The Science of Algorithmic Trading and Portfolio Management - 1st Edition - ISBN: 9780124016897, 9780124016934

The Science of Algorithmic Trading and Portfolio Management

1st Edition

Authors: Robert Kissell
Hardcover ISBN: 9780124016897
eBook ISBN: 9780124016934
Imprint: Academic Press
Published Date: 1st July 2013
Page Count: 496
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Description

The Science of Algorithmic Trading and Portfolio Management, with its emphasis on algorithmic trading processes and current trading models, sits apart from others of its kind. Robert Kissell, the first author to discuss algorithmic trading across the various asset classes, provides key insights into ways to develop, test, and build trading algorithms. Readers learn how to evaluate market impact models and assess performance across algorithms, traders, and brokers, and acquire the knowledge to implement electronic trading systems.

This valuable book summarizes market structure, the formation of prices, and how different participants interact with one another, including bluffing, speculating, and gambling. Readers learn the underlying details and mathematics of customized trading algorithms, as well as advanced modeling techniques to improve profitability through algorithmic trading and appropriate risk management techniques. Portfolio management topics, including quant factors and black box models, are discussed, and an accompanying website includes examples, data sets supplementing exercises in the book, and large projects.

Key Features

  • Prepares readers to evaluate market impact models and assess performance across algorithms, traders, and brokers.
    • Helps readers design systems to manage algorithmic risk and dark pool uncertainty.
    • Summarizes an algorithmic decision making framework to ensure consistency between investment objectives and trading objectives.

    Readership

    Students and professors studying stock selection and portfolio management, as well as traders, practitioners, and portfolio managers working in the financial industry..

    Table of Contents

    Dedication

    Preface

    Acknowledgments

    Chapter 1. Algorithmic Trading

    Introduction

    Changing Trading Environment

    Recent Growth in Algorithmic Trading

    Investment Cycle

    Classifications of Algorithms

    Types of Algorithms

    Algorithmic Trading Trends

    Trading Venue Classification

    Types of Orders

    Execution Options

    The Trading Floor

    Algorithmic Trading Decisions

    Algorithmic Analysis Tools

    High Frequency Trading

    Direct Market Access

    Chapter 2. Market Microstructure

    Introduction

    Market Microstructure Literature

    The New Market Structure

    Pricing Models

    Order Priority

    Equity Exchanges

    New NYSE Trading Model

    NASDAQ Select Market Maker Program

    Empirical Evidence

    Flash Crash

    Conclusion

    Chapter 3. Algorithmic Transaction Cost Analysis

    Introduction

    Unbundled Transaction Cost Components

    Transaction Cost Classification

    Transaction Cost Categorization

    Transaction Cost Analysis

    Implementation Shortfall

    Evaluating Performance

    Comparing Algorithms

    Experimental Design

    Final Note on Post-Trade Analysis

    Chapter 4. Market Impact Models

    Introduction

    Definition

    Graphical Illustrations of Market Impact

    Developing a Market Impact Model

    Derivation of Models

    I-Star Market Impact Model

    Model Formulation

    Parameter Estimation Techniques

    Chapter 5. Estimating I-Star Model Parameters

    Introduction

    Scientific Method

    Solution Technique

    Chapter 6. Price Volatility

    Introduction

    Definitions

    Market Observations—Empirical Findings

    Forecasting Stock Volatility

    HMA-VIX Adjustment Model

    Measuring Model Performance

    Factor Models

    Types of Factor Models

    Chapter 7. Advanced Algorithmic Forecasting Techniques

    Introduction

    Trading Cost Equations

    Trading Strategy

    Trading Time

    Trading Risk Components

    Trading Cost Models—Reformulated

    Timing Risk Equation

    Comparison of Market Impact Estimates

    Volume Forecasting Techniques

    Forecasting Monthly Volumes

    Forecasting Covariance

    Efficient Trading Frontier

    Chapter 8. Algorithmic Decision Making Framework

    Introduction

    Equations

    Algorithmic Decision Making Framework

    Chapter 9. Portfolio Algorithms

    Introduction

    Trader’s Dilemma

    Transaction Cost Equations

    Optimization Formulation

    Portfolio Optimization Techniques

    Portfolio Adaptation Tactics

    Managing Portfolio Risk

    Appendix

    Chapter 10. Portfolio Construction

    Introduction

    Portfolio Optimization and Constraints

    Transaction Costs in Portfolio Optimization

    Portfolio Management Process

    Trading Decision Process

    Unifying the Investment and Trading Theories

    Cost-Adjusted Frontier

    Determining the Appropriate Level of Risk Aversion

    Best Execution Frontier

    Portfolio Construction with Transaction Costs

    Conclusion

    Chapter 11. Quantitative Portfolio Management Techniques

    Introduction

    Are the Existing Models Useful Enough for Portfolio Construction?

    Pre-Trade of Pre-Trades

    How Expensive is it to Trade?

    MI Factor Scores

    Alpha Capture Program

    Chapter 12. Cost Index & Multi-Asset Trading Costs

    Introduction

    Cost Index

    Real-Time Cost Index

    Multi-Asset Class Investing

    Multi-Asset Trading Costs

    Chapter 13. High Frequency Trading and Black Box Models

    Introduction

    Data and Research

    Strategies

    Evaluation

    Summary

    References

    Index

    Details

    No. of pages:
    496
    Language:
    English
    Copyright:
    © Academic Press 2014
    Published:
    Imprint:
    Academic Press
    eBook ISBN:
    9780124016934
    Hardcover ISBN:
    9780124016897

    About the Author

    Robert Kissell

    Dr. Robert Kissell is the president and founder of Kissell Research Group. He has over twenty years of experience specializing in economics, finance, math & statistics, risk, and sports modeling.

    Dr. Kissell is author of the leading industry books, “The Science of Algorithmic Trading & Portfolio Management,” (Elsevier, 2013), “Multi-Asset Risk Modeling” (Elsevier, 2014), and “Optimal Trading Strategies,” (AMACOM, 2003). He has published numerous research papers on trading, electronic algorithms, risk management, and best execution. His paper, “Dynamic Pre-Trade Models: Beyond the Black Box,” (2011) won Institutional Investor’s prestigious paper of the year award.

    Dr. Kissell is an adjunct faculty member of the Gabelli School of Business at Fordham University and is an associate editor of the Journal of Trading and the Journal of Index Investing. He has previously been an instructor at Cornell University in their graduate Financial Engineering program.

    Dr. Kissell has worked with numerous Investment Banks throughout his career including UBS Securities where he was Executive Director of Execution Strategies and Portfolio Analysis, and at JPMorgan 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.

    During his college years, Dr. Kissell was a member of the Stony Brook Soccer Team and was Co-Captain in his Junior and Senior years. It was during this time as a student athlete where he began applying math and statistics to sports modeling problems. Many of the techniques discussed in “Optimal Sports Math, Statistics, and Fantasy” were developed during his time at Stony Brook, and advanced thereafter. Thus, making this book the byproduct of decades of successful research.

    Dr. Kissell has a Ph.D. in Economics from Fordham University, an MS in Applied Mathematics from Hofstra University, an MS in Business Management from Stony Brook University, and a BS in Applied Mathematics & Statistics from Stony Brook University.

    Affiliations and Expertise

    Robert Kissell, PhD, 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 currently an adjunct faculty member of the Gabelli School of Business at Fordham University, and has held several senior leadership positions with prominent bulge bracket Investment Banks.

    Reviews

    "Kissell... introduces the mathematical models for constructing, calibrating, and testing market impact models that calculate the change in stock price caused by a large trade or order, and presents an advanced portfolio optimization process that incorporates market impact and transaction costs directly into portfolio optimization."--ProtoView.com, March 2014
    "This book provides excellent coverage of the challenges faced by portfolio managers and traders in implementing investment ideas and the advanced modeling techniques to address these challenges."--Kumar Venkataraman, Southern Methodist University