So far 2017 has been a slow year. Nine trades in total have been taken (see detail here) with five wins and four losses.
Doesn't sound like much does it? Let's explore a little deeper. For those nine trades the net profit is $937.50 per lot. Which equates to an expectancy of $104.17.
The update I want to discuss though has nothing to do with where the snapshot in time is right now. Automated trading, or trading in general is not a snapshot. It's a long term reversion to the mean. Success is a function of an insanely large sample size. A population.
A few months ago I wrote about win rates, Strategy Win Rate where I proposed that low win rates are often better than high win rates.
Though this may sound counterintuitive the math supports such a statement. And the reality behind focusing on high win rates is often a function of our limited psychology. Our disgust for dealing with losses. So if a high win rate can minimize losses why not go that route?
Here's why. Bottom line is winners are not allowed to "run." Even day traders, scalpers have the chance to let winners run.
In 2017 I changed my system to target bigger moves. And as stated above the net profit per lot is $937.50. The win rate with this system is around 60%.
Contrast that with a previous system where the win rate was closer to 70%. And how would that system have performed year to day? Profitable. But how much? $212.85 per lot ($23.65 expectancy). About one fifth of the current system.
This example I cite is only a snapshot. It too is not an end all that says I was right in making this switch. That move was based on five years of historical data. And then applying out of sample data for the prior four years to confirm I did not curve fit, etc.
But I like what I see so far in production. Today was a loss, I don't like losses. But it was just a snapshot. My current system can now make up for two losses with just one win. That was previously not the case.
The moral of the story? Don't be afraid of losses. Avoiding them may cost you money.