Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading - Image 1

£73.00

CRC Press Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading

Name: Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading
Brand: CRC Press
Price: 73.0 GBP
Availability: InStock

Investments & Securities

About as cheap as it gets. The only time it was cheaper was 1 year ago.

£73 today · all-time low £72 (Sep 2024) · usually the usual

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 530 days • 530 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 530 days • 5 price ranges

Days at Price

Current Price

Price Analysis

Most common range: £72-74 (205 days, 38.7%)

Price range: £72 - £83

Price levels: 5 price ranges over 530 days

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.

Product Specifications

Brand: CRC Press
Format: hardcover
ASIN: 0367536285
Category: Books > Subjects > Business, Finance & Law > Professional Finance > Investments & Securities
Domain: Amazon UK
Release Date: 15 September 2020
Listed Since: 29 May 2020

Barcode

No barcode data available

CRC Press Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading

About as cheap as it gets. The only time it was cheaper was 1 year ago.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

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

Financial Modelling with Forward-looking Information: An Intuitive Approach to Asset Pricing (Contributions to Management Science)

Financial Modelling with Forward-looking Information: An Intuitive Approach to Asset Pricing (Contributions to Management Science)

Optimal Mean Reversion Trading: Mathematical Analysis And Practical Applications: 1 (Modern Trends In Financial Engineering)

Equity Analytics: Strategies, Models, and Techniques in Computational Finance (Investment Analytics)

Kaufman Constructs Trading Systems

High-frequency Trading

Handbook of Price Impact Modeling (Chapman and Hall/CRC Financial Mathematics Series)

Finanzmarktsimulation mit Multiagentensystemen: Entwicklung eines methodischen Frameworks

Trades, Quotes and Prices: Financial Markets Under the Microscope

Algorithmic Trading: Winning Strategies and Their Rationale: 625 (Wiley Trading)

Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments: Developing Predictive-Model-Based Trading Systems Using TSSB

Trading Systems and Methods (Wiley Trading)

Algorithmic Trading Hands-On Approach Using Python

The Backtesting Masterclass: Build, Validate, and Optimize with Python: Ideas are cheap. Verified performance is priceless.

Capital Markets Trading and Investment Strategies in China: A Practitioner's Guide

Lecture Notes In Market Microstructure And Trading: 4 (World Scientific Lecture Notes In Finance)

Professional Automated Trading: Theory and Practice (Wiley Trading)

Financial Trading and Investing

Machine Learning and Big Data with kdb+/q (Wiley Finance)

MiFID: Convergence Towards a Unified European Capital Markets Industry

Numerical Methods Using Java: For Data Science, Analysis, and Engineering

Information Mirages an experimentellen Wertpapiermärkten

Building Winning Algorithmic Trading Systems + Website: A Trader's Journey From Data Mining to MonteCarlo Simulation to Live Trading (Wiley Trading)