Introduction

Welcome!

My intention with this is to share my ideas and methods of analyzing electronic trading performance. The term "trading performance enhancement" is somewhat broad and consists of numerous areas that could lend themselves, respectively, to helping the active trader improve his/her performance.

This blog addresses in detail what I consider to be the single most important aspect in the process of performing consistently better in the market: statistical analysis of past trading performance; the collection, calculation and arrangement of metrics in various formations with the intention of discovering and pinpointing performance strengths, weaknesses, tendencies and trends.

I'm referring to running detailed analysis of past trading results, modifying your approach accordingly, trading again for a period of time, and then repeating the entire process until you fine tune your approach to consistently yield profits that are to your liking.

I'm going to use the analogy of Golf, which is particularly fitting here. At the end of each round of golf, the golfer knows his overall score, and how he scored on each hole. The golfer primarily refers to a single number in measuring his performance: the final score on the round. The intermediate golfer looks back and remembers a handful of great approach shots, one or two long birdie puts, and a few drives that seemed the best he's ever hit. The idea would be to replicate these shots as often as possible and repeat exactly what he did on the great shots.

The problem is, the human memory is selective and lacks the objectivity necessary to accurately perform such a task. What if a golfer could learn more about those great shots so that he could proactively take steps to hit those types of shots more often? Conversely, what if he could learn more about the very poor shots in order to avoid their occurrence in future play?

Consider a device that you could wear around your waist on the golf course. Every time you swing a club, this device would measure the speed of your swing, take note of which club you use, the precise size of your back swing, the precise size of your follow-through, the angle of the club face when contact with the ball was made, your grip, the type of ball you used, the degree to which your knees were bent, the distance to the pin, the weather (including degree of wind, sunshine, rain, overcast), the hole number, and the number of strokes taken on each hole.

Now suppose after each round of golf played, you could take a digital chip out of the device and plug it into the USB port on your PC and download all of the data recorded during play. Let's say you play 5 rounds of golf on the same course. After the fifth round, you withdraw the chip from the device. Later,you insert it into your PC and upload the aforementioned data.

With the device comes a software program which you can use to view the recorded data in various arrangements. With the software, you can group strokes together or look at strokes individually. You can compare your performance on the same hole each of the five times played, and specifically cross certain data elements (measures) with others to look for correlations and trends. What happens, on average, when you use an 8 iron to approach the 16th green from 120 yards away? 3 of the 5 times you used an 8 iron, and the other 2 times you used a 7 iron, and a 9 iron. With which club did you come closest to the pin? What are the optimal weather conditions for your play in certain situations? What are the similarities in the 15 excellent drives that you hit out of the 90 total drives? Were there commonalities in your follow-through? Back swing? Wind direction? Club face angle? Consider the value in grouping together these 15 drives and comparing the above measures to the remaining 75 drives that were average, at best. Maybe then you could learn EXACTLY WHY such drives were great drives.

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The act of actively trading electronic financial markets lends itself to such analysis. It's beautiful. All of the necessary data elements are already captured by the order-entry software the trader is using. We have all the data. What are we doing with it?

Well, until recently not much. Ask any active retail or prop/arcade trader how they track their performance and results, and you'll hear the same thing from nearly everyone: at the end of the day, most look at that all-encompassing number which is either red or green. Some take it a step further and go back and chart up their trades, or import their data into Excel and run basic macros on it. Those who are extremely patient and data-savvy might perform calculations manually, or look back at notes they took during the day.

The above is tedious, time-consuming, and often downright difficult to do. The result is that most traders shy away from looking back at their performance with an analytical eye and reviewing statistics.

On this blog I will introduce easy methods for viewing detailed visual and statistical analysis of trading results. I'll discuss powerful arrangements of basic trade data and statistics, as well as exotic performance metrics created for this niche of trading outright futures or equities. All analysis posted on this blog is generated from the TraderDNA Analyzer, a software application I helped create.

I hope you enjoy the content here and learn something that you can apply.

Stay tuned...



© Copyright 2007 David Adler
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