The following is a review of A Mathematician Plays the Stock Market, by John Allen Paulos.
One of my inaugural tasks at my current job was developing a technical analysis package for market data. I have to admit I rather enjoyed this, for a few reasons only tangentially related to the specific technology at hand.
First, I like solving math problems—always have. Writing programs that do this for me are more enjoyable still. Second, there was the shameful thrill of scrawling some equations involving capital sigmas (the kind of thing those of us destined to be computer scientists are doing by eighth grade) on a whiteboard and watching the panicked expressions of the business and finance people present.
I guiltily concede that the latter motivation was the dominant one. I still keep a sheet with sigmas painted all over it within reach. Anytime I’m asked about the output of my analysis package, I produce it from deep within my desk which by the way, overwhelmingly contains only ketchup (Heinz) and straws (plastic, non-bending). I’ll scribble some new symbols on it and say something like, “so as you can see, the limit of this term as phi approaches infinity is…” and before I’ve finished the sentence the person has muttered something in bewilderment and shuffled away.
I’m not necessarily doing this out of malice or contempt, it’s just that I realized a long time ago that the technical analysis of market data is largely a crock. I’ve always carried this nagging little fact with me, and at times I’ve pondered the morality of having this job at all. So I’m not really doing the user a disservice here, unless I’m somehow expected to explain to everyone in the world that you can find meaningful patterns in any set of data—words in the bible, petals on a flower, sand on the beach, or the price of Superconductor (NasdaqSC:SCON). Chances are, the pattern that you discover holds no predictive power.
So it’s really not important to the person asking what the answer is, it’s just reassuring to believe that I possess one. In the end, they will probably make about as much money as chance would dictate. Maybe a little more, maybe a little less. If they do happen upon the holy grail, that ineffable oracle of a model that really can forecast the future, it is as likely to be in spite of my explanation as it is to be caused by it. Populus vult decipi; decipiatur.
How odd it is, I found myself thinking while reading this book, that there exists a Nobel prize for Economics yet none for Mathematics. Is my support for this book just another example of confirmation bias? I’m obviously not qualified to say. I suggest you judge it for yourself.