By slicing and dicing performance data, we can gain a valuable window on strengths and weaknesses and areas to target for improvement. Of course, the data must be collected over a sufficient time that we see meaningful trends and differences, not just random changes. During any week, a pitcher may do better or worse in a category simply because of normal variation in performance. It is over time that we see important distinctions emerge.
It is common for performers to have blind spots in their self assessments. A simple example would be driving skill. The great majority of drivers rate themselves as better than average when we know that, statistically, that can't be the case. If we had on-board computers calculating things like speed, braking time, closeness to other vehicles, etc., we could more accurately detect who was driving well and who wasn't. Indeed, the metrics would detect areas to focus upon to improve driving that the driver might not be aware of at all.
So it is with trading. We write in journals and we assess our performance, but rarely do we take a hard look at actual performance data. Very often, if we don't measure it, we can't manage--and improve--it. Here are a few examples of traders I've recently worked with who have used metrics to get to the next level of performance:
* A diligent trader measured confidence level in each trade taken based upon the evidence in favor of that trade idea. The trader then tracked the hit rate on high confidence trades versus others. When he saw that the high confidence trades actually had a greater likelihood of being profitable, he began sizing those larger and making more money;
* A wise portfolio manager went back to previous trades and calculated the P/L on those trades if the entries had been made at the end of the trading day rather than when they had actually been made, during the day. The profitability of the trades improved markedly simply by entering on an end of day basis. When entering during the day, the trader tended to buy strength and sell weakness out of a fear of missing the move, creating poor trade location and diminished reward-to-risk.
* A motivated trader working on becoming better at generating ideas kept track of the correlation of his P/L with his hedge fund overall, with the markets he was trading, and with hedge fund industry statistics. Over time, he saw a reduced correlation as he traded some unique strategies and expressed views in more unique ways.
* A concerned trader working on discipline and taking better trades calculated her hit rate on trades (percentage of winning vs. losing trades), and also compared the average size of winning vs. losing trades. We additionally calculated forward P/L after runs of recent winning and losing trades. All of these helped to measure whether she was becoming more selective in her trading, whether she was engaging in sound risk management, and whether she was avoiding overconfidence and underconfidence after winning and losing periods.
Almost any trading goal that we can set can be measured with the right metrics. We may feel we're getting nowhere or we may delude ourselves that we're making progress, but over time the numbers will tell us where we truly stand. Focusing on improving our metrics is a great way of improving our trading processes and not becoming overly focused on short-term P/L.
What are you working on right now and how are you measuring and recording it?
Further Reading: Using Metrics to Discover Your Trading Psychology
.
Komentar
Posting Komentar