But what a grand title for the article!
So many encouraging claims in a completely empty strategy!
That’s an interesting question. In that case, why not use `ollama`, as you do in some of your other Python code? Wouldn’t that work well? Thank you for your attention.
Thank you, a very interesting article. I’m studying this material myself, as well as this trading approach based on discussions involving AI agents and decision-making by senior traders....
Profitable trades are possible with this trading approach… and, again, you can incorporate the news… and trade on the news… Ollama + Cursor + AI agents and that’s it!!! )
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Check out the new article: How to Set Up an AI Hedge Fund in MetaTrader 5.
You run dozens of population-based optimizers on the same test bench and see a neat leaderboard. The problem is that some of these wins do not reflect the algorithm’s true search power: a high score may arise not from an ability to find the optimum, but from a match between the geometry of the algorithm’s steps and the geometry of a specific test function. A maximum located on the boundary, at the center, or near the diagonal of the normalized space gives certain classes of methods a systematic advantage.
In this article, we formalize this risk — especially the “diagonal effect” — provide a measurable diagnostic criterion, and show how to remove structural advantages from a benchmark set. After reading this, you will get specific tools rather than an abstract diagnosis: a rule for checking the position of an extremum, a procedure for verifying raw extrema (VerifyExtremes.mq5), and an example of practical correction of test functions.
Author: Yevgeniy Koshtenko