Stop loss levels are essential when you trade with leverage. Nonetheless, most traders put far more time into forecasting where prices will go and what type and size of position to take than determining stop levels. In fact, stop determination often is the last thing done prior to making a trade. This is a common mistake, and one that traders need to correct for long-term success.
There are a number of ways to set stops. Popular stop techniques include:
- A pure money management approach. The trader determines what he or she is willing to lose and the position size. The stop level comes out of the math.
- Using technical/chart points. A typical argument would be: “If it violates the recent breakout, the uptrend is negated, and I’m out.” This often is hard to reconcile with a fundamental approach where the upside becomes more attractive as the price goes down.
Here, we will describe a mathematical approach to setting stops, using the techniques of Bayesian statistics, a field of statistics that focuses on data distributions and probabilities. A Bayesian approach is useful in many trading decisions because:
It lets you combine your intuitive judgments with objective market data.
It provides a mathematically optimal way of changing your judgments as new market data comes in. This will allow us to move a trailing stop.
We’ll begin with the basic concepts of Bayesian statistics and then explain how it can be used to set stops. We also will show how to use an online tool to experiment with this technique further on your own.