Feeling lucky?

My foretelling of the US non-farm payroll unfolded broadly in line with what I thought might happen. Was my correct prediction just pure luck or a sign of some masterful trading skill? Are you a good trader or should you test your “skills” at a bitcoin casino?

Before I tackle that question I’d like to quickly recap how I handled the events of Friday’s NFP release.

Price didn’t make it into the lower half of Q3 during Friday’s London session; instead it just hung around the 1.3550 level. That was good enough for me and I entered a Q3 position at 1.3561.

The headline NFP employment change number was only 88,000 with a downward revision for the previous two months. These were the first downward revisions in quite a long time. Coupled with the slightly weaker than expected headline number we saw a pop in the euro to just above 1.36. Some profit taking took things to just below 1.36 again, but price stablised and remained at that level going into the weekend.

Both the Fed and the ECB will make interest rate decisions this coming week. How I trade this week will depend on how price plays out in the run-up to these announcements. If the euro stays stong, well in the 1.36 range, then I’m going to be wary of a ’sell the fact’ scenario unfolding if the ECB does raise rates this week. On the other hand, if the euro fades back down to 1.35 or below then I think that a ECB rate hike could easily bounce the euro back up to its recent highs and maybe even into 1.37 territory.

With my quick market analysis out of the way, let me answer my initial question of whether my prediction for the NFP release was luck or skill.

I don’t really see it as either to be honest. What I wrote in my last post was more a plan of action. I reckoned that there was a good chance that the NFP would not be a great number. No surprises there, as neither did any of the economists who were polled to generate the consensus number. A duff number after a week of mildly positive US data offered a good probability setup that price would venture back up above 1.36.

The key phrase there is ‘good probability setup’. I didn’t know for certain, nor did I have any concrete expectations, that price would go back up on an in-line or slighly weaker than expected data release. I did feel that there was a better than 50-50 chance that it would, based on my own observations and research. Someone else with a different viewpoint could easily have reached the opposite conclusion. Those people who do reach those opposing viewpoints are an absolute necessity in the trading world. They’re the people that take the opposite side of your trade.

I am currently reading Way of the Turtle by Curtis Faith, who was one of the original Turtle traders. While the book primarily takes the approach of a mechanical or systematic trader, he offers many valuable insights into the world of trading that any trader can learn from.

He dedicates a chapter to examining the four major sources of discrepancies that traders often find between their historical test results and what actually happens when they trade live. One of these four sources is the effect of randomness. How much of a role does pure random chance play?

Another way to answer my question at the beginning of this post is given by Curis Faith when he writes:

When you are looking at a short-term track record, you should realize that much of what you are seeing is attributable to luck. If you want to know whether a particular trader is one of the lucky average or one of the excellent few, you need to dig deeper than the track record and focus on the people behind the track record.

Good investors invest in people, not historical performance. They know how to identify traits that will lead to excellent performance in the future, and they know how to identify traits that are indicative of average trading ability. This is the best way to overcome random effects.