Hack the market

There’s an old wall st saw: “Sell Rosh Hashanah, Buy Yom Kippur” that, according to this guy at least, has had good performance since 1915.

I haven’t tried to reproduce his work to confirm it, but I’m certain that anyone who bought today’s close is a serious mensch!

Although we’ve been in business since 2005, we’re still something of a start-up and certainly an entrepreneurial entity, so when a VC friend of mine suggested checking-out meetup.com‘s technology and business groups I was open to the idea. This past week I attended my second meeting of the “ny tech” group and was as impressed the second time around as the first. It’s quite a production – from the venue, to the organization, to the ideas, people and products being presented – all for $5! (Though they sadly announced a price increase to $10 starting next meeting.) If you have even a small inclination towards entrepreneurial ventures or emerging technologies, it’s well worth a look-see.

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This week we spent a few hours at the tradetech conference to see what people in the industry are up to and see some demos. Their “certified” logo inevitably reminded me of an old colleague who would from time to time mimic an old saturday night live skit. We saw some interesting things and, most importantly, found that our creative niche remains our own.

The booths we checked out included a few of the big sell-side firms shilling their creatively-named execution quality algos and their white-labeled oms/ems offerings. They had, by far, the best shwag (I should thank Merrill for their nice umbrella and commend citi for the very knowledgeable lady at their booth) but their algo offerings weren’t very interesting to me as they aren’t of the alpha-seeking variety.

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This week I attended another of the excellent quant seminars I’ve written about before. This time the talk was about stochastic modeling of equity markets and was presented by Robert Fernholz of Intech. Intech is evidently a subsidiary of Janus which manages some large amount of money presumably based on some of the portfolio management theory on which Dr. Fernholz is an expert. If you visit their site, you’ll be greeted by a bigger version of their credo which I’ve, um, honored as this post’s banner: “Math is power.”

Right then. While Mao would likely have been capable of convincing me otherwise, it’s probably best for everyone involved that portfolio managers are running around with esoteric mathematical models rather than the sorts of munitions favored by 20th century Chinese revolutionaries…

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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.

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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.

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