From the May 01, 2010 issue of Futures Magazine • Subscribe!

Forex fund management, student trader style

The best way to describe the Flyer Forex Fund’s birth into the currency world is with a horse analogy. At the beginning of the fall 2009 semester, there was much student interest in building the fund, but no knowledge base to leverage. The professor was stuck with simultaneously teaching the fundamental and technical trading of the currency market and building the fund. The horse ran wild in many directions and required a lot of effort to corral and tame. Then we found that the cowboys liked certain tasks (mostly the trading) but lacked the discipline to perform consistently the middle and back office functions. Again, the lack of knowledge about middle and back office functions came into play, and the professor found that assuming a knowledge base often meant a valuable waste of time. Christmas break came and the horse stopped running and just stood around in the field.

The spring semester began; the student body managing the fund totally changed, with only three students carrying over from the previous semester. Of the three carry-over students, each student tried to actively lead a portion of the fund. However, now it seemed the horse had trouble being led forward and there was significant resistance on the harness. While much improvement had been made to the back and middle office functions at the end of the previous semester, it seemed in January we started from scratch again. By February, after resolving many operational issues (both old and new), our horse was off his feet and plopped down in the pasture. We looked around and knew we needed a defibrillator to revive it.

The student management of the model trade produced a loss of $4,280 vs. a gain of $7,980, if the model was run purely over the time horizon. “Not how it was planned,” right, illustrates the difference between the pure model and our students’ execution of that model; in other words, it is the cost of the learning curve of the students running an FX algorithmic model. The object of the simulation of the fall semester was to get to trading real money in the model during the spring semester. That did not happen. Of further note, this fund was purely a student self-motivated experience and no grade was given. It was not for any academic credit and its purpose was solely to increase the students’ practical knowledge base.

The desired method
The students opened a demo account at FXCM of $50,000. They were to trade one lot ($100,000) as directed by the model based on the four-hour chart (see “Learning to Trade,” October 2009). The only currency the fund traded was the euro. We began trading on Sept. 6, 2009 and finished for the purposes of this analysis on March 4, 2010. All documents were kept on a Google Group site. We also ran a weekly update on a blog spot Each team of students, regardless of semester, rotated though six trading teams and one management team weekly. As a result, every student had experience in the front, middle and back office of the fund. To discuss this experiential learning event, we break down our analysis of the cost of the learning curve into front, middle and back office issues and management buckets, which occurred over both semesters unless indicated.

(Click on image above for full-size chart.)

Front office issues
Operationally, the “trader” had the following duties to the Flyer Forex Fund: read the market data at the correct four-hour candlestick, immediately update the data within the model as the close of that candlestick, run Girth calculations to determine if a market action was needed, and execute the trade in a timely manner in the correct pre-determined lot size as necessary. If any error occurred in this process, the trader was required to update the error report and estimate the dollar cost of the error. If there was any market action, the trader was to print out the FXCM profit/loss report from the system and at 3 p.m. each day the trader ran the same report regardless of market action.

The fund faced issues across the entire trader process. Traders were consistently unable to update the model, execute in a timely fashion, report errors, or find trader replacements if they were in class at the execution time and could not reach a computer. Trading teams could not communicate consistently, despite the fact that they were in close geographical proximity. All data was located on a Google Group site, but many traders lacked the discipline to monitor the site regularly. Operational issues entailed entering a trade with the incorrect lot size (for example, $90,000 instead of the pre-determined $100,000), entering the incorrect data in the model either from the wrong candlestick (not the close of the four-hour candlestick) or even the wrong time period candlestick, using the wrong version of Excel (version 3.0 instead of 7.0), which caused model calculation issues and prompted incorrect market action, incorrectly managing the model, which in one case drove the trader to an erroneous early close of a position and thus a re-entry of the desired trade, and finally, leaving the trading platform open with a live trade, which provoked a passing student to close some of the fund’s trades and execute positions in the pound, the yen and the yuan. Amazingly, those trades were profitable!

The biggest drawback of running the fund with new students each semester was the lack of continuity. While the fall students stated that they would oversee and train the new spring students, only three of the fall students fulfilled their mission. However, the majority of the fall students did not participate in the spring semester.

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