I’m a serial tech entrepreneur with Wall Street roots. I’m also in my 26th year of teaching mathematical finance and computing in the masters in mathematical finance program at The Courant Institute of Mathematical Sciences at NYU. My Algorithmic Trading and Quantitative Strategies course, which I co-teach with Petter Kolm, celebrated its 15th year in Courant’s course offerings.
I was one of three founding partners of Pragma Financial Systems, an algorithmic trading boutique that keeps winning hi tech Wall Street praise (like this and this). Among its many clients are hedge funds, banks, pension managers and the New York Stock Exchange.
Before that, I was a statistical trader at Mint Investment Management, one of the first systematic mega funds and once one of the largest commodity trading advisors in the world by assets under management. (There’s more about Mint in Jack Schwager’s interview of Mint’s founding partner, Larry Hite in the book Market Wizards.)
In 1999, I co-founded ThoughtWheel, a technology company that developed a novel knowledge management tool. (My patent for which can be found here.)
In 2002, my partners, David Mechner, Francis Mechner, and I founded Pragma Financial Systems, which eventually became Pragma Securities. After our first meeting, David came to one of my lectures on market microstructure. Those were the early days of algorithmic trading and few people had heard of the Almgren-Chriss optimization much less the more advanced form of dynamic portfolio trading that we wanted to offer to our clients. I will describe dynamic portfolio trading in a separate series of posts. (Meanwhile, here is a paper by my colleagues at Courant, Petter Kolm and Gordon Ritter describing a Bayesian approach to the problem.)
I served as Pragma’s Director of Research until 2008, when I was replaced by Dr. Peter Fraenkel, the same Peter Fraenkel with whom I co-taught my first class at Courant. While at Pragma, I also brought in a former student, Dr. Eran Fishler, who later took over for Peter, and is currently Pragma’s architect in chief (and my co- instructor in the Computing in Finance class at Courant).
Since my departure from Pragma, I have spent my time developing tech startups, some that came entirely from my own ideas, and some in which I hold – or once held and subsequently sold – equity interest. Not all of these startups are in finance but all are influenced by my work on Wall Street studying the universal nature of markets.
Markets are everywhere. You might not think dating is anything like a financial market, but consider the following. In the financial markets, the initiator of a trade – the first to indicate interest or take action – is penalized. Is that also true of the market for romance? Check out this paper! And this one. In a separate post, I will explain why models of market microstructure predict that the initiator of the trade – the seeker – is penalized in all markets, including the market for romance. (In more technical terms, this effect is a direct consequence of aversion to risk and a perception of information asymmetry.)
Currently, there are five startups in my portfolio. They are in various stages of completion. One is close to going live, another is not far behind, and the rest are just burning cash and developer time. That’s how these things work. For every winner, there are usually many losers. (Would be entrepreneurs need a portfolio of significant size to stand a good chance of realizing their profits.) More on my projects in separate posts.
I’m not just the frontman for my ideas. I like to get my hands dirty. I code in Java, Python, and R, to name a few. I like data science and have some strong opinions about the right way to run a modeling project. This is one of my favorite papers on machine learning. More generally, Andrew Ng’s work on data driven – as opposed to model driven – machine learning resonates with me.
Modern heuristics were an early passion of mine. (Here is a cute example of using genetic algorithms to teach robots to walk.) More recently, I spent a significant amount of time working out a novel method for finding the optimal number of clusters to use for a given data set. From this obsession came some fascinating and unusual insights about machine learning and prediction, some of which I will share in a separate post.
Ok, enough. Here’s a little about my other interests.
I read a lot. I go to movies with my eight year old daughter. I love moral philosophy. I host a philosophy dinner in which I cook for my guests and we try to answer some weighty questions. I like the thorny ones, the ones that compel the thin skinned to stomp out. It has happened! One topic temporarily derailed two separate romantic relationships (thankfully, at the time, not my own). I will write a post about a conundrum that recently generated some debate and yielded interesting insights.
I box. I practice judo and jiu jitsu. I take hip hop lessons. I commute on an electric unicycle.
(My posts are currently marked private.)
–Lee
lee.maclin@gmail.com
Lee Maclin rants mercilessly... 