academic papers

  • 02 Nov 2012 at 5:44 PM

Traders Copy Academics Who Copy Traders

Ed Thorp is by all accounts a pretty bright guy, having invented among other things1 card-counting for blackjack and the Black-Scholes formula for option pricing. Here is a short story2

… about Ed Thorp and his discovery of the formulae and their use for making money (rather than for publication and a Nobel Prize!) … Fischer Black asked Ed out to dinner to ask him how to value American options. By the side of his chair Ed had his briefcase in which there was an algorithm for valuation and optimal exercise but he decided not to share the information with Black since it was not in the interests of Ed’s investors!

The rest is some sort of history; Thorp made lots of money trading options (and then lost it, as one does)2a; Black figured out how to value options, published the formula, got his name attached to it, and won a Nobel Prize. Nobel Prizes are harder to lose, so there’s that, but otherwise I think a lot of people would take the money.

A while back we talked about a sort of astonishing paper that showed that stocks go up predictably before every FOMC policy announcement, earning 3.89% excess return on average, and I said “One thing you might ask about any economics paper that identifies a colossal and tradeable market inefficiency is: why on earth would you publish this? … I guess it’s safe to assume that tombstone for ‘the pre-FOMC announcement drift’ will read ‘1994-2011′: if, going forward, you can make a free 3.89% excess return by buying on pre-Fed days, you will, so you can’t.”

Today Dan Primack reports on some academics working in a field not dissimilar to that suggestion and it turns out I was only about 1/3rd right. The paper is by R. David McLean of Alberta and MIT/Sloan and Jeffrey Pontiff of BC, and it is called “Does Academic Research Destroy Stock Return Predictability?” and, read it, it is rich with things to ponder. They look at 66 academic studies that identify 82 “anomalies,” meaning looooooosely speaking examples of weak-form inefficient markets – things where publicly available historical data can be used to predict future performance. Here is the main conclusion: Read more »