, so using several models shouldn't cause major issues. The results vary because of random forest so not every backtest will perform this well.

Clone Algorithm
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Backtest from to with initial capital
Total Returns
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Alpha
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Beta
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Sharpe
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Sortino
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Max Drawdown
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Benchmark Returns
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Volatility
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Returns 1 Month 3 Month 6 Month 12 Month
Alpha 1 Month 3 Month 6 Month 12 Month
Beta 1 Month 3 Month 6 Month 12 Month
Sharpe 1 Month 3 Month 6 Month 12 Month
Sortino 1 Month 3 Month 6 Month 12 Month
Volatility 1 Month 3 Month 6 Month 12 Month
Max Drawdown 1 Month 3 Month 6 Month 12 Month
# Backtest ID: 59855c02e524714fc898c5b6
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