The Science of Algorithmic Trading and Portfolio Management, 1st Edition

  • Published By:
  • ISBN-10: 0124016936
  • ISBN-13: 9780124016934
  • DDC: 332.6
  • Grade Level Range: College Freshman - College Senior
  • 496 Pages | eBook
  • Original Copyright 2013 | Published/Released June 2014
  • This publication's content originally published in print form: 2013

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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.

Table of Contents

Front Cover.
Half Title Page.
Title Page.
Copyright Page.
Dedication Page.
Algorithmic Trading.
1: Market Microstructure.
2: Algorithmic Transaction Cost Analysis.
3: Market Impact Models.
4: Estimating I-Star Model Parameters.
5: Price Volatility.
6: Advanced Algorithmic Forecasting Techniques.
7: Algorithmic Decision Making Framework.
8: Portfolio Algorithms.
9: Portfolio Construction.
10: Quantitative Portfolio Management Techniques.
11: Cost Index & Multi-Asset Trading Costs.
12: High Frequency Trading and Black Box Models.