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Sunday, November 20, 2005

Simons, Thorp and Shannon

Nice article on Jim Simons and Renaissance in Saturday's Times. Part of me wants to get into the new fund (fees are pretty reasonable compared to Medallion), but then again they are embarking on something new, so it's no sure thing. See earlier posts here and here. Most impressive about Medallion is their consistency -- no down years since 1988 and only a single down month in the last 5 years!

BTW, I've received my copy of Fortune's Formula and it's quite good. I learned a number of tidbits about Thorp (the mathematician who wrote Beat the Dealer and invented a system for counting cards in blackjack), Shannon (the father of information theory) and others from this book. Apparently, Thorp and Shannon's investment returns (Thorp ran an early hedge fund called Princeton-Newport, while Shannon invested his own account) rivalled those of the best managers like Buffet and Soros. Buffet and Thorp actually knew each other early on, and had very high opinions of each other. The stories of Thorp testing his card counting system in Nevada are hilarious -- the level of detail after all these years suggests a phenomenal memory!

The bit about optimizing geometric vs arithmetic returns (a subject of controversy between math/physics guys like Kelly, Shannon, Thorp and economists such as Samuelson, and the origin of the title of the book) seems not so interesting to me, as the answer depends on what one wants to achieve. On the subject of hedge funds, it appears everyone is starting one, including information theorist Thomas Cover and former physicist turned AI researcher Eric Baum (author of What is Thought?, the best book I've read on AI).

NYTimes: $100 Billion in the Hands of a Computer

By JOSEPH NOCERA
PEOPLE ask me all the time: What's your secret?" James Simons said. We were sitting in an office in Manhattan that Mr. Simons uses when he's not at the Long Island offices of Renaissance Technologies, the money management firm he founded in 1982. He was wearing an elegant shirt and tie, and loafers with no socks. He took a drag from a cigarette, the second of three he would smoke in the course of a long interview.

I had indeed come to ask him what his secret was. In the hedge fund world, that's what everybody wants to know.

Mr. Simons, 67, who rarely talks to journalists, is hardly a household name like Warren E. Buffett. But Mr. Simons, who got into the hedge fund business after abandoning a stellar career in mathematics, has a track record that is jaw-dropping. This summer, word leaked out that he was starting a new fund - people took to calling it the "$100 billion fund" because its marketing materials say that it could conceivably grow to that enormous size. Not surprisingly, that has caused Wall Street types to be even more curious about him.

Here are Mr. Simons's numbers: from 1990 to 2004, Renaissance's primary hedge fund, called Medallion, has delivered annualized returns of 33.21 percent. (The Standard & Poor's 500-stock index has returned, on average, 10.98 percent during those same years.) Since the end of 2002, the fund, which has $5 billion under management, has disbursed $4.9 billion to its investors - with another $1.5 billion to be delivered at the end of this year.

And these returns are after Medallion's 5 percent management fee and 44 percent share of the profits - surely the highest hedge fund fees in the land. Medallion's returns, and its fees, have helped make Mr. Simons a very wealthy man, with a net worth that Forbes estimates at $2.7 billion.

When I showed Mr. Simons's returns to a hedge fund friend, he looked startled. "Nobody has numbers like those," he said. But here's the real eye-opener: no one outside the firm's 200 or so employees has a clue how he does it.

Medallion, you see, is a quantitative fund. In quant funds, trading activity is generated by complex computer models rather than human judgment. Most quants are secretive about the algorithms that drive their models; after all, that's their investing edge. But of the handful of big-time "black box" investors, as they're often called, Mr. Simons's box may well be the blackest.

HERE'S what we do know. Medallion's portfolio contains literally thousands of stocks and other financial instruments that it trades in rapid-fire fashion. The firm's scientists are constantly searching for repeatable patterns, and other signals, in the enormous amounts of data they compile. The computer models they devise tell them when to make trades based on those signals.

As Mr. Simons put it - and this is about as specific as he would get - "Certain price patterns are nonrandom and will lead to a predictive effect." He also told me that Medallion sticks with highly liquid securities that trade in public markets around the world. Why? "Because there is a lot of data on such instruments, and we're very statistically oriented," he said. He stays away from exotic derivatives.

Not even Mr. Simons's investors know much more than I've just described. "We trust Jim and we think he's smart," said one longtime Medallion investor. "So we stopped caring what the computer was doing." When this investor began describing Mr. Simons's investing approach, he admitted he was guessing.

Mr. Simons shrugged when I suggested to him that his firm's lack of "transparency," as they say in the business, was bound to make people nervous. Humans fail in the market all the time, but somehow we are willing to keep giving our money to human beings to manage because we understand investing based on human judgment. Or at least we think we do. But black box investing feels different. It feels scary somehow, precisely because it is not something most of us can understand.

"How any great investor does it isn't in the least obvious," Mr. Simons responded. "How we do it isn't any more mysterious than how a great fundamental investor does it. In some ways it is less mysterious because what we do can be programmed." Then he stopped, took another drag from his cigarette, and let out a small chuckle. "Well," he conceded, "it's less mysterious to us."

Mr. Simons wasn't always a quant. A former crypt analyst - a code breaker, that is - he did important work in mathematics that helped lay the foundation for string theory. When he began managing money in the 1970's, he did it the same way most investors did: he used his own judgment. "At first," he said, "I didn't think about investing in a scientific fashion. But I was trading currencies, and it gradually occurred to me that there might be some way to create models that would allow you to predict currency movements."

Although Mr. Simons and a partner made an absolute killing in the currency markets the old-fashioned way - they made huge bets that turned out to be right - he began surrounding himself with scientists who developed models for all sorts of tradeable securities. "By the end of the 1980's," he said, "I was a model man, and didn't want to do fundamental analysis." One advantage, he said, is that "models can lower your risk." Another, though, is that "it reduces the daily aggravation." With old-fashioned stock picking, he said: "One day you feel like a hero. The next day you feel like a goat. Either way, most of the time it's just luck."

Indeed, trading the way he does, making thousands of small trades aimed at capturing small price movements, doesn't generate the kind of "10 bagger" that investors love. But when done well, quant investing is less likely to have the kind of disaster that is always the danger when one bets big on a stock.

To those who point to Long-Term Capital Management as an example of the dangers of black box investing, Mr. Simons's defenders point out that his fund has far less leverage than Long-Term Capital, and that in any case, while Long-Term Capital had several Nobel laureates on board, human bets were what caused it to go awry.

Clifford Asness, another well-known quant hedge fund manager, said that while he knew no more about Mr. Simons's methods than anyone else, "It's hard to believe that there isn't a measure of safety in Jim's approach.

"Presumably, he's got a highly diversified portfolio, high turnover, and he's capturing small inefficiencies. It's hard to lose a ton of money doing that. It is always possible that someday his models might stop working. But that's different from 'blowing up.' "

"You know," Mr. Asness added, "human beings have a black box, too. It's called the brain."
As for the new "$100 billion fund," Mr. Simons was even more constrained than usual, thanks to regulatory restrictions that limit what he can say publicly while the fund is raising money. People are buzzing about it nonetheless, for it seems to be a major departure from Medallion. Medallion's investors were almost all wealthy individuals; the new fund, called the Renaissance Institutional Equities Fund, has a $20 million minimum investment and is aimed at institutions. It has a much lower fee structure. It will invest in - or sell short - only publicly traded equities. Instead of making rapid-fire trades, it will be much closer to a buy-and-hold portfolio. And so on.

In one critical way, though, it is similar to Medallion. As the marketing document, which I obtained from a person unconnected to Mr. Simons, put it: "The company's risk control, variance and covariance estimation, execution techniques, slippage models, and predictive signals are all derived from those employed by the managing member in trading the Medallion Funds."

In other words, Mr. Simons believes that computer models similar to those that have worked for Medallion will also work for a fund that can hold $100 billion worth of stocks over long periods of time. It is absolutely audacious.

What interested me most of all was: why? At an age when most men are contemplating retirement, with more money than he can count, why was Mr. Simons still at it? "I enjoy the challenge," he replied.

He then began describing a demonstration he saw recently of a new nuclear accelerator at the Brookhaven National Laboratory, where he is on the board. Two atoms hurtled toward each other, colliding with great force. "A huge number of particles are thrown out," he said, "and the job is to analyze everything that results from the collision."

"Watching the spray of particles on the screen made me think of the stock market," he continued. Every trade, even of a hundred shares of a company, affects every other trade. And every day there are thousands upon thousands of such trades, all of them affecting the rest of the market. His work, as he sees it, is to analyze that incredibly complex mosaic and try to figure out how it all fits together.

"The subject may not be the most important in the world," he concluded, "but the dynamics of the market are really interesting. It's a serious question."

I suddenly understood the motivation behind Mr. Simons's new fund. He's doing it because he wants to see if it can be done. Once a scientist, always a scientist.

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