I generally avoid optimizing for philosophical reasons. Traders always care about the bottom line. The question people inevitably ask is “how much does the EA make?” Although understandable, I believe that such a black and white concern does not model real life.
In reality, people care very much not just about how much they make. They also care a great deal about how they make it. The difference is that they know the former and tend to ignore the latter. It’s the primary reason why traders cannot stick to successful systems. They tend to walk away whenever their personal pain threshold is exceeded.
Optimizing for balance is extremely risky because it ignores one critical factor: it’s entirely possible that the optimal strategy for a given time period is a random outcome. Short of nose diving to zero, it is very difficult to conclude a strategy’s merit solely on the basis of return.
More importantly, the process of parameter optimization implies that a magical combination of settings exists that’s just begging to get discovered. It’s plain fallacy to believe that using a 50 period moving average really makes a critical difference compared to a 51 period moving average. Yet I see traders all the time exhausting every possible outcome looking for historical sweet spots.
One test that I ran several years ago, and I wish that I had kept the screenshots, was to write a strategy that entered and exited the market purely at random. The only rule that I retained control over was the frequency.
The random process blew my mind. It was ultimately in a good way, but I realized that many of the strategies and expert advisors that I reviewed previously and deemed “not bad” were indeed truly worthless. 20 independent trials wound up with 20 different outcomes. Excluding commissions, most of the strategies neither made nor lost money. Most of the random trades exhibited wild round trips. Profits might run up 10%, decline to -10%, then settle near a 0% return. The profitable strategies stood out most in my mind. One or two of them resembled ATM machines that churned out consistent profits on most trades.
The easiest way to limit the risk of using random parameters is to look at the underlying indicators used in the decisions. Price crossing above or below a moving average, for example, exhibits a genuine entry and exit efficiency that NinjaTrader can evaluate (70% if used as a range bound exit strategy. Entries are random). Moving averages crossing one another, however, show an entry and exit efficiency of 50%. Using that metric, I confidently chuck that type of rule out the window.
If you’ve performed an analysis on the entry and exit efficiency and found something greater than 55%, then at that point optimizing is at least a less bad pursuit. I confess to using it in the past to look for hotspots on potential parameter settings. If you decide to go down that road, it’s important to consider them as suggestions to evaluate rather than a holy grail.