George Soros, a poor Hungarian immigrant with a philosophical bent and a London School of Economics degree, founded Quantum Capital in the late 1960s and led it to breathtaking returns, famously “breaking the Bank of England” in 1992 by shorting the pound sterling. Julian Robertson, the hard-charging North Carolina charmer who made huge contrarian bets on stocks, built the Tiger Fund in the 1970s and seeded dozens of Tiger Cubs that collectively manage hundreds of billions of dollars. John Meriwether left Salomon Brothers to collect a stable of PhDs in quantitative finance from the University of Chicago to form the envied, and later notorious, Long-Term Capital Management (LTCM). Each of these groups earned persistent returns for their investors that exceeded 30 percent per year, handily trouncing the market indexes. Each of their partners became billionaires, likely faster than ever before in history.
Each of these financial legends, and hundreds of other lesser-known investors, built a hedge fund. Private pools of funds have existed for as long as liquid capital markets—at least 800 years—but the first hedge fund is generally thought to be Albert Winslow Jones’ “hedged fund,” formed in the late 1940s. Since then, the number of such funds has grown into the thousands, and they manage trillions of dollars in clients’ funds.
Hedge funds are the least understood form of Wall Street institution—partly by design. They are secretive, clannish, and barely visible. Hedge funds have received a generous share of envy when successful and have been demonized when financial markets have melted down. But whether you wish to join them or beat them, first you need to understand them, and how they make their money.
Hedge funds are pools of money from “accredited” investors—relatively wealthy individuals and institutions assumed to have sufficient sophistication to protect their own interests. Therefore, unlike publicly traded company stock, mutual funds, and exchange traded funds (ETFs), hedge funds are exempt from most of the laws governing institutions that invest on behalf of clients. Implicitly, policy makers seem to believe that little regulation is necessary. The absence of scrutiny has helped hedge funds keep their trading strategies secret.
The scale of hedge funds has grown tremendously in the past few decades, as illustrated in Figure 1.1. The amount of funds under management has grown by a factor of 15 from 1997 to 2013. Hedge funds today represent a large minority of all liquid assets in the United States, and only a somewhat smaller fraction worldwide (Figure 1.2).
These lightly regulated funds continually adopt innovative investing and trading strategies to take advantage of temporary mispricing of assets (when their market price deviates from their intrinsic value). These techniques are shrouded in mystery, which permits hedge fund managers to charge exceptionally high fees. While the details of the approach of each of the funds are carefully guarded trade secrets, this book draws the curtain back on the core building blocks of many hedge fund strategies. As an instructional text, it will assist two types of students:
• Economics and finance students interested in understanding what “quants” do, and
• Software specialists interested in applying their skills to programming trading systems.
Figure 1.1 Total hedge fund assets under management, 1997 to 2013
Figure 1.2 Hedge funds compared with other asset classes
A number of fine journalistic accounts of the industry exist—and should be read by anyone interested in understanding this industry—which offer interesting character studies and valuable cautionary tales. These include The Quants, by Scott Patterson (2010), The Big Short and Flash Boys, by Michael Lewis (2010 and 2014, respectively), More Money Than God: Hedge Funds and The Making of the New Elite, by Sebastian Mallaby (2010), and When Genius Failed: The Rise and Fall of Long-Term Capital Management (2000), by Roger Lowenstein. But none dives very deeply into how quantitative strategies work. Many readers seek such tools so that they can improve current practice—from the inside, at hedge funds; or from the outside, as regulators, journalists, or advocates.
This book is a modest attempt to explain what hedge funds really do. Our focus is on the trading strategies that hedge funds use. We will provide basic investing and portfolio management background to the uninitiated and then move on to the computational details of efforts to automate trading strategies in machine learning systems.
This book is organized in modules; not all modules will be of interest to all readers. The main elements are as follows:
• Part I (Investing Basics) is a short introduction to investing for readers without prior financial training. Those with such training will find it worth a scan to refresh your recollection.
• Part II (Investing Fundamentals) outlines how to “optimize” a collection of investments—a portfolio—to maximize the ratio of return to risk within any constraints imposed by your situation.
• Parts I and II together constitute the financial background that computer scientists will need to program trading systems. Part III constitutes the core techniques of interest to programmers.
• Part III (Market Simulation and Portfolio Construction) describes the heart of most “quant” (quantitative) hedge funds’ strategies—testing proposed trading rules based on historical market experience.
• Part IV (Case Study and Future Directions) provides important context regarding recent and prospective developments in the hedge fund industry, which will set the environment in which investors, quants, and programmers will operate.
• Finally, the back matter includes a glossary and a list of related teaching cases for use by instructors who use this book in their courses.
The book will be of interest to a variety of readers:
• Individual investors considering investing in “quant” mutual funds and ETFs, which are increasingly prevalent as Wall Street markets “absolute return” and “liquid alternative” products to you.
• IT students who need to understand the investing background behind the trading systems; they will design and program.
• Finance students who need an introduction to the IT underlying trading systems.
• Investing students who wish to understand how quant strategies can affect their portfolios.
• Public policy makers interested in asset market regulation.
• Journalists who wish to understand the markets they cover.
Read carefully the portions least familiar to you, and skim the familiar parts for refresher.
The two authors are, respectively, an economist and a former government official who made public policy regarding financial institutions; and a robotics specialist and former fighter pilot who founded a software firm that designs analytic platforms for hedge funds. We bring diverse perspectives to this topic, and we imagine that you may likewise be interested in more than one aspect. This book is broader than it is deep. We hope we stimulate your appetite to learn more about this growing, powerful, but little-known industry—and about the techniques that built its power.
Julian Robertson, Tiger Management
Born: Julian Harr Robertson, 1932
Firm: Tiger Management
Operated: 1980 to 2000 (seeded “Tiger Seeds” and “Tiger Cubs” in the early 2000s)
Annual return: 31.7 percent (1980 to 1998); 26 percent (1980 to 2000)
AUM at peak: $22 billion (1998)
Style: Long/short equity; added an international macro overlay in the 1990s
Robertson’s background: Raised in North Carolina, with a syrupy Southern charm. During the 1970s when working at Kidder Peabody, Robertson befriended Bob Burch, A. W. Jones’s son-in-law, and later Jones himself. Robertson quizzed Jones about trading strategies and hedge fund structures.
When he formed Tiger in 1980, Burch invested $5 million, 20 percent of the surviving Jones assets.
Differentiation: Tiger emphasized bottom-up domestic stock selection, adding international equities and a global macro view in the early 1990s. “Our mandate is to find the 200 best companies in the world and invest in them, and find the 200 worst companies in the world and go short on them. If the 200 best don’t do better than the 200 worst, you should probably be in another business.”
Color: “Tall, confident, and athletic of build, he was a guy’s guy, a jock’s jock, and he hired in his own image. To thrive at Tiger Management, you almost needed the physique: otherwise, you would be hard-pressed to survive the Tiger retreats, which involved vertical hikes and outward-bound contests. The Tigers would fly out west . . . and be taken to a hilltop. They would split up into teams, each equipped with logs the size of telephone poles, some rope, and two paddles. They would heave the equipment down to the nearby lake, lash the logs together, and race out to a buoy—with the twist that not all of the team could fit on the raft, so some had to plunge into the icy water” (from Mallaby’s More Money Than God).
Legacy: After Robertson restructured and wound down Tiger in 1998 to 2000, he seeded 36 funds founded by Tiger alumni, deemed “Tiger Seeds” and “Tiger Cubs.” According to Hennessee group LLC hedge fund advisory, the 18 Tiger Cubs for which performance information could be found returned nearly three times Hennessee’s index of long/short hedge funds (11.89 percent versus 4.44 percent annually) from 2000 to 2008, with slightly less risk (7.42 percent versus 7.76 percent standard deviation), yielding nearly 3 times the Sharpe ratio (1.42 for the cubs versus 0.47 for the index). Robertson’s personal investments in Tiger offspring perform handsomely: Forbes reports that in 2009 his personal trading account earned 150 percent.