Montecarlo statistical mode parameter optimization

I was wondering if i can access to the montecarlo generated curves of a strategy test and all the parameter values for each one of them.

The idea is take the best 'n' montecarlo curves, extract the parameter values associated and then compute the statistical mode for each parameter.

We would take this parameter modes as the supposedly most robust ones.

¿Has anyone tried this? ¿Is it worth doing it? ¿How could i do it with zorro and other tools?

Thanks.

Monte Carlo just randomly shuffles the order of trades from a backtest to see what effect it has on drawdown and profit. It’s an evaluation tool.

I understand that, but i´ve seen this idea mentioned on an article on a blog and i wanted to know if it´s feasible in zorro.

Anyway, when the author of the article releases the second part, i´ll see how exactly this idea works and if it has any sense.

AndrewAMD, in your opinion, ¿What´s the best approach for selecting good robust parameters? ¿Is it enough with the zorro approach?.

Thanks.

May I have a link to the article?

Of course.

This is where i first saw this idea mentioned at the end of the post (spanish article):
https://www.rankia.com/blog/oscar-cagigas/4101414-cual-mejor-ratio-optimizacion

In short, the author performs a comparison of different ratios for obtaining system parameters, and he concludes that in the second part, he will apply the statistical mode of a given ratio over the whole montecarlo generated curves.

This is another article with a more detailed explanation, adding some MQ5 code:
https://www.mql5.com/en/articles/4347

Looking forward for your reply.

Bye.

I have some thoughts, in no particular order:

* The first article does not talk about monte carlo at all, from what I can tell.
* I wouldn't know what the "best" optimization method is, I simply use the most practical ones. Currently, this would be the default Zorro optimization method.
* Perhaps the method described in the second article can be a useful technique, it might be worthy of experimentation.
* One other optimization method I like is described in Trading Systems by Jaekle and Tomasini. When they initially design a trading system, they use a dual-parameter brute force optimization to produce various 3D plots, in order to identify stable profitable parameter regions. This helps with the final design of the script. I have been able to produce such 3D plots by exporting trade data CSV's and making 3d plots with the plotly R package. (Anyways, this has nothing to do with statistics.)

Hello.

* About the first article, when the author says he will consider the statistical mode of the best 100 equity curves, i interpret he is obtaining these curves from montecarlo analysis. Anyway, when he publishes the second part, i will tell you.

* I also think that Zorro style is the simplest and most practical method for choosing parameters, but one always like to experiment new things.

* I will have a look to the book you have told me.

Thank you for your reply.