Fr. 76.00

Detecting Regime Change in Computational Finance - Data Science, Machine Learning and Algorithmic Trading

Anglais · Livre de poche

Expédition généralement dans un délai de 1 à 3 semaines (ne peut pas être livré de suite)

Description

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Based on interdisciplinary research into "Directional Change", a new data-driven approach to financial data analysis, this book applies machine learning to financial market monitoring and algorithmic trading.



Table des matières

1. Introduction. 2. Background and Literature Survey. 3. Regime Change Detection using Directional Change Indicators. 4. Classification of Normal and Abnormal Regimes in Financial Markets. 5. Tracking Regime Changes using Directional Change Indicators. 6. Algorithmic Trading based on Regime Change Tracking. 7. Conclusion. Appendix A. A Formal Definition of Directional Change. Appendix B. Extended Results of Chapter. 3 Appendix C. Experiment Summary of Chapter. 4 Appendix D. Detected Regime Changes in Chapter.

A propos de l'auteur

Jun Chen received his PhD in computational finance from the Centre for Computational Finance and Economic Agents, University of Essex in 2019.
Edward P K Tsang is an Emeritus Professor at the University of Essex, where he co-founded the Centre for Computational Finance and Economic Agents in 2002. He is a Visiting Professor at University of Hong Kong.

Résumé

Based on interdisciplinary research into "Directional Change", a new data-driven approach to financial data analysis, this book applies machine learning to financial market monitoring and algorithmic trading.

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