The MetricAnalyzer is a free tool to find good strategies

Hello, at this point I would like to introduce you to my metrics analyzer. This tool can help you create more successful strategies with StrategyQuantX. This is the first version of the metrics analyzer. I will do additional update next week so that the installer will install a version and a complete demo will also be installed. This makes it even easier to get to know everything. The metrics analyzer is freeware, you can use the tool freely. The metric analyzer is a free tool that offers some simple features for analyzing the strategy generator. I have found that the most important thing when generating strategies is the generator. If it’s good, then the strategies will work. The metrics analyzer is not intended to compete with StrategyQuantX. I hope that the SQX team will integrate some features of the analyzer into a similar improved version in one of the next versions of SQX. I don’t have that much time to realize all possible ideas. The tool should also serve as a suggestion for what else you could do.

Next week I will integrate a demo into the installer so that you can get to know how the metric analyzer works even more easily.
I am also aware that the metrics analyzer may over-optimize too much. I already have an idea of ​​what I’m going to integrate. If you want, you can try out version 0.1.4.3 (without demo mode). I have attached the current documentation here. You can download the Metric Analyzer from my gmx-webspace.

https://c.gmx.net/@329881123612003410/AXjh2A75Rm-xTLKwpAVWSA

thomas

I updated the Metrikanalyser.

1) I added a Demomode installation for easier understanding this all

2) I updated the Installer

thomas

I am working on the next update for the Metrikanalyser, integrating a small robustness test. I will test the top 100 Metrikrules with unseen data, allowing you to review the results and decide whether to adopt the discovered rules.

Currently, there are only 77 strategies. I need to repeat this process with 10,000 or more strategies. Each set of unseen data constitutes 10% of all data, allocating 50% for generation and 50% for testing with unseen data.

I plan to update the Metrikanalyser with this feature in the coming days.

For the foreseeable future, I do not intend to update the Metrikanalyser. Instead, I will familiarize myself with Weka and explore various learning models. I believe this approach is more efficient than trying to reinvent the wheel.

thomas