New Strategy Development Process with Machine Learning / Neural Network

Specification

Hello

I would like to create my own strategy development process including a ML integration. There are tons of possibilites and I don't know which will fit the best for me.

Let's say I have one simple mean reversion strategy:
- Long: RSI under 30
- Short: RSI above 70
- Exits: RSI at 50

This is a simple strategy right? Now how could ML get integrated in this? I heard about classification (labelling the trades based on their past results) is a good approach. Do you have an idea where to start? I need a Machine Learning specialist which also have a degree in ML. I would like to create the strategy development process together including machine learnig / neural network. We look especially for time, price, volume and volatility. Are there other good features to include? Questions we need to answer:

  1. Which ML approach do we integrate and why? CatBoostClassifier, Classification, Regression, Clustering, HMM, FeedForward, etc.?
  2. How can we avoid an overfitted strategy?
  3. What's the step-by-step approach?

Keep in mind that I'm not a ML expert. I'm a beginner but have python and mql5 knowledge. In addition, we are actually two people which will code and create the strategy development process together.

I'm curious about your suggestion :-)



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