000			04080cam a2200589 i 4500
001			9781003087595
003			FlBoTFG
005			20240213122824.0
006			m o d
007			cr cnu---unuuu
008			200620t20212021flua ob 001 0 eng
040			_aOCoLC-P _beng _erda _cOCoLC-P
020			_a9781003087595 _qelectronic book
020			_a1003087590 _qelectronic book
020			_z9780367536282 _qhardcover
020			_a9781000220162 _q(electronic bk. : PDF)
020			_a1000220168 _q(electronic bk. : PDF)
020			_a9781000220360 _q(electronic bk. : EPUB)
020			_a1000220362 _q(electronic bk. : EPUB)
020			_z9780367540951
020			_a9781000220261 _q(electronic bk. : Mobipocket)
020			_a1000220265 _q(electronic bk. : Mobipocket)
035			_a(OCoLC)1164826779 _z(OCoLC)1197637267
035			_a(OCoLC-P)1164826779
050	0	4	_aHG176.7 _b.C44 2021
072		7	_aMAT _x004000 _2bisacsh
072		7	_aCOM _x037000 _2bisacsh
072		7	_aUMB _2bicssc
082	0	0	_a332.01/511352 _223
100	1		_aChen, Jun, _d1990 February 16- _eauthor.
245	1	0	_aDetecting regime change in computational finance : _bdata science, machine learning and algorithmic trading / _cJun Chen, Edward P K Tsang.
250			_aFirst edition.
264		1	_aBoca Raton : _bCRC Press, Taylor & Francis Group, _c2021.
264		4	_c©2021
300			_a1 online resource (xxvi, 138 pages) : _billustrations (some color)
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
505	0		_aBackground 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.
520			_a"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"-- _cProvided by publisher.
588			_aOCLC-licensed vendor bibliographic record.
650		0	_aFinancial engineering _xMethodology.
650		0	_aFinance _xMathematical models.
650		0	_aStocks _xPrices _xMathematical models.
650		0	_aHidden Markov models.
650		0	_aExpectation-maximization algorithms.
650		7	_aMATHEMATICS / Arithmetic _2bisacsh
650		7	_aCOMPUTERS / Machine Theory _2bisacsh
700	1		_aTsang, Edward, _eauthor.
856	4	0	_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9781003087595
856	4	2	_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999			_c4755 _d4755