Introduction to Profit Factor

The profit factor (PF) is one of the most important statistics to calculate when developing a trading system.

PF is defined as total profits divided by total losses.  Another way of stating this is:

average net profit on winning trades      # winning trades
——————————————————-  *   ————————–    (1.1)
average net loss on losing trades             # losing trades

Although very similar, I would point out that PF is not exactly the same as a trading system’s expectancy (E):

Expectancy (E)  = (Probability of Win * Average Profit) – (Probability of Loss * Average Loss)

E may be interpreted as the average gain or loss per dollar risked on a trade.  PF may be interpreted as the number of dollars made per dollar lost. A successful trading system should have E > 0 and PF > 1.

Maintaining a relative equivalence between average losses and average gains is one way to run a successful income trading business.  Consider a trading strategy that sells 20 naked puts per month for $2.00 each to collect $4,000. These puts are so far out of the money that only a very rare event will result in a loss.  Eventually, October 2008 happens and this very consistent trade suddenly loses $396,000.  Not only did this one month just wipe out profits from your last 99, but the psychological devastation will likely result in a swift career change.

The PF calculation gives us the minimal requirements by which to profit through income trading. If a strategy’s average losses are three times its average gains then the second term of (1.1) must equal at least 3 for PF to exceed 1.  That is, three trades must win per every trade lost: a win rate of 75%. Similarly, if the strategy loses twice as much as it usually gains then it must win 67% of the time to break even.

I will build on this concept of PF in my next post with an introduction to Sizing Risk.