Ideas for Automating Naked Trading using ML Techniques

Walters Naked Trading strategy is centered around a concept of investor fatigue and how to detect when the current trend is exhausted  and is likely to reverse. I have not tested the strategy  but I think it provides a nice framework for a well bounded ML problem that could be useful for the Apply Machine Learning for Investing meetup group.

I watched this presentation during my mandatory exercise time yesterday. It seems like a well bounded but non-trivial way get started testing various ML ideas. I added my ideas about how to think about automating for ML below. Continue reading “Ideas for Automating Naked Trading using ML Techniques”

Stock recommendations engine with Machine Learning and AI based optimization

Introduction to Bayes analytic Stock recommendations engine

The stock recommendations engine delivers maximum stock trading profit by finding the subset of current buying opportunities which offer the highest probability of producing the desired profit.    It combines hundreds of statistical measurements with proprietary trading algorithms to deliver a high degree of accuracy and trading profits.     Advanced trading algorithms  allow the system to adjust trading recommendations throughout the day to adjust for changing market conditions. Continue reading “Stock recommendations engine with Machine Learning and AI based optimization”