Quant Analysis for Discretionary Traders

My office is entirely composed of ‘discretionary’ traders. ‘Discretionary trader’ tends to conjure images of cowboys who shoot from the hip or ‘trade from the gut’ type persona. While sometimes the size and frequency of some of the individual trades seem haphazard even to me, most of the guys employ some system or process to their trading strategy. So when I say ‘discretionary’ it is more likely their position sizing and portfolio construction is based on intuition but their actual edge comes from some repeatable process.

In any event, part of what I do is analyze each traders performance for the previous year and create an independent report which is utilized by management during the yearly trader review. It’s a pretty straightforward analysis consisting of basic statistics that are similar to reports I analyzed when I back tested strategies at a hedge fund; For example, equity curve, stats like win/loss rations, Sharpe Ratios, average win to average loss, etc.

Monte Carlo so I look smarter then I am

Equity Curve with P&L removed

The challenge I face is that most of this data is brand new to the traders. Despite the hedge fund or previous prop background, many of these guys have very rarely calculated their own statistics or performed any post trade analysis. It is up to me to translate these statistics into relevant, understandable, and actionable ideas for the trader to improve their performance in the upcoming year. This is quite a challenge indeed. Even with cold hard facts looking you straight in the face, it is extremely difficult to get someone to change behavior. One example was a fundamental technology analyst who was superb at identifying medium term trends but an absolutely atrocious day trader. And it wasn’t an insignificant sum, we’re talking over 7 figure losses for positions held intra-day. When you consider the high payouts associated with prop trading, that’s a lot of cheese.

~ by largecaptrader on March 7, 2011.

2 Responses to “Quant Analysis for Discretionary Traders”

  1. That’s interesting, I’m one of those guys! From a practical standpoint, how do you use those kind of statistics to improve trading?

  2. Each trader looks at different statistics. Honestly, in some cases the statistics don’t find anything useful (scratch traders for example) Others, like the sector specialist, really appreciated a holding period analysis. Day traders liked P&L by day of the week. I thought that stat is pretty useless. I personally think your win rate, avg gain/loss, and peak to trough draw down are most important. There are certain strategies for trying to improve one metric over the other, perhaps when I have some time I could go into further detail on it…

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