Why discretionary Trading?

A young reader sent me an email and in one section asked me why I switched from mechanical trading to discretionary trading and I thought it was a very interesting question, especially considering the recent popularity of “algo” driven strategies. For one I think there are many misconceptions regarding black box trading and the biggest one is that in some way your work is done once you discover the ‘right’ algo. From that point you simply switch on the money maker, sit on a beach, and drink mojitos; RenTech has over 95 PhD’s full time on staff, I worked with another individual full-time, 10 hours+, 5 days (sometimes 7 on my spare time) at a hedge fund, researching….researching….researching. The quest is never ending, and in the end your left searching for a grail that does not exist.

Perhaps you are ‘enlightened’ and realize that truly successful algo trading is based on portfolio construction, risk management, and position sizing. You’ve cut back on work considerably but you will eventually and inevitably come to a point where your skill in deciphering a market inflection point will be put to the test.

I think this paragraph from “Against the Gods” summarizes why much better then I could:

“The past seldom obliges by revealing to us when wildness will break out in the future. Wars, depressions, stock-market booms and crashes, and ethnic massacres come and go, but they always seem to arrive as surprises. After the fact, however, when we study the history of what happened, the source of the wildness appears to be so obvious to us that we have a hard time understanding how people on the scene were oblivious to what lay in wait for them. Surprise is endemic above all in the world of finance….

If these events were unpredictable, how can we expect the elaborate quantitative devices of risk management to predict them? How can we program into the computer concepts that we cannot program into ourselves, that are even beyond our imagination?

We cannot enter data about the future into the computer because such data is inaccessible to us. So we pour in data from the past to fuel the decision-making mechanisms created by our models, be they linear or nonlinear. But therein lies the logicians trap: past data from real life constitute a sequence of events rather then a set of independent observations, which is what the law of probability demands…..Once again, resemblance to truth is not the same as truth. It is in those outliers and imperfections that the wildness lurks.”

Your model works until it doesn’t. How do you know it’s not working? Well you can wait till you have enough trades and analyze the distribution versus the past distribution or against a back test but by then your broke. No, at some point one has to make a discretionary decision, has the market changed??

So instead of chasing my tail, I’ve decided to focus on learning and analyzing the intangibles in the market. How to read the tape, when is it right to have a bullish bias, bearish bias, no bias. Re-read “Reminiscence of a Stock Operator” and apply that versus say Advance Statistical Analysis. I just need to be good enough to be consistently profitable. I have learned the skills to test my ideas before implementation and an understanding of behavioral finance so I have a chance to inhibit biases while trading or formulate a method (thru stop losses, position sizing, etc) to work around them. Only time will tell I guess, if it doesn’t work out I guess I can sell the old systems online for $$$ 🙂

~ by largecaptrader on March 24, 2010.