The Science of Algorithmic Trading and Portfolio ManagementThe Science of Algorithmic Trading and Portfolio ManagementRobert Kissell Ph.DAMSTERDAM BOSTON HEIDELBERG LONDON NEW YORK OXFORD PARIS SAN DIEGO SAN FRANCISCO SINGAPORE SYDNEY TOKYO Academic Press is an imprint of ElsevierAcademic Press is an imprint of Elsevier 525 B Street, Suite 1800, San Diego, CA 92101?4495, USA The Boulevard, Langford Lane, Kidlington, Oxford, OX5 1GB, UK 225 Wyman Street, Waltham, MA 02451, USAFirst published 2014 Copyright r 2014 Elsevier Inc. All rights reservedNo part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher.Permissions may be sought directly from Elseviers Science fax (144) (0) 1865 853333; email: permissionselsevier.com. Alternatively, visit the Science and Technology Books website at www.elsevierdirect.com/rights for further information.Notice No responsibility is assumed by the publisher for any injury and/or damage to persons, or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made.British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British LibraryLibrary of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of CongressISBN: 978-0-12-401689-7For information on all Academic Press publications visit our website at elsevierdirect.comPrinted and bound in United States of America14 15 16 1710 9 8 7 6 5 4 3 2 1Landon and MasonA continuous source of joy and inspirationAnd a reminder to keep asking why why why.PrefaceIf we knew what it was we were doing, it would not be called research, would it? Albert EinsteinThe Science of Algorithmic Trading and Portfolio Management is a reference book intended to provide traders, portfolio managers, analysts, students, practitioners, and financial execu- tives with an overview of the electronic trading environment, and insight into how algorithms can be utilized to improve execution quality and fund performance.We provide a discussion of the current state of the market and advanced modeling techniques for trading algorithms, stock selection, and portfolio construction.This reference book will provide readers with:GAn understanding of the new electronic trading environment.GAn understanding of transaction cost analysis (TCA) and proper metrics for cost measurement and performance evaluation.GA thorough understanding of the different types of trading algorithms: liquidity seeking, dark pools, arrival price, implementation shortfall (IS), volume weighted average price (VWAP), arrival price, and portfolio implementation shortfall.GProven market impact modeling techniques.GAn understanding of algorithmic trading across various asset classes: equities, futures, fixed income, foreign exchange, and commodities.GAdvanced algorithmic forecasting techniques to estimate daily liquidity and monthly volumes.GAn algorithmic decision making framework to ensure consistency between investment and trading objectives.GA best execution process.Readers will subsequently be prepared to:GDevelop real-time trading algorithms customized to specific institutional needs.GDesign systems to manage algorithmic risk and dark pool uncertainty.GEvaluate market impact models and assess performance across algorithms, traders, and brokers.GImplement electronic trading systems.For the first time, portfolio managers are not forgotten and will be provided with proven techniques to better construct portfolios through:GStock SelectionGPortfolio OptimizationGAsset AllocationGMI Factor ScoresxvGMulti-Asset InvestingGFactor Exposure InvestingThe book is categorized in three parts. Part I focuses on the current electronic market envi- ronment where we discuss trading algorithms, market microstructure research, and transac- tion cost analysis. Part II focuses on the necessary mathematical models that are used to construct, calibrate, and test market impact models, as well as to develop single stock and portfolio trading algorithms. The section further discusses volatility and factor models, as well as advanced algorithmic forecasting techniques. Part III focuses on portfolio manage- ment techniques and how TCA and market impact can be incorporated into the investment decisions, stock selection, and portfolio construction to improve portfolio performance. We introduce readers to an advanced portfolio optimization process that incorporates market impact and transaction costs directly into the portfolio optimization. We provide insight into how MI factor scores can be used