Deep learning alpha signals from limit order books: practical insights and lessons learned
An analysis on network architectures applied to limit order book data is presented
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In recent years, deep learning models have gained traction in predicting high-frequency equity returns by leveraging order book data, a shift from manual feature engineering. Petter Kolm and Nicholas Westray examine a number of key questions relevant for the application of these models in practice. They investigate several network architectures, input selection for
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