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Process Engineering and Best Practices for Systematic Trading and Investment PDF

280 Pages·2008·1.46 MB·English
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Quality Money Management Process Engineering and Best Practices for Systematic Trading and Investment The Financial Market Technology Series Series Editor Benjamin Van Vliet The Financial Market Technology Series is a partnership between Elsevier, Inc. and the Institute for Market Technology (i4mt) to publish cutting-edge books covering topics concerning the integration of technology with financial markets, including: ● automated trading, ● building trading and investment systems, ● operational issues in back office processing, ● clearing and settlement, and ● compliance and governance issues as they relate to technology. The goal of the series is to promote increased understanding and competency with tech- nology in the finance industry through publishing high-quality books on the latest areas of research and practice for professionals working in the financial markets. Series Editor: Ben Van Vliet is a Lecturer at the Illinois Institute of Technology (IIT), where he also serves as the Associate Director of the M.S. Financial Markets program. At IIT he teaches courses in quantitative finance, C (cid:2) (cid:2) and .NET programming, and auto- mated trading system design and development. He is vice chairman of the Institute for Market Technology, where he chairs the advisory board for the Certified Trading System Developer (CTSD) program. He also serves as series editor of the Financial Markets Technology series for Elsevier/Academic Press and consults extensively in the financial markets industry. Mr. Van Vliet is also the author of “Modeling Financial Markets” with Robert Hendry (2003, McGraw Hill) and “Building Automated Trading Systems” (2007, Academic Press). Additionally, he has published several articles in the areas of finance and technology, and presented his research at several academic and professional conferences. We welcome proposals for books for the series. Please go to www.books.elsevier.com/ finance where you will find a link to send us your proposal. Quality Money Management Process Engineering and Best Practices for Systematic Trading and Investment Andrew Kumiega Benjamin Van Vliet AMSTERDAM (cid:129) BOSTON (cid:129) HEIDELBERG (cid:129) LONDON (cid:129) NEW YORK (cid:129) OXFORD PARIS (cid:129) SAN DIEGO (cid:129) SAN FRANCISCO (cid:129) SINGAPORE (cid:129) SYDNEY (cid:129) TOKYO Academic Press is an imprint of Elsevier Academic Press is an imprint of Elsevier 30 Corporate Drive, Suite 400, Burlington, MA 01803, USA 525 B Street, Suite 1900, San Diego, California 92101-4495, USA 84 Theobald ’ s Road, London WC1X 8RR, UK Design Direction: Joanne Blank Cover Design: Joe Tenerelli Cover Images © Corbis Corporation This book is printed on acid-free paper. Copyright © 2008, Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permissions may be sought directly from Elsevier ’ s Science & Technology Rights Department in Oxford, UK: phone: ( (cid:2) 44) 1865 843830, fax: ((cid:2) 44) 1865 853333, E-mail: [email protected] You may also complete your request on-line via the Elsevier homepage ( http://elsevier.com ), by selecting “ Support & Contact ” then “ Copyright and Permission ” and then “ Obtaining Permissions. ” Library of Congress Cataloging-in-Publication Data Kumiega, Andrew. Quality money management : best practices and process engineering for systematic trading and investment / Andrew Kumiega, Benjamin Van Vliet. p. cm. Includes index. ISBN-10: 0-12-372549-6 (hardback : acid-free paper) ISBN-10: (invalid) 0-12-372549-3 (hardback : acid-free paper) ISBN-13: 978-0-12-372549-3 (hardback : acid-free paper) 1. Electronic trading of securities. 2. Finance—Mathematical models. 3. Investments—Mathematical models. 4. Financial engineering. I. Vliet, Benjamin Van. II. Title. HG4515.95.K86 2008 332.6—dc22 2007052636 British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library. ISBN: 978-0-12-372549-3 For information on all Academic Press publications visit our Web site at www.books.elsevier.com Typeset by Charon Tec Ltd (A Macmillan Company), Chennai, India www.charontec.com Printed and bound in the United States of America 08 09 10 10 9 8 7 6 5 4 3 2 1 Contents Preface vii 1 Introduction 1 2 Key Concepts and Definitions of Terms 15 3 Overview of the Trading/Investment System Development Methodology 29 4 Managing Design and Development 45 5 Types of Trading Systems 61 6 STAGE 0: The Money Document 67 STAGE I Design and Document Trading/Investment Strategy 79 7 STAGE 1: Overview 81 8 Describe Trading/Investment Idea 87 9 Research Quantitative Methods 97 10 Prototype in Modeling Software 105 11 Check Performance 115 12 Gate 1 123 S TAGE II Backtest 129 13 STAGE 2: Overview 131 14 Gather Historical Data 139 15 Develop Cleaning Algorithms 149 16 Perform In-Sample/Out-of-Sample Tests 157 v vi Contents 17 Check Performance and Shadow Trade 165 18 Gate 2 169 S TAGE III Implement 175 1 9 STAGE 3: Overview 177 20 Plan and Document Technology Specifications 183 21 Design System Architecture 193 22 Build and Document the System 205 23 Check Performance and Probationary Trade 213 24 Gate 3 221 S TAGE IV Manage Portfolio and Risk 227 25 STAGE 4: Overview 229 26 Plan Performance and Risk Processes 237 27 Define Performance Controls 245 28 Perform SPC Analysis 251 29 Determine Causes of Variation 263 30 Kaizen: Continuous Improvement 271 Endnotes 279 Index 287 Preface This book began several years ago as an attempt to provide a detailed road map for students to follow from the theoretical quantitative finance taught in graduate school to building a trading/investment system to manage real money in the real world. From our years of con- sulting and experience in building funds and through academic research, discussions with working students, and feedback from many colleagues, our perspective grew from writing a classical money management book with detailed equations for calculating trading signals and risk calculations to process engineering, statistical process control, Six Sigma, and soft- ware design. The original shift back to industrial engineering was slow in the beginning, but we kept going back to manufacturing examples to explain how to build trading/investment systems. Every class, job, and consulting assignment led us away from the financial litera- ture toward process engineering. Eventually, we both realized that the true missing theory in finance was not another equation, but a concise methodology to implement theoretical concepts. At colleges and universities around the world and in most industry publications, the mathematics of markets and trading is most often taught from a theoretical perspective using clean sample data, in spite of the practical nature of the discipline as well as the fact that most students are pursuing the knowledge for purely professional reasons. While most academics prefer to teach students highly mathematical theory, working students want to learn how to implement those theories in the real world and turn them into prof- itable ideas and careers. While academics prefer to find and explain degrees of market efficiency, working students hope one day to find and exploit inefficiencies. Students who lack experience in the real-world financial markets study mathematics diligently only to fail in interviews that ask for real-world knowledge. A gap exists between students of the markets and the educational service providers. Furthermore, students learn by doing. An ancient Chinese proverb states, “ I hear and I forget, I see and I remember, I do and I understand.” No class or homework assignment is sufficient for one to become a good trading/investment system architect. Due to time con- straints, students will not build their own components but rather buy off-the-shelf ones. The value is in learning how to test components and glue the pieces together to build a complete system. Does the school attempt to organize its curriculum around a process vii viii Preface for solving real-world problems, similar to engineering disciplines, or does it more or less offer a smattering of courses in mathematics related to finance? Just as with product teams, for students to implement financial theory in the real world, they need a step-by- step process to follow. Other engineering disciplines have confronted this same problem and chosen to design courses around building products using real-world machines and real companies. In this book, we present an overview of the body of knowledge of finance, linking topics to create a linear progression of steps toward solutions to a business problem—how to build trading and investment systems. We have not written in-depth chapters on areas that are covered in detail in dozens of other books and hundreds of papers. We had a difficult time drawing the line between adding in-depth quantitative finance information and focusing solely on higher-level processes. Like graduate students doing research, we often wandered off the path to smell the surroundings, only to force our- selves back on the road to present a process map. For the interested reader who intends to sniff the mathematical and technological flowers close up, we recommend the readings in the end notes or searching the Internet for papers and books on topics of interest. As one can imagine, additional credit for completion of this project must be given to many friends, family, and colleagues, in particular to the many individuals who read drafts of the chapters and provided invaluable feedback, including Bruce Rawlings, Debbie Cernauskas, Fabian Valencia, Mulianto The, Dr. Zia Hassan, Assad Fehmy, Jason Malkin, Batavia, Larissa J. Miller, Dr. Joe Wojkowski, Matt Lech, and Josip Roleta; and all of our colleagues at the Illinois Institute of Technology’ s Stuart School of Business: Russell Wojcik, Dr. Michael Gorham, Keith Black, Dr. Michael Ong, Dr. John Bilson, Dr. Michael Kelly, and Jodi Houlihan. Also we would like to thank the many students at IIT who have also provided valuable feedback. Certainly without their help and the help of many others this book would never have been completed. Andy Kumiega also thanks Megan, Kayla, Carrie, and Therese Kumiega for their long-term support. He also thanks Dr. Miller, Dr. Rice, and Dr. Cesarone for their guid- ance and support in graduate school. Ben Van Vliet thanks his wife Julia for putting up with late nights and long weekends of research and writing. W e hope you learn from our research the topic of process engineering for trading and investment systems and are inspired to delve deeper into the topic. Please provide us with any feedback you may have. CHAPTER ◆ 1 Introduction In the financial markets, the competition gets tougher every day. Today, the difference between 25th and 75th percentile performance of money managers in some sectors of the industry is measured in basis points. The only trading and money management firms that survive now are the ones that continually discover cutting-edge position selection strategies and technologies to build better quality trading and investment systems. Where once traders and money managers based decisions on greed and hope, now rational self- interest controls discovery processes that promote fact-based decisions and implement proven research. Entrepreneurs refer to the discovery process as knowledge-based innovation. In finance it has begotten a new discipline: systematic trading and investment, the reasoned study of financial markets using the scientific method to explain and replicate market phe- nomena and the use of computer automation to make profitable trading/investment deci- sions. Today, entrepreneurial activity in financial markets revolves around the practice of systematic innovation1 to build new (and shut down old) trading and investment systems. A top-rated hedge fund company stopped accepting new money in 2004 and started liquidating posi- tions. In 2005 management shut down the fund completely. Their diligent and continuous research made it clear that their models were no longer working. There was a fundamental shift in their ability to arbi- trage convertible bonds and they told their investors to take their money back. Every investor is waiting anxiously for them to open their next fund. (Compare that to Long Term Capital Management.) Ideally, the hedge fund manager should have been building new strategies ahead of time so that they could have kept the customers ’ money by switching funds. T he key determinant of sustainable competitive advantage is the ability to continu- ally discover, build, and operate better trading/investment systems. Which is to say, in financial markets the new business model is quality: higher returns, lower risk, and lower cost, all at a faster time-to-market. This model is complicated, though, by the tendency of many skillful fund managers, traders, and financial engineers to fall short when it comes to process engineering. 2 Other industries have faced this same problem. In manufacturing plants, small margins demand reductions in waste and costs of reworking defective parts. High quality is necessary to gain and maintain market share. 1

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