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E-Book
Title Detecting regime change in computational finance : data science, machine learning and algorithmic trading / Jun Chen, Edward P K Tsang.

Description 1 online resource (xxvi, 138 pages) : illustrations (some color)
Edition First edition.
Note Includes bibliographical references and index.
Contents Background and literature survey -- Regime change detection using directional change indicators -- Classification of normal and abnormal regimes in financial markets -- Tracking regime changes using directional change indicators -- Algorithmic trading based on regime change tracking.
Summary "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 summarizing 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 ("zigzag"). By sampling data in a different way, the 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"-- Provided by publisher.
Note Description based on online resource; title from digital title page (viewed on September 21, 2020).
Subject Financial engineering -- Methodology.
Finance -- Mathematical models.
Stocks -- Prices -- Mathematical models.
Hidden Markov models.
Expectation-maximization algorithms.
Electronic books.
Local Subj. Taylor and Francis ebook collection.
Alt Author Tsang, Edward, author.
Standard # 9781003087595 electronic book
1003087590 electronic book
9780367536282 hardcover
9781000220162 (electronic bk. : PDF)
1000220168 (electronic bk. : PDF)
9781000220360 (electronic bk. : EPUB)
1000220362 (electronic bk. : EPUB)
9780367540951
9781000220261 (electronic bk. : Mobipocket)
1000220265 (electronic bk. : Mobipocket)

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