Warning message

Mean Menu style requires jQuery library version 1.7 or higher, but you have opted to provide your own library. Please ensure you have the proper version of jQuery included. (note: this is not an error)

Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading (Hardcover)

Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading Cover Image
$99.95
Backordered. Place an order and we will let you know when to expect your book.
(This book cannot be returned.)

Description


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:

Data science: as an alternative to time series, price movements in a market can be summarised as directional changes

Machine learning for regime change detection: historical regime changes in a market can be discovered by a Hidden Markov Model

Regime characterisation: normal and abnormal regimes in historical data can be characterised using indicators defined under Directional Change

Market Monitoring: by using historical characteristics of normal and abnormal regimes, one can monitor the market to detect whether the market regime has changed

Algorithmic trading: regime tracking information can help us to design trading algorithms

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.

About the Author


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.


Product Details
ISBN: 9780367536282
ISBN-10: 0367536285
Publisher: CRC Press
Publication Date: September 15th, 2020
Pages: 138
Language: English