Algorithmic Trading Methods - Applications Using Advanced Statistics, Optimization, and Machine Learning Techniques (Paperback, 2nd edition)

Algorithmic Trading Methods: Applications using Advanced Statistics, Optimization, and Machine Learning Techniques, Second Edition, is a sequel to The Science of Algorithmic Trading and Portfolio Management. This edition includes new chapters on algorithmic trading, advanced trading analytics, regression analysis, optimization, and advanced statistical methods. Increasing its focus on trading strategies and models, this edition includes new insights into the ever-changing financial environment, pre-trade and post-trade analysis, liquidation cost & risk analysis, and compliance and regulatory reporting requirements. Highlighting new investment techniques, this book includes material to assist in the best execution process, model validation, quality and assurance testing, limit order modeling, and smart order routing analysis. Includes advanced modeling techniques using machine learning, predictive analytics, and neural networks. The text provides readers with a suite of transaction cost analysis functions packaged as a TCA library. These programming tools are accessible via numerous software applications and programming languages.

General

Imprint:	Academic Press Inc
Country of origin:	United States
Release date:	September 2020
First published:	2020
Authors:	Robert Kissell
Dimensions:	229 x 152 x 34mm (L x W x T)
Format:	Paperback
Pages:	612
Edition:	2nd edition
ISBN-13:	978-0-12-815630-8
Categories:	Books > Business & Economics > Business & management > Business strategy Books > Business & Economics > Finance & accounting > Finance > Banking Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Books > Business & Economics > Finance & accounting > Finance > Investment & securities > General Books > Money & Finance > Banking Books > Money & Finance > Investment & securities > General Promotions
LSN:	0-12-815630-9
Barcode:	9780128156308

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