Title: Optimizing financial technical indicators: Evolutionary learning approach in optimizing advertise learning experts

Abstract:

Within the framework of expert advice learning strategies, one needs to have good enough experts in terms of performance, causality, and stability. Indeed, an expert advice online learning algorithm is an algorithm, which deduces its prediction from the advice of its experts. Having well-performing experts increases the performance of our algorithm; therefore, it is necessary to improve their performance. In order to achieve this objective, we were able to create an objective function, which reflects the performance of our experts and we created a causality inspired by brain neurons causality. In the case of our experts (technical indicators), we cannot determine with certainty the regularity of our objective functions which differs from one expert to another. This lack of information on regularity and a large number of functions to be optimized has pushed us to see beyond classical convex optimization and to think of a type of optimization, evolutionary learning.

Biography:

Chaouachi Wassim has completed his Master's degree at the age of 24 years from Ecole Normale supérieure and Paris-Dauphine University in Applied Mathematics and Machine Learning. He is a Quantitative Portfolio Manager at one of the best hedge funds in Europe. He is Co-Founder and CEO of Richmond Analytica, a company providing AI-based investment strategies in the cryptocurrencies universe