The Science of Algorithmic Trading and Portfolio Management

1st Edition

Authors: Robert Kissell
Print ISBN: 9780124016897
eBook ISBN: 9780124016934
Imprint: Academic Press
Published Date: 1st July 2013
Page Count: 496
53.95 + applicable tax
42.99 + applicable tax
69.95 + applicable tax
Compatible Not compatible
VitalSource PC, Mac, iPhone & iPad Amazon Kindle eReader
ePub & PDF Apple & PC desktop. Mobile devices (Apple & Android) Amazon Kindle eReader
Mobi Amazon Kindle eReader Anything else

Institutional Access


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.


    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




    Chapter 1. Algorithmic Trading


    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


    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


    Chapter 3. Algorithmic Transaction Cost Analysis


    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



    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


    Scientific Method

    Solution Technique

    Chapter 6. Price Volatility



    Market Observations—Empirical Findings

    Forecasting Stock Volatility

    HMA-VIX Adjustment Model

    Measuring Model Performance

    Factor Model


    No. of pages:
    © Academic Press 2014
    Academic Press
    eBook ISBN:
    Hardcover ISBN:

    About the Author

    Robert Kissell

    Robert Kissell is an Executive Director responsible for analytics product initiatives within UBS Direct Execution and UBS Portfolio Trading. Prior to joining UBS, he was with JP Morgan where he served as Head of Quantitative Trading Strategies.

    Affiliations and Expertise

    Executive Director, analytics product initiatives, UBS Direct Execution and UBS Portfolio Trading


    "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.", 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