In a truly bizarre story, CNBC is reporting allegations that traders at SAC Capital were forced to take female hormones in order to reduce their aggression, in hopes of improving trading performance. The allegations stem from a sexual harassment suit filed by one of the hedge fund’s junior traders, who claims that “the hormones caused [him] to start wearing dresses, avoid his wife’s touches altogether and allegedly begin a sexual relationship with his boss”. The story is all the more dramatic given that the trader’s boss is Ping Jiang, a top trader with a reported income north of $100 million a year.

Sexual harassment cases are nothing new on Wall Street, but CNBC has uncovered new details of one of the most salacious cases to hit a big trading house in a long time.

The case involves a sexual harassment lawsuit filed by a Andrew Z. Tong, a former junior trader at SAC Capital, the powerful Greenwich, Conn., hedge fund, against one of SAC’s top producers, a trader named Ping Jiang.

A New York State judge has sealed the case and sent the lawsuit into arbitration, where both sides would battle it out in private. He even cancelled oral arguments that were scheduled for Thursday following an appeal by Tong’s lawyers, who want the case to remain in state court.

The judge said he sealed the details of Tong’s allegations contained in the lawsuit because it is not in the public interest to disclose the salacious nature of the complaints. CNBC has learned the suit includes the following allegations made by Tong against Jiang:

• After being hired at SAC, Tong alleges that Jiang came to him and told him he had a trading method in which his traders must not be too aggressive; that traders must be more effeminate and to do so, he directed Tong to begin taking female hormones.
• Tong says he then took the female hormones that he bought on the black market.
• Tong then alleges he suffered emotional and physical distress. The hormones, he says, caused him to begin wearing women’s clothes. He also could not perform sexually with his wife, who wanted to have a baby.
• Tong says the sexual harassment included sexual relations between the two men.

While the salacious details will certainly generate a lot of press, could it really be that giving your male traders estrogen Kool-Aid would actually improve their market performance? Let’s review the research.

In many contexts, men have been found to be systematically more overconfident than women. Among these is “Gender and Overconfidence” by Bengtsson, Persson, and Willenhag. The authors studied a Stockholm University economics exam which has an optional extra credit question, which only applies to a student’s grade if they did sufficiently well on the rest of the exam. While women overall are more likely to pass the exam, only 83.8% of them attempt the extra credit question, compared to 87.1% of men.

This type of overconfidence can induce many decision making biases which can depress investment returns. Among these are a tendency to trade too often, generating excessive trading costs, and attributing random market movements with one’s own predictive skill, which impairs learning. In a study of trading activity by 35,000 households with a large brokerage house, Barber and Odean report that due to overconfidence, men trade 45% more than women. This excessive trading reduces men’s average net returns by 2.65% a year, compared to a 1.72% reduction for women.

Let’s do a thought experiment. SAC Capital has about $14 billion in assets under management, and reportedly returned 34% in 2006. While the type of trading activity going on at SAC is far different from the household brokerage trades in the dataset studied above, let’s assume for a moment that SAC could capture the 0.93% male-female performance difference if only its traders all behaved more like women. This small performance edge would improve the fund’s returns by OVER A BILLION DOLLARS in five years.

Perhaps it’s no mystery then why a top trader would want his underlings to trade more like women. Maybe the real question then is why a hedge fund would think it was better off taking the substantial legal risk of forcing employees to take drugs against their will, as opposed to working to hire actual women — overconfidence, perhaps?

Read more:

• CNBC: Detail emerge in SAC Capital Sex Harassment Case
  
• Gender and Overconfidence, by Claes Bengtsson, Mats Persson and Peter Willenhag
• Boys Will Be Boys: Gender, Overconfidence, and Common Stock Investment, by Brad M. Barber and Terrance Odean

Earlier:

• Mars and Venus on Wall Street
• All posts tagged “gender”
• All posts tagged “overconfidence”

Earlier this week I wrote about James Montier, global equity strategist for Dresdner Kleinwort, and his contention that purely quantitative models outperform independent human judgment for a wide array of decision problems across many fields of expertise. You can read his whole article here: Painting By Numbers: An Ode To Quant. He gives examples of quantitative models outperforming experts in medical diagnosis, university admissions, predicting criminal recidivism, and even judging the quality of wines. When there is so much evidence of quantitative models outperforming exports, why are the former used relatively rarely?

The most likely answer is overconfidence. We all think that we know better than simple models. My own confession at the start of this note is a prime example of such hubris. The key to the quant model’s performance is that it has a known error rate, whereas our error rates are unknown.

And furthermore:

Grove and Meehl suggest many possible reasons for ignoring the evidence presented in this note; two in particular stand out as relevant to the discussion here. Firstly, the fear of technological unemployment. This is obviously an example of a self serving bias. If, say, 18 out of every 20 analysts and fund managers could be replaced by a computer, the results are unlikely to be welcomed by the industry at large.

Secondly, the industry has a large dose of inertia contained within it. It is pretty inconceivable for a large fund management house to turn around and say they are scrapping most of the processes they had used for the last 20 years, in order to implement a quant model instead.

Another consideration may be the ease of selling. We find it ‘easy’ to understand the idea of analysts searching for value, and fund managers rooting out hidden opportunities. However, selling a quant model will be much harder. The term ‘black box’ will be bandied around in a highly pejorative way. Consultants may question why they are employing you at all, if ‘all’ you do is turn up and run the model and then walk away again.

It is for reasons like these that quant investing is likely to remain a fringe activity, no matter how successful it may be.

Read more:  Painting By Numbers: An Ode To Quant

Earlier:

• James Montier: Quantitative Strategies Rule
• All posts tagged James Montier

In a recent interview with Smart Money magazine, finance contrarian Nassim Taleb discusses one of the reasons more information does not always improve the quality of our decisions. There are rapidly diminishing returns to the number of new pieces of information we factor into a decision. Yet more information has the psychological effect of increasing our confidence in the correctness of our decision making process. This overconfidence impairs our ability to evaluate our current decision against viable alternatives.

SM: Explain what high-frequency information is and why it’s bad for you.

NT: Here’s a simple example. Psychologists ran experiments to see how people absorb information. In one experiment they found people who work with racehorses, and asked them to name up to 50 pieces of information they would need [to determine if it was going to be a winner]. They ranked them by order of importance. They took the 10 most important ones out of 50 and looked at the prediction of accuracy to determine if a horse will win a race. Then they took the 20 most important pieces, then the 30. In the end, you had no gain in predictive power beyond the first 10 pieces of information, but a huge gain of overconfidence…

I showed in the book that if something has a 93% probability to happen over a year, in one second the chances of it happening are 50-50. If you sample it at a smaller frequency, there’s more information and less noise. You would think your brain can handle cleaning up the noise, but it can’t. We have cognitive impediments that make us very vulnerable to information overload. You get like a pot that you fill up with water. Too much information is bad for your ability to see the meaning. This is the second effect; I call it a scaling problem.

People ask, Isn’t information good for you? Information is good for you, but try to filter it. Your brain can’t handle filtering itself. For example, you will feel good if your portfolio performs well two hours in a row. It’s insignificant; it does not reflect your abilities or the abilities of your manager. You feel good without knowing why. Likewise, having the opposite will put you in a bad mood, without the faintest idea why. Basically, noise can control you because you don’t use your cognitive skills when looking at data at a high frequency.

Read the full interview: Smart Money — Chance Encounters with Nassim Taleb