Hedge funds have been giving vast sums to academia this last year. In February Ken Griffin, founder of Chicagobased hedge fund firm Citadel, donated $150 million to Harvard College, the biggest single gift to the college ever. Michael Hintze, head of Londonheadquartered hedge fund firm CQS, donated £1.5 million ($2.5 million) to Oxford University, to help search the universe for invisible dark matter and dark energy. These followed Jerseybased hedge fund firm Brevan Howards £20.1 million donation to Imperial College Business School last year and the £4.5m to Oxford Universitys Saïd Business School from Bill Ackman, the activist investor CEO of New York hedge fund firm Pershing Square Capital Management.
University coffers seem to be awash with hedge fund money. But more recently there has been a new trend to harness academic research with investment returns.
In February Capital Fund Management (CFM), one of Frances largest hedge fund firms, which manages $4.5 billion, announced a formal partnership with Imperial College London to create the CFM-Imperial Institute of Quantitative Finance, which will explore new directions in the modeling of risks in financial markets. To promote academic inquiry into finance, CFM is funding a postdoctoral fellowship, stipends for doctorate-level students and a program for visiting international scholars, as well as a series of seminars and conferences.
The project is a solid fit for CFM, the company of which physicist Jean-Philippe Bouchaud is chair, a leading figure among quantitative hedge fund firms. Finance is as important for humans as nuclear science and pharmaceutical research, says Bouchaud. Academia and finance are two separate things. But the gap is getting narrower; this tie-up is proof of that. Its time to stop warring and get the best of both insights.
As well as overseeing CFM, Bouchaud teaches physics at the Ecole Polytechnique in Paris and has published several books and more than 250 scientific papers on physics and finance. He is also a well-known proponent of econophysics, the study of economics using statistical theories and methods developed by physicists. The firms teaching connections have helped CFM to bring 40 scientists on staff out of its 140 employees, many of whom have come from the ranks of higher education.
The urge to marry finance and academia is nothing new. Economics has leaned on physics for a variety of model equations, such as for earthquake prediction and chaos theory. Even the Black-Scholes-Merton option pricing formula,which won Myron Scholes and Robert Merton the 1997 Nobel Memorial Prize in Economic Sciences, shares its derivation with the heat equation in physics. (The formula was first published in a 1973 paper and was co-created by Fischer Black, who died in 1995 and was thus ineligible for the Nobel.)
But the formalization of recent partnership suggests a direct route to harnessing science for investment. CFMs initiative is the latest tie-up of hedge fund firm and science. Man Group, the worlds largest publicly traded hedge fund, pledged £13.75 million ($27.5 million using 2007 rates) in 2007 to sponsor the Oxford-Man Institute (OMI) of Quantitative Finance for a five-year period. Last year Man Group extended this partnership until 2018. East Setauket, New Yorkbased hedge fund firm Renaissance Technologies is known for specifically seeking out job candidates with science backgrounds for its quantitative research positions. Longtime quant James Simons, who founded the firm in 1982, has donated hundreds of millions of dollars to institutions of higher learning and research, including $60 million to the namesake Simons Institute for the Theory of Computing at the University of California, Berkeley, and those on his resident Long Island, including $13 million to the Brookhaven National Laboratory and $85 million to the State University of New York at Stony Brook, where he is chair emeritus of the board of trustees.
For Man Group, the OMI is a way to access and incubate top talent as well as to procure relevant research.
We have a constant need across Man for high-quality people, so having a road into one of the top universities is very helpful, says Tim Wong, executive chair of Mans AHL fund, which relies on computer algorithms to spot profitable trends. You have the chance to get to know the candidates on a much deeper level before you hire them. You can see how they work, and they have the chance to see how we work too. It also gives us links into Oxfords large network across the world.
The application of theoretical physics to what at times can appear to be the gravity-defying properties of money is one thing. But where does theory end and practice begin? A brilliant quantitative mind is not necessarily an alpha generator. Last year hedge fund manager George Soros argued that economics had tried to be a hard science like physics but ignored that society and the thinking of human beings entered into the course of events, introducing unpredictability into the equation.
Mans AHL fund has suffered three straight years of losses: not exactly the shining display of science working for investors. There have, of course, been performance challenges in the trend-following space more broadly, but the industry is rapidly evolving and diversifying, says Wong. OMI plays a key role in this commitment.
As evidenced by the failure of models to deal with the financial crisis, banks have had a rough go of incorporating quant models in their strategies but havent always had the patience to see them through. Twenty years ago, we were stunned by seeing that banks considered a week to be long-term research, says Bouchaud. You have no time to research in a week you wont get answers. Innovation needs long-term research.
Even Isaac Newton lost a bundle investing in the speculative South Sea bubble in the 18th century, explaining later, I can calculate the movement of stars, but not the madness of men. Berkshire Hathaway chair and CEO Warren Buffett quipped in his 2005 letter to shareholders that if Newton had not been traumatized by this loss, Sir Isaac might well have gone on to discover the Fourth Law of Motion: For investors as a whole, returns decrease as motion increases.
A school of thought holds that far from being physical systems, markets are based on informational asymmetry and become difficult to model because there is always something looking to disrupt order to gain an informational advantage that is, the traders edge. In a 2010 paper titled Warning: Physics Envy May Be Hazardous to Your Wealth!, Massachusetts Institute of Technology academics Andrew Lo and Mark Mueller put it succinctly, Attempts to understand uncertainty are mere illusions; there is only suffering.
Bouchaud insists that mathematical models are not the only factor in trading success. He has criticized the Efficient Market Hypothesis, the proponent of which, University of Chicago economist Eugene Fama, and avowed critic, Yale University economist Robert Shiller, jointly won the 2013 Nobel Memorial Prize in Economic Sciences (Chicago economist Lars Peter Hansen also shared the prize). Bouchaud is also not a fan of the BlackScholes-Merton model, which he believes leads to a systematic underestimation of risk in options trading.
We are doing a little bit of the math that is needed. But most of the time you dont need math, he says. You need intuition and an understanding of what the numbers mean and how to pull them together. There is a huge difference between understanding something on an academic level and looking at implementing it.
So to where does this all lead? Could we really see the next generation of hedge fund firms being staffed by wonks in ironic T-shirts splashed with mathematically themed puns? Despite the riches on offer, the marriage between science and hedge funds isnt necessarily one from the fairy tales.
The sentiment among many academics is that finance has kidnapped scientists away from their ivory towers. In a study for the Bank for International Settlements published in 2012, BIS economists Stephen Cecchetti and Enisse Kharroubi argue that the lure of riches during times of plenty literally bids rocket scientists away from the satellite industry. The result is that erstwhile scientists, people who in another age dreamt of curing cancer or flying to Mars, today dream of becoming hedge fund managers.
Others disagree, stating that the best in science will generally stay in academia and not jump ship to finance. James Owen Weatherall, assistant professor of logic and philosophy of science at the University of California, Irvine, argues in his book The Physics of Wall Street, published in February, that mathematical models are the remedy, not the ailment. One of the cases in point in his book is Simonss Renaissance Technologies.
The vast majority of research scientists have gone into their fields because they want to do research. They have made great sacrifices, both personal and financial, to be successful in academia, Weatherall says in an interview. The Ph.D.s who move to finance tend to be the ones who decide that a good salary on Wall Street, or elsewhere in industry, is better than a progression of postdocs and no job security, or a teaching position with no research support.
Bouchaud himself is quick to state that financial firms should look for scientists whose hearts are more into quantitative modeling than their wallets. If you want to attract people and avoid moral hazard, you need to have people who are not solely into the money, he says. You need to have the intellectual challenge with it. He believes that his own companys tie-up will encourage development through exploration and research, which, as he sees it, is the way finance should be. The idea is to avoid being too prescriptive. You should let surprises arrive.
Bouchauds words suggest the science and hedge fund relationship is a mutually beneficial one. But what happens when the influence over scientific research turns into interference? Hedge funds are money-making machines. One could assume the longer science languishes, the more scientists will look to finance to capture money. The boundaries between finance and science are ever more co-dependent.