Professor DeLong points out that Emanuel Derman has begun posting lecture notes to classes he’s teaching as part of the Columbia Master’s of Financial Engineering. If you’re even remotely interested in financial engineering or algorithmic trading, then you should read Dr. Derman’s engrossing book “My Life as a Quant” as it gives a unique and personal perspective on the explosion of engineering as a discipline within finance. I haven’t studied his notes carefully yet but a cursory examination suggests they look very worthwhile.
I recently found in my inbox an invitation to study for a Certificate in Quantitative Finance which is, I’m sure, a great program. But it’s pretty pricey and any quant should be aware of costs! Laughing in the dark might be a reasonable alternative to shelling out for a more structured offering…
Among the more challenging questions we face when describing the Puppetmaster environment are those like “how do you create new proprietary trading strategies within the environment?” It’s a difficult question because of expectations – people want to hear about some super simple scripting language that any non-technical person can immediately learn and be up and algorithmically trading in no time. A few platforms intended for retail users offer such things – one is even appropriately named easy language. When researching approaches for our system, we spent some time learning easy language and found that it in fact did make easy things easy!
The problem was that it also made sophisticated things impossible.
This led us to pursue another, more powerful, approach for which we are currently seeking a patent.
This past week I had the opportunity to see MIT’s Professor Andrew Lo present his paper “What Happened to the Quants In August 2007?” as part of the seminar series on quantitative finance presented by NYU and Columbia and sponsored by BlackRock and other relevant institutions. If you’re in the NYC area and interested in such things, I recommend attending any lectures which might capture your fancy.
I had read his paper some time back and implemented, within the Puppetmaster environment, the mean-reversion trading strategy he used as a microscope into what transpired last August. I was interested to see him speak as he’s a seminal thinker on hedge funds and quantitative finance, but also because the strategy he described works pretty well and I thought he might hint at various improvements.
I’ve stolen a line from his paper to serve as the title of this post as it captures one of the central dilemmas faced by algorithmic traders.