Cover for Algorithmic Trading Methods

Algorithmic Trading Methods

Applications Using Advanced Statistics, Optimization, and Machine Learning Techniques

Book • Second Edition2020

Authors:

Robert L. Kissell

Algorithmic Trading Methods

Applications Using Advanced Statistics, Optimization, and Machine Learning Techniques

Book • Second Edition2020

 

Cover for Algorithmic Trading Methods

Authors:

Robert L. Kissell

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Book description

Algorithmic Trading Methods: Applications using Advanced Statistics, Optimization, and Machine Learning Techniques, Second Edition, is a sequel to The Science of Algorithmic Tradin ... read full description

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Table of contents

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  2. Book chapterNo access

    Chapter 1 - Introduction

    Pages 1-21

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    Chapter 2 - Algorithmic Trading

    Pages 23-56

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    Chapter 3 - Transaction Costs

    Pages 57-97

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    Chapter 4 - Market Impact Models

    Pages 99-128

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    Chapter 5 - Probability and Statistics

    Pages 129-150

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    Chapter 6 - Linear Regression Models

    Pages 151-173

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    Chapter 7 - Probability Models

    Pages 175-195

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    Chapter 8 - Nonlinear Regression Models

    Pages 197-219

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    Chapter 9 - Machine Learning Techniques

    Pages 221-231

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    Chapter 10 - Estimating I-Star Market Impact Model Parameters

    Pages 233-267

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    Chapter 11 - Risk, Volatility, and Factor Models

    Pages 269-299

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    Chapter 12 - Volume Forecasting Techniques

    Pages 301-322

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    Chapter 13 - Algorithmic Decision-Making Framework

    Pages 323-348

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    Chapter 14 - Portfolio Algorithms and Trade Schedule Optimization

    Pages 349-374

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    Chapter 15 - Advanced Algorithmic Modeling Techniques

    Pages 375-403

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    Chapter 16 - Decoding and Reverse Engineering Broker Models with Machine Learning Techniques

    Pages 405-428

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    Chapter 17 - Portfolio Construction with Transaction Cost Analysis

    Pages 429-467

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    Chapter 18 - Quantitative Analysis with TCA

    Pages 469-518

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    Chapter 19 - Machine Learning and Trade Schedule Optimization

    Pages 519-542

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    Chapter 20 - TCA Analysis Using MATLAB, Excel, and Python

    Pages 543-558

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    Chapter 21 - Transaction Cost Analysis (TCA) Library

    Pages 559-567

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    References

    Pages 569-576

  24. Book chapterNo access

    Index

    Pages 577-588

About the book

Description

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.

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.

Key Features

  • Provides insight into all necessary components of algorithmic trading including: transaction cost analysis, market impact estimation, risk modeling and optimization, and advanced examination of trading algorithms and corresponding data requirements
  • Increased coverage of essential mathematics, probability and statistics, machine learning, predictive analytics, and neural networks, and applications to trading and finance
  • Advanced multiperiod trade schedule optimization and portfolio construction techniques
  • Techniques to decode broker-dealer and third-party vendor models
  • Methods to incorporate TCA into proprietary alpha models and portfolio optimizers
  • TCA library for numerous software applications and programming languages including: MATLAB, Excel Add-In, Python, Java, C/C++, .Net, Hadoop, and as standalone .EXE and .COM applications
  • Provides insight into all necessary components of algorithmic trading including: transaction cost analysis, market impact estimation, risk modeling and optimization, and advanced examination of trading algorithms and corresponding data requirements
  • Increased coverage of essential mathematics, probability and statistics, machine learning, predictive analytics, and neural networks, and applications to trading and finance
  • Advanced multiperiod trade schedule optimization and portfolio construction techniques
  • Techniques to decode broker-dealer and third-party vendor models
  • Methods to incorporate TCA into proprietary alpha models and portfolio optimizers
  • TCA library for numerous software applications and programming languages including: MATLAB, Excel Add-In, Python, Java, C/C++, .Net, Hadoop, and as standalone .EXE and .COM applications

Details

ISBN

978-0-12-815630-8

Language

English

Published

2020

Copyright

Copyright © 2021 Elsevier Inc. All rights reserved.

Imprint

Academic Press

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Authors

Robert L. Kissell

President, Kissell Research Group and Adjunct Faculty Member, Gabelli School of Business, Fordham University, Manhasset, NY, United States