One of the most important underlying concepts that contribute to the success of Trend Following is the fact that the strategy is based on the non-normality of market returns. Let me explain.
Trend followers position themselves to profit from and capture the “fat tails” exhibited in market returns distribution. In a fat-tail distribution (Power law, Levy or Mandelbrotian distributions), extreme occurrences occur with a probability greater than normal.
If you put in stops and run your profits and trade randomly you make money; and if you put in targets and no stops, and you trade randomly you lose money. So the old saw about cutting losses and running profits has some truth to it.
The basics of trend following is to ride the trend until the end (when it bends) and to protect yourself on the downside by cutting your losses.
This ensures that the location of your trades in the returns distribution will:
As the markets are mostly random, most of the trades will end up in the centre of the distribution curve either side of the horizontal axis – and their return should cancel each other out.
Trend Following’s alpha (the actual strategy return) is generated by extreme movements: By letting trades run on the right-hand side fat-tail and stopping them from “wandering” on the left-hand side one, an overall positive return is generated. This outlines the fact that Trend Following relies on rare extreme returns (outliers) whereas the bulk of trades cancel each other out.
Note that this post simplifies matters to illustrate the fundamental point. Other parameters such as trading costs, etc. obviously need to be considered.
UPDATE: For those readers wanting to investigate this concept a bit further, a later post presents a research paper investigating the effects of the 4 first moments of the price distributions on the return of a Trend Following system. Please read here