On Jim Simons, String Theory, and Quantitative Hedge Funds

Renaissance Technologies founder and mathematics professor Jim Simons is an enigma in quantitative hedge funds.

 

Simons rarely gives interviews. One of the best is an Institutional Investor interview he gave in 2000 (PDF). One insight is that Renaissance makes trades in specific time periods using pattern recognition to model volatility.

 

Simons has done important work in differential geometry and the theoretical physics subdiscipline of string theory. I recently looked at some academic journal articles by Lars Brink (Sweden’s Chalmers University of Technology) and Leonard Susskind (Stanford University) to try and understand how Simons views financial markets.

 

String theory proposes one-dimensional objects called strings as particle-like objects that have quantum states. String theory and cosmology has progressed over the past 35 years to describe this phenomena but still lacks some key insights.

 

How might Simons use string theory to understand financial markets? Two possibilities:

 

(1) The mathematical language of couplings, phase transitions, perturbations, rotational states, and supersymmetries provides a scientific way to describe financial market  data and price time-series. It does so in a different way to fundamental analysis, technical analysis, and behavioural finance: Simons uses string theory to understand the structure of information in financial markets. (Ed Thorp pursued a similar insight with Claude Shannon using probability theory.) String theory-oriented trading may be falsifiable in Karl Popper’s philosophy of science.

 

(2) String theory provides a topological model that can be applied to money flows between mutual funds, hedge funds, and bank trading desks over short periods of time. This might enable Simons’ traders to forecast the likely catalysts for changes in stock prices in the short-term and to trade accordingly. This might involve using string theory to forecast how price trajectories might change if portfolio managers at other funds alter their portfolio weights for a stock. In doing so, Simons is trading in a similar way to SAC’s Steve Cohen (who uses game theory) and D.E. Shaw’s David Shaw but uses different methods of pattern recognition to do so.

 

I have made a list of popular science books and Springer academic monographs to keep an eye on string theory. Simons’ success also illustrates how insights from one knowledge domain (string theory, astrophysics, computational linguistics, and voice recognition) can be transferred to another domain (financial markets trading).

Dissecting Steve A. Cohen’s Edge

One of my discarded PhD chapter outlines was on the hedge fund SAC Capital and the insider trading case involving former SAC trader Matthew J. Martoma and the firms Elan and Wyeth. I had hypothesised that SAC founder Steve A. Cohen had developed a specific organisational strategic subculture. Recently, I read and analysed Cohen’s legal defence. Now, The New Yorker‘s Patrick Radden Keefe has written a lengthy article on SAC, Cohen, Martoma, and the insider case’s legal outcomes. I reflected on how Cohen developed his edge:

 

1. Cohen had ignition experiences early on in his career. Keefe and the PBS Frontline ‘To Catch A Trader‘ point to Cohen’s formative trading experiences with the investment bank Gruntal & Company as a likely first encounter with insider trading. Possibly more important to Cohen’s creative psychobiography are his early experiences in learning to perceive fluctuations in stockmarket prices, as told to Jack Schwager. This tape-reading ability has been part of trading education since Jesse Livermore and is echoed in the Market Wizards series interviews that Jack Schwager did with Michael Marcus and Paul Tudor Jones II. Cohen’s early experiences also parallel the role of ignition experiences in the literature on genius and creativity. They also meant that Cohen did not adopt the dominant approaches of fundamental and technical analysis. Instead, he anticipated behavioural finance in looking for catalysts that moved stocks and that led to rational herding and overconfidence behaviours he could trade against.

 

2. Cohen hired a performance psychologist. Keefe mentions but does not name the late Ari Kiev as the performance psychologist who Cohen hired to mentor his traders. Kiev’s books notably The Mental Strategies of Top Traders (Hoboken, NJ: John Wiley & Sons, 2009) draw on his SAC experiences and detail his personal synthesis of elite sports training, game theory, portfolio management, and leadership frameworks. Kiev foreshadowed other performance psychologists such as Brett N. Steenbarger who have worked with hedge funds. In doing so, Kiev and Steenbarger became de facto strategic foresight practitioners, albeit with a different knowledge base to futures studies.

 

3. Cohen created a specific organisational strategic culture. Keefe and PBS Frontline‘s narratives focus on SAC’s competitive culture between rival portfolio managers; the inside discussion of “black edge” as material non-public information; how Cohen ran his trading floor; and how Cohen got the best trading ideas from portfolio managers whilst also insulating himself from their information sources. There are observations here worthy of the third generation literature on strategic culture, and how specific organisations have developed ways to hedge risk and volatility. If Keefe had been familiar with the sociology of finance literature then he might have focused on this more. Now that SAC has transformed into Point 72 Asset Management – to manage Cohen’s estimated $9 billion wealth – we may never really know what went on inside SAC, unless there is further operational disclosure in civil cases, or in trader memoirs.

 

4. Cohen was pro anti-fragile. Keefe tells an anecdote about how Cohen would ask job applicants: “Tell me some of the riskiest things you’ve ever done in your life.” Keefe segues from this into an anecdote about insider trader Richard Lee. But there are several other possible ways to interpret Cohen’s question and why he would pose it to SAC job applicants. Cohen may have wanted to assess how the job applicant conceptualised risk; how they made decisions; and what specific decisions they made when faced by risk. As Kiev identified these are crucial aspects to successful trading. The anecdote also suggests to me that Cohen was pro anti-fragile: options trader and philosopher Nassim Nicholas Taleb’s term for phenomena that become stronger due to volatility exposure. Being pro anti-fragile – and taking considered risks – was in part how Cohen turned an initial $US25 million in the early 1990s into his fortune – as a possible successful example also of the Kelly Criterion risk management strategy.

 

5. Cohen factored in transaction and execution costs. Keefe alludes in passing to how SAC used dark pools – private exchanges that hedge funds use to trade their positions – in order to exit Martoma’s Elan and Wyeth trades. Kiev’s game theoretic reasoning about catalysts and other market participants provided one rationale that was influential in SAC’s organisational strategic subculture. Awareness of transaction and execution costs – and their impact on a trade’s profitability – provide another rationale. In one of the few public statements by SAC staff, Neil Chriss emphasised the importance of considering transaction and execution costs in his introduction to Robert Kissell and Morton Glantz’s book Optimal Trading Strategies (New York: AMACOM, 2003), pp. viii – x. Chriss suggested there was “an efficient frontier of trading strategies . . . Each strategy has a certain transaction cost and a certain risk” (emphasis original) (p. x). He then stated: “no institutional manager can afford not to understand transaction costs” (emphasis original) (p. x). In doing so Cohen anticipated the impact that dark pools, and algorithmic / high frequency trading have had on contemporary market microstructure.

 

There is thus far more to Cohen’s hedge fund success with SAC Capital – his sustained edge over two decades – than what the Martoma insider trading case has revealed to-date. Keefe’s New Yorker profile reveals aspects – but more trading knowledge is needed to piece together Cohen’s secrets from public information sources.

Reading Steve A. Cohen’s White Paper in the SAC Insider Trading Case

I’ve followed hedge funds – pooled fund structures that engage in active management often uncorrelated with financial markets – for about a decade.

 

Almost 12 years ago I wrote a Masters paper on Long-Term Capital Management (PDF) in Swinburne University’s Strategic Foresight program. I read Sebastian Mallaby’s history More Money Than God (PDF) and MIT’s Andrew Lo. Hedge funds appeared to be exemplars of Richard Slaughter‘s Institutes of Foresight thesis. More recently, I have thought of hedge funds as possible examples of meso-level, organisational strategic subcultures.

 

Today, I re-watched the PBS Frontline documentary ‘To Catch A Trader‘ (2014) and read the white paper (PDF) from SAC founder Steve A. Cohen’s lawyers in the now-notorious Elan and Wyeth insider trading case. Cohen’s portfolio manager Matthew Martoma was convicted of insider trading and sentenced to jail. Cohen’s SAC was fined millions and is now basically a family office.

 

I’ve had the white paper for over a year but only today got a chance to have a close read of it with an eye on how Cohen’s lawyers describe his trading strategies. I learned to do this when studying strategic foresight methodologies.

 

Some of my summary notes from the white paper:

  • Back of envelope estimate of Steve Cohen’s trading portfolio size in July 2013: $US1,253,000,000.
  • Cohen trades over 80 individual securities a day.
  • Algorithms, direct market access, and dark pools are routinely used for trade execution.
  • The PBS Frontline documentary describes Edge as an informational advantage about market activity.
  • The white paper describes the following as Events: (1) corporate access (competitor announcements; adverse developments); (2) market moving (catalysts, technical analysis); (3) analyst convergence (broker-deal reports; ratings such as downgrades); and (4) market rumours (false market).
  • SAC portfolio managers develop a Company Investment Thesis. This may involve: (1) trimming positions whilst going into earnings announcements; (2) using option hedges to offset long/short positions using a market neutral strategy; (3) anticipating slippage: incremental shifts in share prices due to the timing of executed trades; and (4) responding to risk reviews of large positions.
  • Market price-psychology patterns that Cohen has identified: (1) increases in individual share prices versus S&P 500 declines (deteriorating market) over specific time periods; (2) tests of if positive market reaction is sustainable (possible mean reversion); (3) company news that is ambiguous or less-than-spectacular information that will trigger a decline; and (4) rapid stock appreciation that creates high expectations and the probability of a price decline.

 

The Steve A. Cohen white paper illustrates how to potentially reverse engineer a hedge fund’s trading strategy – as a strategic foresight example – and to not be a Muppet-like naive retail trader.