Interpretable trading pattern designed for machine learning applications
Machine Learning with Applications(2023)
摘要
Financial markets are a source of non-stationary multidimensional time series which has been drawing attention for decades. Each financial instrument has its specific changing-over-time properties, making its analysis a complex task. Hence, improvement of understanding and development of more informative, generalisable market representations are essential for the successful operation in financial markets, including risk assessment, diversification, trading, and order execution.
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关键词
Applied ML,Volume profiles,Boosting trees,Explainable ML,Computational finance
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