• Renaissance hired mathematicians and computer scientists, not economists, another factor that distinguished it from LTCM.
  • —Gregory Zuckerman, The Man Who Solved the Market,1 page 212
Gregory Zuckerman’s book tells the story of the investment business headed by James Simons. The business was restructured many times, but the most durable component was Renaissance Technologies Corporation.

Zuckerman’s theme is that by using highly advanced computerized pattern recognition, Renaissance was able to achieve returns that far exceeded those attained by firms that employed more traditional approaches. The firm is very protective of its trading secrets, but Zuckerman was able to put together a satisfactory description of the general principles to which Renaissance subscribed.

Much of the book consists of tales of the gifted mathematicians who ran the firm, along with their foibles and conflicts. These are entertaining enough, but I want to focus instead on two deeper economic issues that arise from the story.

1) Does the success of Renaissance show that financial markets are inefficient?

2) Are the social benefits of the trading conducted by firms like Renaissance commensurate with the profits that they earned?

Zuckerman apparently believes that the answer to the first question is “yes.” He does not directly answer the second question, but his description of the significant involvement of Renaissance executive Robert Mercer in the Presidential campaign of Donald Trump seems likely to influence many readers to take a negative view. (Simons and other Renaissance executives contributed heavily to Democrats.)

Efficient Markets Hypothesis (EMH)

In their article for the Concise Encyclopedia of Economics,2 Steven L. Jones and Jeffry M. Netter write,

  • In a weak-form efficient market, future returns cannot be predicted from past returns or any other market-based indicator, such as trading volume or the ratio of puts (options to sell stocks) to calls (options to buy stocks). In a semistrong efficient market, prices reflect all publicly available information about economic fundamentals, including the public market data (in weak form), as well as the content of financial reports, economic forecasts, company announcements, and so on… In strong form, the highest level of market efficiency, prices reflect all public and private information.
  • A simple way to distinguish among the three forms of market efficiency is to recognize that weak form precludes only technical analysis from being profitable, while semi-strong form precludes the profitability of both technical and fundamental analysis, and strong form implies that even those with privileged information cannot expect to earn excess returns.

Zuckerman points out that the pattern-based trading strategies that Renaissance employed were a highly refined form of technical analysis. The firm built extensive databases of past price movements in commodity markets, bond markets, foreign exchange markets, and stock markets. It then had computers search for patterns of price changes that predicted profitable trading opportunities that seemed to recur on a reliable basis. Using these patterns, which seemed to show opportunities for very short-term trades as opposed to buying and holding a security, the firm proceeded over a span of more than two decades to earn returns that often exceeded 50 percent per year on portfolios that grew to billions of dollars.

Not every individual trade produced a profit. In fact, some of the statisticians described the results as making bets that worked between 50 percent and 51 percent of the time (after allowing for transaction costs). Doing a tremendous volume of such trades resulted in high net returns.

For background definitions, see Capital Gains Taxes, by Stephen Moore, in the Concise Encyclopedia of Economics.

Also, the firm may have used an instrument known as “basket options” in its Medallion Fund for advantageous tax treatment. These enabled Medallion’s trades to become eligible for the more favorable long-term capital gains tax, even though many of them lasted just a few days or even hours. That’s because the options were exercised after a year, allowing Renaissance to argue that they were long-term in nature. (Short-term capital gains are taxes at a rate of 39.5 percent while long-term gains face a 20 percent tax.)

  • Several years later, the Internal Revenue Service would rule that Medallion had improperly claimed profits from the basket options as long-term capital gains. Simons, who had approved the transactions, along with other Renaissance executives, paid a whopping $6.8 billion less in taxes than they should have, the IRS said… Renaissance challenged the IRS’s finding and the dispute was still ongoing as of the summer of 2019. (page 226)

The success that Renaissance enjoyed in trading based on these historical patterns appears to disprove even the weak form of the EMH. The weak form says that there should be no way to exploit past information in a way to make reliable excess returns, yet Renaissance seems to have done exactly that.

But economists inclined to believe the EMH have a counter-argument when someone points to the success of one particular individual or investment firm. Consider the hypothetical case of a coin-flipping tournament. We start out with thousands of flippers. Everyone flips a coin the first round, and those who flip heads get to proceed to the second round. Of these, those who flip heads on the second round get to proceed to the third round, and so on. Finally, after, say, ten rounds, we declare those who have not dropped out the winners. The existence of such lucky flippers does not disprove the hypothesis that each coin flip has a fifty percent chance of landing on heads.

In the world of financial investments, one can think of a fund that beats the market in a given year as like a coin flipper who turned up heads in one round. With thousands of speculators playing the game, it is likely that over the course of 10 or 15 years, one of them will turn out to have beaten the market every year. But that does not disprove the EMH.

A natural human inclination is to attribute the success of winning speculators to skill rather than luck. But consider some examples of past winners and their more recent performance. Zuckerman himself points out that once-fabled investors appear to have lost their touch.

For more background on the Financial Crisis of 2008, see The 2008 Financial Crisis, by Arnold Kling in the Concise Encyclopedia of Economics.

For an organized list of discussions about the 2008 Financial Crisis and Great Recession, see also Financial Crisis of 2008, an Econlib College Topics Guide.

See also “Thank Heaven for an Inefficient Market: A Tale of Zombies and Speculators”, by Anthony de Jasay, Library of Economics and Liberty, September 7, 2009.

In the years leading up to 2019, John Paulson, who made billions predicting the 2007 subprime credit crisis, suffered deep losses and lasting client defections. David Einhorn, a poker-playing hedge-fund manager once known as “King David” for anticipating Lehman Brothers’ 2008 collapse, saw his own clients bolt amid poor performance. [Paulson and Einhorn’s earlier successes are chronicled in another book by Zuckerman, The Greatest Trade Ever.3]

In Newport Beach, California, Bill Gross, an investor known to chafe when employees at bond powerhouse PIMCO spoke or even made eye contact with him, saw his returns slip ahead of his shocking departure from the firm. Even Warren Buffet’s performance waned. His Berkshire Hathaway trailed the S&P 500 over the previous five, ten, and fifteen years leading up to May 2019. (p. 309)

Zuckerman sees these examples as illustrating that investment strategies based on analysis of fundamental values of securities were no longer as profitable as doing pattern searches. Economists inclined to believe the EMH would say that these examples may instead illustrate that the winners of a recent coin-flipping tournament are likely to be only average performers in the next one.

Suppose that in the coming years Renaissance produces mediocre returns. Journalists will say that their computerized trading methods degraded in some way. But adherents of the EMH would say that the years of high returns were luck that was bound to run out.

Even if there are profit opportunities that a firm like Renaissance can reliably exploit, it still might be possible that markets are mostly efficient. That is, although security prices might deviate from their theoretically correct values regularly enough for one firm to make systematic profits, as long as the deviations are small enough and transitory enough, we would say that the markets are doing their job sufficiently well. (I thank Alan Marcus of Boston College for making this point.)

Social Benefits of Speculation

“The economic argument for speculation is that it facilitates price discovery in financial markets, which in turn improves the allocation of resources.”

The economic argument for speculation is that it facilitates price discovery in financial markets, which in turn improves the allocation of resources. For example, suppose that commodity speculators, anticipating conditions in supply and demand at the time of the next wheat harvest, buy wheat futures contracts. This drives up the price of wheat, which in turn tells some soybean farmers to switch to planting wheat and tells some large bakeries to shift toward using other grains where possible. If the speculators have assessed the market correctly, then when the harvest comes in, wheat prices will indeed turn out to be high, the speculators will earn profits, and the adjustments made by farmers and bakers will prove correct. It is a story in which the lure of speculative profit plays a constructive role, by giving an incentive to speculators to make the effort to forecast future market conditions, leading to better price signals and resource allocation.

But Renaissance technologies pays no attention at all to fundamental conditions of supply and demand. Instead, it looks for patterns in past price behavior. Moreover, it only holds its positions for a few days or less, which is not enough time to send a durable price signal. So how does its speculation help the economy? Zuckerman writes, “Most employees concluded that their heavy trading was adding to the market’s liquidity, or the ability of investors to get in and out of positions easily, helping the financial system… ” (page 229).

Short-term traders, like Renaissance, may be helpful to long-term investors. When you put savings into a stock index fund, the managers of that fund need to buy stocks. If they cannot do so without paying a large premium over the current prices for those stocks, then your returns will be undermined. What you want instead is for the mutual fund to find that the market is liquid, meaning that it can make new purchases without having to pay premium prices.

Short-term traders like Renaissance may be the suppliers of liquidity in this instance. If they spot a temporary rise in share prices as the mutual fund makes its purchases, the short-term traders may sell, expecting to profit as soon as the short-term blip gets reversed. When many traders compete for these profits, market liquidity improves and the mutual fund is able to make its purchases with little or no effect on the prices it pays.

To take another example, suppose that I am a long-term speculator who sees a high price ahead for wheat, and I want to buy futures contracts, holding them until the price goes to where I think it is headed. If the wheat futures market were not liquid, meaning that there is not much trading in the market, then before my order for futures contracts can be satisfied, the price will shoot up, taking away my profit opportunity. But short-term traders like Renaissance may interpret a price rise as a selling opportunity, because the price has gotten out of line relative to past patterns. As the price of wheat futures starts to climb, these short-term traders will sell, helping to cushion the price rise. That enables me as a long-term speculator to place my bet profitably.

Long-term investors, such as index funds, and long-term speculators who take positions based on their outlook for securities, are the demand side for liquidity. Short-term traders, who try to identify and profit from transitory over- or under-pricing of securities, are the supply side for liquidity.

Regardless of whether your investment strategy puts you on the demand side or the supply side for liquidity, it pays tactically to engage in disguise and deception. As in poker, players want to avoid giving away “tells” that make their own moves transparent and predictable, while avoiding traps set by other players’ deceptions. In the stock market, for example, a firm might try to disguise its desire to increase its holdings of a stock by spreading out its purchases over several days. One may think of the sort of pattern analysis undertaken by Renaissance as aimed at uncovering subtle tells and recognizing traps.

But if long-term speculators are betting that today’s price is too low relative to future market conditions, and short-term traders are betting that today’s price is too high because of transitory market conditions today, how can they both make profits?

Economists suspect that speculators and traders collectively make profits from their trades with other market participants, who in turn obtain profits in different ways. For those of us who buy stock mutual funds, profit comes from sharing in the growth of businesses in the economy at large. For farmers and bakers, profit comes from selling what they produce for more than the cost of production. But, on average, we give up something to the speculators and traders, just as people who go to Las Vegas end up giving up something to the “house” on average.

A case can be made that short-term traders are playing a zero-sum game among themselves. What one short-term trader gains, some other trader loses. Perhaps if the overall “house take” earned by the suppliers of market liquidity was $X in any given year, Renaissance earned an outsized fraction of X, while other short-term traders earned proportionately less or even took losses.

In fact, short-term trading might be a negative-sum game. As an individual, you might win in short-term trading by investing in more powerful computers and faster communications technology, but that does not increase the size of the pie. For the economy as a whole, the cost of these investments might just be deadweight loss, not unlike the deadweight loss that comes from rent-seeking.

Many financial transactions represent attempts at tax avoidance and/or evasion of regulations. Assuming that the taxes or regulations are not misguided to begin with, it is hard to see how profits from evasion are socially beneficial.

Suppose that other firms, unlike Renaissance, did not use basket options to avoid taxes, either because they did not spot the opportunity or because they doubted its legality. This would put them at a disadvantage, because trades that were profitable on an after-tax basis for Renaissance would not have been profitable for its competitors.

It is not immediately obvious whether the overall resources devoted to providing market liquidity are excessive, insufficient, or about right. Economist Eric Budish and others suspect that there is over-investment in the short-term trading business. Suppose that we could somehow set up an exchange where the market is highly liquid exactly once a day, but not liquid at all at other times. The market participants who need price signals (the farmers and the bakers) probably could make good decisions even if they only got accurate signals once a day, or even less frequently. The mutual-fund investors who also are on the demand side of the market for liquidity can get by with daily trading. The suppliers of liquidity might be spared the effort and expense of trying to gain every split-second’s edge on their competitors.

In fact, Budish and his co-authors have argued that any system of discrete trading times—they suggest once per second rather than once per day—would potentially reduce deadweight loss in short-term trading, thereby improving the supply side of liquidity. They suggest that the fact that we do not observe exchanges that work with only discrete trading times does not necessarily show that it would not be more economical to do so.4

In conclusion, I am afraid that it is difficult to draw reliable inferences from the spectacular success of James Simons and his investment business. Perhaps his firm “solved the market” as Zuckerman claims, or perhaps it only experienced an unusual streak of luck. Perhaps the returns that the firm earned on its investment in high-powered computers and mathematicians reflected the social benefits of its role in supplying market liquidity, or perhaps the economy over-invests in liquidity provision as the result of a negative-sum game in which short-term traders reach for advantage relative to one another.


[1] Gregory Zuckerman, The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution, Portfolio, 2019. Note that LTCM is Long Term Capital Management, a hedge fund that was famous for its highly-reputed economists and infamous for the way that it collapsed in 1998, resulting in a bailout arranged by the Greenspan-era Federal Reserve.

[2] Efficient Capital Markets, by Steven L. Jones and Jeffry M. Netter. The Concise Encyclopedia of Economics.

[3] Gregory Zuckerman, The Greatest Trade Ever: The Behind-the-Scenes Story of How John Paulson Defied Wall Street and Made Financial History. Crown Business, 2010.

[4] See Eric Budish, Peter Crampton, and John Shim, “The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response,” Quarterly Journal of Economics, Nov. 2015; and Eric Budish, Robin S. Lee and John J. Shim, “Will the Market Fix the Market? A Theory of Stock Exchange Competition and Innovation”, working paper, May 6, 2019. I would like to thank Robert McDonald of Northwestern University for recommending these papers.

*Arnold Kling has a Ph.D. in economics from the Massachusetts Institute of Technology. He is the author of several books, including Crisis of Abundance: Rethinking How We Pay for Health Care; Invisible Wealth: The Hidden Story of How Markets Work; Unchecked and Unbalanced: How the Discrepancy Between Knowledge and Power Caused the Financial Crisis and Threatens Democracy; and Specialization and Trade: A Re-introduction to Economics. He contributed to EconLog from January 2003 through August 2012.

Read more of what Arnold Kling’s been reading. For more book reviews and articles by Arnold Kling, see the Archive.

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