Statistical Trading consists of using statistical tools on historical price data in order to improve trading returns. The idea behind statistical trading is that if a trader can find even a slight statistical edge, then the expected return over a large number of trades will be positive. I'm talking about the same kind of edge that a casino owner or an insurance company has.
This is a statistical edge based on the law of large numbers. The casino doesn't know if a particular spin of the roulette wheel will be a win or a loss, but they know that after spins they will very likely be richer. Their edge is simple to describe using the game of roulette as an example. So what's the average take for the house? That's why casinos get rich and gamblers go broke. Insurance companies get rich in pretty much the same way.
The company has no idea if a particular person will die this year, but they do have a pretty accurate idea how many people out of 1,, policyholders with a given profile will die this year. So how much should the company charge in premiums for those one million policies each year then?
That's their statistical edge. Now let's look at some ways that we can use this idea of a "statistical edge" in trading. A very common way that traders try to apply the ideas of statistics is by planning trades in such a way that the potential gain exceeds the potential loss. This is the classic "cut losses short and let profits run" argument. And any numbskull can be right more than a quarter of the time right? So why aren't we all rich?
After trading currencies for a while in , I figured out what the problem was. A tight stop and a wide target will tend to make you wrong a lot simply because it's easier for the stop to get hit. On the other extreme, suppose you decide that you like to have a lot of winning trades, so you place very wide stops and very close price targets.
Fine, now you'll win a lot of the time but the amounts will be small. And one loss, although uncommon, will tend to wipe out many little wins. So no matter where you are on the "trading setup" spectrum, wide stops and tight targets, tight stops and wide targets, or any combination in between, statistically it ends up being a wash. There is no intrinsic "edge" in any given trading setup scheme, including "cutting losses short and letting profits run.
Getting a real statistical edge requires that you can identify situations in which the price tends to move in such a way that you can set up trades which have a positive expected return. Expected return is just the percentage of wins multiplied by the win amount, minus the percentage of losses multiplied by the loss amount.
An example will make this clearer. Now even though this only happens less than half the time, it still allows you to set up trades with a positive expected return. The expected return is:. So on the average, you can expect to get 4 pips per trade using this strategy, even though you lose most of the time!
But remember that this whole example is predicated on the knowledge that a positive crossover of the 20 day moving average tends to skew the expected return in your favor. That's your edge in this example. Percival has a degree in Civil Engineering from Northeastern University, and has worked as a Registered Representative and trading instructor at Fidelity Investments. Forex Day Trading Signals Indicator. Trading Tutorials Metatrader 4 Tutorials.