There seems to be a developing meme out there suggesting that algorithmic-, and in particular high-frequency, trading is some kind of gold-rush route to easy money which brings to mind…
…this revision of a paper I’d read previously: “Statistical Arbitrage in the US Equities Market” by Avellaneda and Lee. It’s a detailed and thoroughly worked (and now re-worked) paper illustrating the development and analysis of a US equity stat-arb strategy based on Principal Component Analysis (PCA) and then revised to use ETFs.
I came across this paper as I have still never used PCA in any of my own strategy development work and read Carol Alexander’s excellent Market Models over my summer vacation with an eye towards giving a PCA hedging model a spin in the near-term. Thus, I wanted another look at this paper as a reference point. Although it’s an excellent paper, I’m not going to urge you to go out and read it immediately unless you have a reasonably pressing practical interest. Instead, I find it interesting largely because of one of its authors – Professor Avellaneda – and its conclusions in the form of its strategies’ performance.
I’ve seen Prof Avellaneda speak a number of times at a variety of quant meetups organized by the relevant Columbia/NYU financial engineering depts. His paper reminds me that at least once during my noisome adolescent years, my father intoned darkly that:
the streets are littered with brilliant minds