Single Market Factor #1: Optimal f in Share Market
In his 1990 book titled “Portfolio Management Formulas,” Ralph Vince popularized a formula known as optimal f. The theory behind this method is that:
• There is a “correct” amount of capital to apply to any contract using a particular trading approach in Stock Market.
• Trading using the “correct” amount of capital will maximize the profitability experienced without sustaining a total loss of capital in Stock Market.
• Trading with less than the suggested amount of capital will likely result in a total loss of capital in Stock Market.
• Trading with more than the suggested amount of capital will result in an exponential decrease in the percentage return compared to using the “correct” amount. In brief, using a listing of actual and/or hypothetical trades generated by trading one market using a given approach, a calculation is performed and a value is arrived at between .01 and 1.00. The largest losing trade within the listing of trades is then divided by this value to arrive at the suggested amount of capital with which to trade one contract.
As an example, if the largest losing trade within a particular trade listing was $2,000 and the optimal f value turns out to be 0.40, then the suggested capital amount would be $5,000 ($2,000 / 0.4). According to this theory, if you were only going to trade one contract of this one market using this one trading approach, then you should place $5,000 into your trading account. If future results mirror past results your percentage rate of return will be maximized by trading with $5,000. Also, according to the theory, if you trade with less than $5,000 you will likely “tap out” and if you trade with more than $5,000 you may trade profitably in Stock Market. However, your rate of return will be far inferior than if you had traded with $5,000. Needless to say this is a bold theory. This approach makes the assumption that future trading results will be similar to past results. If future results are far inferior to past results then the end result using optimal f can be disastrous. However, in testing using trading systems that have a positive expectation, and for which future results were similar to past results, optimal f has definitely shown the ability to increase profits exponentially compared to simply trading a preset number of contracts. Unfortunately, the reality of the situation is that using optimal f to trade one market is generally not practical. The big problem with a strict usage of optimal f is that it does not consider drawdowns in its analysis. The only measure of risk that is used is the single largest losing trade. While the case can be made that this is statistically correct, the fact of the matter is that using this method alone will invariably result in large percentage drawdowns at some point in time. Because the drawdowns that can result on a single market basis can be huge in percentage terms, most traders will not adhere to this approach long enough to enjoy the expected benefits in Stock Market. However, the goodnews is that this method can be very useful when applied across a portfolio of stock markets.
Whether you choose to trade systematically, subjectively or somewhere in between there are certain criteria that you need to address in stock market. The more clearly stated and objective your answers to these questions, the greater the likelihood of your long-term success in stock market.
Be sure to constantly ask yourself, “what is the worst case scenario and what will I do if it unfolds?” If you always have an answer to this question you have the potential to be a highly successful futures trader. On the other side of the coin, if you find yourself reassuring yourself that, based on your analysis, you have nothing to worry about, then you DO have something to worry about. If you have no real contingency plan for protecting yourself if you turn out to be wrong, be afraid, be very afraid. Remember, it only takes one bad trade to wipe out a lot of hard earned money. If you don’t believe me, ask Victor Neiderhoffer.
