Based on interdisciplinary research into "Directional Change", a new data-driven approach to financial data analysis, Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading applies machine learning to financial market monitoring and algorithmic trading. Directional Change is a new way of summarising price changes in the market. Instead of sampling prices at fixed intervals (such as daily closing in time series), it samples prices when the market changes direction ("zigzags"). By sampling data in a different way, this book lays out concepts which enable the extraction of information that other market participants may not be able to see. The book includes a Foreword by Richard Olsen and explores the following topics:
It will be of great interest to researchers in computational finance, machine learning and data science.
About the Authors
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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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