We can find the probability of being profitable N periods into the future using Ralph Vince’s concept of Leverage Space Theory. In Vince’s new book “Risk Opportunity Analysis,” he describes a technique that joins probability tables, allowing you to calculate the probability of being profitable after N time frames. Using a leverage space library created by Joshua Ulrich, we calculated the probability of profit from one to 24 months. We use the robust method to calculate f, which is P/2=0.30 in our case because we have 60% winning monthly periods. Our results are shown in “Monthly profit probability” (below).
On the first month, the probability of being profitable matches the winning percentage in the results of our simulation. This rises slowly over 23 months, when it breaks the 75% threshold. Keep in mind that this still means that after two years, 25% of the time you would be losing money. If we look at the monthly returns more closely, we can see that, indeed, we have two losing years in a row.
The win percentage by trade and period return do not give us the same view of chance of future profitability over different periods. We could look at daily returns and apply a Monte Carlo simulation. To do this, we would take sample windows of daily returns over 10, 20, 40, 80, 100, 150, 200, 300, 400, 500 and 600 days. The idea is to take different sampling periods and then calculate the probability of a given window length being profitable after, for example, 100 trials. This will provide a different view of profitability over a given time horizon.
Further research in profitability and time horizons is an important and exciting area. It also is a burgeoning field, as viable applications of the relevant math just are being developed.