Yeah, I kind of did @GraHal, so many things to look at and test! I know it’s not a “pancea” as you put it and in fact, one of my generic Univ Osc systems (set at -0.8/0.8, bandedge =100) performed far better than the one, two or three ML algo system versions, (I might post that example and see if anyone can figure out why), but it is definitely a highly useful addition to the existing PRC codes that are on this site.

I had a lot of thoughts about it, even as writing this now I just thought, what if it was applied to Money Management position sizing? Would anyone like to have a look at that?

So on Friday night, having run the ML system with two algos (for Universal Oscillator threshold, individual Long and Short entries (the Bandedge was static and set to 100)) and the ML system with 3 algos which also optimised the Bandedge too as well as the entry thresholds, and then tested them together on Coffee, pls see image, this time ML x2 performed far better that the ML x3.

So…. my thought was… @Juanj, is there a way to put both ML2 and ML3 codes in the same system and then have them “fight it out,” or self optimise and find the better of the two systems (ML2 and ML3)? Perhaps the two systems switch and alternate back and forth, much like the self optimised variables selected in these ML algos? It would kind of be like having a backup plan in case one of the two systems performs poorly. If Juanj is busy, can anyone else think of a way that could be done?

As for performance metrics that Juanj mentioned, can anyone code Sharp or Sortino Ratios to be included in the ML code? Here’s a copy and paste from Van Tharp’s page on he performance metrics subject:

System Performance, Part IV

A ratio I like to use is the average annual percentage gain divided by the maximum draw down. This gives us a ratio of how much we make per year divided by how much we would be down at any time during the year. Or in simple terms: How much will I have to risk losing in order to generate my average returns? Any ratio of that is less than 2:1 is suspect (do you really want to risk a 50 percent draw down to make a 50% gain?).

Industry standard performance measures. Let’s close by looking at two composite numbers that many money managers use to measure their performance:

1. Sharpe Ratio: (system rate of return – risk-free rate of return) / standard deviation of system returns.

The Sharp Ratio measures risk to reward by giving the returns of the system as a ratio to its standard deviation. If the system has very constant returns, it will have a high Sharpe Ratio. A system with returns that vary greatly period-to-period will have a lower Sharpe Ratio.

2. Sortino Ratio: One problem with the Sharpe Ratio is that it penalizes a system for a big up month or “good volatility”. The Sortino Ratio attempts to overcome this issue by dividing the same risk-adjusted rate of return used in the Sharpe Ratio by only the negative deviation or “bad volatility” (the downside semi-variance).

https://www.vantharp.com/trading/system-performance-2/