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It depends on the data, horizon, inputs, etc. Wavelet transforms seems to be good for reducing time, and PCA seems to be good for reducing assets. There's been a lot of work done in this area, so e.g., look at Jurik Research WAV and DDR modules. Their results indicate that you don't know which bars (days for EOD) are the most informative and also which ...


Neural networks are a supervised machine learning algorithm. Unlike unsupervised machine learning, the key to supervised machine learning is the selection of input factors and explicit labeling of outputs. Input factors have to be manually selected, such as your combination of technical / fundamental / statistical indicators. Outputs have to be ...

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