Last Updated on April 24, 2022 by Oddmund Groette
David Shaw, the King of Quant, was one of the objects interviewed in Jack Schwager’s Stock Market Wizards. How did he make it into the book? Because of his superb annual returns. Schwager’s book is a bit old, published in 2001, but since D.E. Shaw’s flagship fund inception in 1988, it managed 22% annual returns until the year 2000. What is D.E. Shaw’s investment strategy? To look for statistical anomalies in the markets, just like Jim Simon’s Medallion Fund.
This article looks at the trading strategies employed by D.E. Shaw, gives a background of its founder, David E. Shaw, and summarizes our main takeaway from the interview in Jack Schwager’s book.
We start with a short description of the firm D.E. Shaw and a bit longer description of its founder, David Shaw:
What is D.E. Shaw?
D.E. Shaw is a quantitative hedge fund founded by David. E. Shaw, hence the name. It was founded in 1988 and has later made fantastic returns, even when the founder later decided to “retire”. The hedge fund manages billions of dollars and was early labeled the king of quant.
Who is David Shaw?
David Shaw is an American scientist and former hedge fund manager. He founded D.E Shaw & Co. He was a former assistant professor of computer science at Columbia University.
He grew up in Los Angeles, CA. David’s father was a theoretical physicist who specialized in plasma and fluid flows, and his mother was an artist and educator.
David graduated from the University of California with a bachelor’s degree and earned his Ph.D. from Stanford University in 1980. He then became an assistant professor of computer science at Columbia University.
At Columbia University, he researched massively parallel computing with the NON-VON supercomputer. This supercomputer is composed of processing elements in a tree structure meant for fast relational database searches. In his early career, he founded Stanford Corp.
He joined Morgan Stanley as vice president for technology in Nunzio Tartaglia’s automated proprietary trading group in 1986. He then started his hedge fund, D.E Shaw & Co., known for its use of sophisticated mathematical modeling and algorithms, in 1988.
David made his fortune by taking advantage of inefficiencies in the market using a state-of-the-art high-speed computer network.
In 1994, He was appointed by President Clinton to the president’s Council of Advisors on science and technology, where he headed the panel on educational technology.
In 1996, David was called “King Of Quant” by Fortune Magazine because of his firm’s role in pioneering high-speed quantitative trading. By 2001, he had turned into a full-time scientific researcher in computation biochemistry — specifically the molecular dynamics simulations of proteins.
In 2002, he created an executive committee to manage the company, then retired from the company’s day-to-day activities.
He was on the board of directors of the American Association for the Advancement of Science in 2000 and served as its treasurer from 2000 to 2007. Additionally, he was appointed as a fellow of the American Academy of Arts and Sciences in 2007.
Again, he was appointed by President Obama to the president’s Council of Advisors on Science and Technology in 2009. He was appointed to the National Academy of Engineering in 2002. In 2014, together with James H. Simons of Renaissance Technologies, David was ranked among the top 25 earners in the hedge fund industry by Institutional Investor’s Alpha.
David has donated more than $2.25 million to priorities USA Action — a super PAC that supported Democratic presidential candidate Hilary Clinton and $1 million to Organizing for Action. David and his wife, through the Shaw Family Endowment Fund, donated $400k to the Stephen Wise Free Synagogue, $400k to Memorial Sloan Kettering Cancer Centre, and $800k to the Horace Mann School — all in 2014. Also, the fund had donated $1 million annually to Yale University, Harvard University, Stanford University, Princeton University, and $500k to Brown University and Columbia University. The College donations represent about 60% of the total fund’s philanthropy.
He is married to Beth Kobliner, a personal finance commentator and journalist. David and Beth are both members of the Stephen Wise Free Synagogue in NYC. They have three children and live in NYC.
D.E. Shaw wants quant traders
The hedge fund is famous for hiring people on their abilities and capabilities, not on their experience. Perhaps their most famous “signing” was Jeff Bezos:
Jeff Bezos, the founder of Amazon, was hired by D.E. Shaw because of his intellect and presumed capabilities, even though they didn’t really have a vacant position for him at the time. Bezos later resigned to start Amazon, but his last assignment in D.E. Shaw was to formulate ideas for various technology-related new ventures. One of them was a universal electronic bookstore!
D.E. Shaw’s trading strategies
How has D.E. Shaw managed to extract consistent profits from the market for over a decade in both bullish and bearish periods? Just like Jim Rogers, David Shaw is extremely secretive about their trading strategies. However, it’s possible doing a little reading between the lines to sketch some rough ideas about what the firm is doing.
According to Jack Schwager, who did some guesswork, D.E. Shaw probably does (or did) mainly strategies like these:
- Classical arbitrage: buy gold in New York, sell in London when prices differ.
- Statistical arbitrage: This is locking in profits when two closely related financial instruments differ. This could be, for example, Ford and General Motors. Pairs trading could be called statistical arbitrage. This is not guaranteed profits, but probable profits.
Jack Schwager goes on to describe many types of statistical trading, which we are not going into detail here. However, at the time of the interview, D.E. Shaw made most of their money in equities and less in other asset classes.
Quotes from David Shaw:
Below we have taken some excerpts from Jack Schwager’s interview in the Stock Market Wizards book:
I grew up with the idea that, if not impossible, it was certainly extremely difficult to beat the market.
But the inability to precisely explicate the hypothesis being tested is one of the signposts of a pseudoscience (on technical analysis).
The problem, of course, is that as soon as these anomalies are published, they tend to disappear because people exploit them.
In our business, it’s as important to know what doesn’t work as what does.
There’s a tendency for academics to be more open about their results than practitioners.
The vast majority of the research that really does work will probably never be published.
The game is largely over for most of the “easy” effects.
We look at balance sheets, income statements, volume information, and almost any other sort of data we can get our hands on in digital form.
In general, I try not to say much about historical inefficiencies that have disappeared from the markets, since even that type of information could help competitors decide how to more effectively allocate scarce research resources, allowing them a free ride on our own negative findings, which would give them an unfair competitive advantage.
The more variables you have, the greater the number of statistical artifacts that you’re likely to find, and the more difficult it will generally be to tell whether a pattern you uncover actually has any predictive value.
…one of our most powerful tools is the straightforward application of the scientific method.
…we typically start by formulating a hypothesis based on some sort of structural theory or qualitative understanding of the market, and then test that hypothesis to see whether it is supported by the data.
Once in a while, though, we do find a new market anomaly that passes all our tests, and which we wind up incorporating into an actual trading strategy.