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Applications Of Machine Learning In High-Frequency Trade Direction Classification, Jared E. Hansen
Applications Of Machine Learning In High-Frequency Trade Direction Classification, Jared E. Hansen
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
The correct assignment of trades as buyer-initiated or seller-initiated is paramount in many quantitative finance studies. Simple decision rule methods have been used for signing trades since many data sets available to researchers do not include the sign of each trade executed. By utilizing these decision rule methods, as well as engineering new variables from available data, we have demonstrated that machine learning models outperform prior methods for accurately signing trades as buys and sells, achieving state-of-the-art results. The best model developed was 4.5 percentage points more accurate than older methods when predicting onto unseen data. Since finance and economics …