Another significant operational risk is the passing of a contaminated book: a model that has errors in it. To mitigate this risk, each morning the management team confirms the accuracy of all the data entered into the model over the last 24 hours, prepares a daily profit/loss report that combines both cash and mark-to-market positions and reports any anomalies to the fund’s faculty supervisor and
The managing team also is responsible for preparing weekly reports summarizing the fund’s closed trades, floating P/L and other parameters of the fund’s performance, including any operational risk occurrences or human errors.
At the end of New York trading on the last trading day of each month, the fund closes any open position and goes to cash. The managing team is responsible for this action and for the preparation of the end-of-month performance and investor return reports. The end-of-month liquidated positions may be re-established at the beginning of the new month next trading day, if girth and trends dictate. These steps have been implemented to mitigate any issue of an operationally contaminated book.
Risk management is largely intrinsic to the girth model, as the model never enters trades against the four-hour trend. The model instead is traded with the trend, after the trend is established, and then looks to make an early exit from
The girth model works best when there are strong trends during the four-hour time frame. The model may churn or yield no profits if the market is not trending during the four-hour time frame. However, the trader will never be able to hold a long position against a short trend; thus, it inherently limits losses. Further, each trade will be entered with a hard stop loss, which is determined by the volatility of the market. If normal market historical volatility dictates 80 pips of noise in the market, then an 80-pip stop loss is set. However, if historical volatility has increased two fold, then the stop loss will be set higher than 80 pips as a factor of volatility.
Implementing the girth model also gives students a chance to calculate value at risk (VaR) and to monitor VaR over a floating P/L position. Of course, the actual calculation of VaR needs to be taught before such an undertaking ensures.
A strong sense of discipline will also be instilled via reporting, which will be performed on a daily, weekly, monthly and end-of-semester basis. Basic reports will be posted to the Web at the same frequency. Students will be required to produce updated analyses of volatility, VaR, average trade length, P/L (cash and floating), maximum drawdowns and any deviations from the trading model. At the semester’s end, the entire group will issue a written report to the center summarizing the fund’s performance. The group will prepare a professional road show presentation, comparing the fund’s performance to various benchmarks, and evaluating correlations between the fund’s performance and that of other investment types.
There is a lot to learn and a lot to implement before the girth model can run smoothly. The process has a large risk of human and operational error, even after the requisite knowledge base is obtained. For these reasons, running the model in simulation to build experience is prudent. The move to trading real money depends on how well the simulation goes.
Leslie K. McNew is a clinical professor of finance and visiting director at the Hanley Group Derivatives Trading Center, Department of Economics and Finance at the University of Dayton Business School. E-mail her at firstname.lastname@example.org . Dr. Tup Ingram is a private trader. E-mail him at email@example.com .