Algorithmic Trading Methods
eBook - ePub

Algorithmic Trading Methods

Applications Using Advanced Statistics, Optimization, and Machine Learning Techniques

  1. 612 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Algorithmic Trading Methods

Applications Using Advanced Statistics, Optimization, and Machine Learning Techniques

About this book

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.- 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

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Yes, you can access Algorithmic Trading Methods by Robert Kissell in PDF and/or ePUB format, as well as other popular books in Economics & Finance. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Academic Press
Year
2020
eBook ISBN
9780128156315
Edition
2
Topic
Economics
Subtopic
Finance
Index
Economics

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Preface
  6. Acknowledgments
  7. Chapter 1. Introduction
  8. Chapter 2. Algorithmic Trading
  9. Chapter 3. Transaction Costs
  10. Chapter 4. Market Impact Models
  11. Chapter 5. Probability and Statistics
  12. Chapter 6. Linear Regression Models
  13. Chapter 7. Probability Models
  14. Chapter 8. Nonlinear Regression Models
  15. Chapter 9. Machine Learning Techniques
  16. Chapter 10. Estimating I-Star Market Impact Model Parameters
  17. Chapter 11. Risk, Volatility, and Factor Models
  18. Chapter 12. Volume Forecasting Techniques
  19. Chapter 13. Algorithmic Decision-Making Framework
  20. Chapter 14. Portfolio Algorithms and Trade Schedule Optimization
  21. Chapter 15. Advanced Algorithmic Modeling Techniques
  22. Chapter 16. Decoding and Reverse Engineering Broker Models with Machine Learning Techniques
  23. Chapter 17. Portfolio Construction with Transaction Cost Analysis
  24. Chapter 18. Quantitative Analysis with TCA
  25. Chapter 19. Machine Learning and Trade Schedule Optimization
  26. Chapter 20. TCA Analysis Using MATLAB, Excel, and Python
  27. Chapter 21. Transaction Cost Analysis (TCA) Library
  28. References
  29. Index