In this educational presentation; we first review some general concepts about trends and how to build generic systematic trend following strategies according to classic definitions. Then we focus on the use of price-based features to construct a dataset designed for training different Machine Learning (ML) approaches (trees based and neural net based) to build diversified Futures portfolio. We finally conclude by contrasting the results between generic and ML based approach and how they relate to contemporary methodologies used in the systematic CTA/Trend following.
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