Über die Autorin bzw. den Autor

Richard Tortoriello is the aerospace and defense analyst in the equity research division of Standard & Poor's and has also conducted numerous quantitative investment studies for the company. He is responsible for buy, sell, and hold recommendations on twenty-five aerospace- and defense-related stocks, including General Electric, Boeing, United Technologies, Lockheed Martin, and Honeywell. He has been interviewed numerous times for Bloomberg Television, CNBC, BBC TV, CNN, The Wall Street Journal, The New York Times, and The Washington Post.

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QUANTITATIVE STRATEGIES FOR ACHIEVING ALPHA

The McGraw-Hill Companies, Inc.

Contents

Chapter One

I do not know what I may appear to the world; but to myself I seem to have been like a boy playing on the sea-shore, and diverting myself now and then finding a smoother pebble or a prettier shell than ordinary, whilst the great ocean of truth lay all undiscovered before me.

Sir Isaac Newton

Don Quixote: Dost thou see? A monstrous giant of infamous repute whom I intend to encounter.

Sancho Panza: It's a windmill.

Don Quixote: A giant! Canst thou not see the four great arms whirling at his back?

Sancho Panza: A giant?

Don Quixote: Exactly!

From Man of La Mancha, Dale Wasserman, Miguel de Cervantes

I've read with interest the journals of Meriwether Lewis and William Clark as they undertook, at the request of Thomas Jefferson, to explore the unknown western frontier and to find a route to the Pacific. These journeys contained as many dangers as they held wonders (and were financed by Congress for $2,500—the dollar went further back then). Their expedition, which did much to open the West to further exploration and settlement, became known as the Corps of Discovery. Although the greatest dangers faced by the author of this work were perhaps fatigue and eye strain—a far cry from grizzly bear, white-water rapids, and belligerent natives—the same spirit of discovery motivated the undertaking of the tests and explorations that form the basis of this book.

Unlike the western United States in the early 1800s, the frontiers of finance have been well charted. Many of the investment field's greatest minds have put their ideas and methods, earned through years of hard work and experience, down on paper for anyone with a few dollars or a library card to explore. The student of common stock investing can find hundreds of books covering almost every imaginable topic, from valuation analysis, to risk arbitrage, to day trading. With such a vast literature, developed by thousands of market participants over many decades, one might ask What is there left to discover?

One answer, I believe, is that, while investment theory has been mapped out well qualitatively—based on the experiences and insights of market participants—it has yet to be mapped out comprehensively from an empirical point of view. The reason for the wealth of qualitative literature and dearth of quantitative (outside of the university) is quite simply that investing is more art than science. Some of the best investment strategies are too dependent on the capabilities of the human mind to be reduced to a few lines of computer code. However, the advent of the personal computer and the database has provided a wonderful tool with which many investment strategies can be effectively modeled and tested. Numerous individual quantitative studies have been published, particularly in academia. Most, however, have been specialized, and some have been of questionable practical value. Quantitative professionals, on the other hand, have primarily written technical volumes (how-to guides for quantitative analysis), when they have written anything at all.

My quest began with two primary goals: to create a series of quantitative stock selection models for the Standard & Poor's Equity Research department and to provide myself and others with a "map" of the market from a quantitative point of view. This book presents investors with this map, as far as I have been able to draw it. Specifically, the work seeks to determine empirically the major fundamental and market-based drivers of future stock market returns. To arrive at this empirically drawn investment map, we tested well over 1,200 investment strategies: some worked well, and others didn't. Some of the strategies presented here are well known and widely employed; others are less well known and much less used outside of the world of professional money management. However, all of the factors presented in this book work, from a quantitative standpoint.

A true quantitative investor uses sophisticated mathematical models to gain an edge, sometimes ever so slight, over the market. This edge is then magnified with lots of money and lots of leverage (borrowed money). This book is not written for the "quant." Indeed, I am not qualified to write such a book. Readers need neither a Ph.D. in math nor an advanced knowledge of statistics to understand any of the tests contained herein. What readers do need is some interest in quantitative analysis and a desire to understand the basic drivers of stock market returns. This book was written with qualitative investors in mind, particularly those who wish to "understand" the stock market from a quantitative (empirical) point of view and who desire to integrate quantitative screens, tests, or models into their investment process—or simply into their thinking. Such integration is where art meets science. My personal belief is that the quantitative approaches outlined in this book can provide a proven way to generate investment ideas for the qualitative investor as well as a discipline that can help improve investment results.

QUANTITATIVE VERSUS QUALITATIVE ANALYSIS

Perhaps a couple definitions are in order here. Quantitative analysis differs from qualitative analysis in a variety of ways. In qualitative analysis, the investor typically focuses on a small number of individual companies and conducts research on each to determine its business strengths and weaknesses, its market opportunities and competitive position, the capabilities of management, and the comparative value offered by its stock relative to other stocks available for purchase. Qualitative investors often use a company's historical record (income statement, balance sheet, cash flow statement, etc.) as a jumping off point to project future trends in earnings and cash flows. The focus in qualitative analysis, as in the stock market itself, is on the future. Analytical techniques are tailored to the company and industry in question, and the investor seeks to make large gains in individual stocks. In short, qualitative analysis favors depth over breadth and the art of investment over a more "scientific" approach.

Quantitative analysis, on the other hand, seeks to discover overall tendencies or trends in the investment markets, particularly those that are predictive of future "excess" returns. To identify these trends, the quantitative analyst examines large numbers of companies over long periods of time. Analysis is by necessity standardized and depends entirely on the historical record: income statement, balance sheet, cash flow statement, and market- based data. That is, unlike most qualitative research, quantitative tests primarily look backward. Quantitative analysis emphasizes breadth over depth and science (testing and observation) over art. The quantitative analyst may apply the art of investment analysis in devising investment models and backtests, but once the models are determined, they're often purely mechanical in their operation. In sum, quantitative analysis relies primarily on computer-assisted inquiry, while qualitative analysis relies primarily on the workings of the human mind.

Although there are many similarities between the computer and the human mind, there are also vast differences. Of the two, only the human being can stake any real claim to intelligence. The mind has the...