Algorithmic Trading Methods : Applications Using Advanced Statistics, Optimization, and Machine Learning Techniques

Robert (President Kissell, Molloy College Professor, Fordham University) Adjunct Professor

ISBN 10: 0128156309 / ISBN 13: 9780128156308

Published by Elsevier Science Publishing Co Inc Sep 2020, 2020

About this Item

Neuware - Provides insights into all necessary components of algorithmic trading, including transaction costs analysis, market impact, risk and optimization, and a thorough and detailed discussion of trading algorithms Includes increased coverage of mathematics, statistics and machine learning Presents broad coverage of Alpha Model construction.

Seller Inventory # 9780128156308

Bibliographic Details

• Title: Algorithmic Trading Methods : Applications Using Advanced Statistics, Optimization, and Machine Learning Techniques
• Publisher: Elsevier Science Publishing Co Inc Sep 2020
• Publication Date: 2020
• Language: English
• ISBN 10: 0128156309
• ISBN 13: 9780128156308
• Binding: Taschenbuch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 238W x 191H x 34D millimeters 238 millimeters width by 191 millimeters height by 34 millimeters depth
• Weight: 1128 grams

About this title

Synopsis

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.

About the Author

Robert Kissell, Ph.D., is President of Kissell Research Group, a global financial and economic consulting firm specializing in quantitative modeling, statistical analysis, and algorithmic trading. He is also a professor at Molloy College in the School of Business and an adjunct professor at the Gabelli School of Business at Fordham University. He has held several senior leadership positions with prominent bulge bracket investment banks including UBS Securities where he was Executive Director of Execution Strategies and Portfolio Analysis, and at JP Morgan where he was Executive Director and Head of Quantitative Trading Strategies. He was previously at Citigroup/Smith Barney where he was Vice President of Quantitative Research, and at Instinet where he was Director of Trading Research. He began his career as an Economic Consultant at R.J. Rudden Associates specializing in energy, pricing, risk, and optimization. Dr. Kissell has written several books and published dozens of journal articles on Algorithmic Trading, Risk, and Finance. He is a coauthor of the CFA Level III reading titled “Trade Strategy and Execution,” CFA Institute 2019.”