E!12894 An advanced investment tool based on machine learning and big data

The main objective of the project was to provide the capability of the most efficient mechanism for investment asset portfolio optimization and risk control with improved long-term investment performance by applying the latest advances in Artificial Intelligence (AI). The latest developments in machine learning, particularly reinforcement learning, are much more advanced than the methods available 3-4 years ago. Adapting these methods has allowed us to achieve better investment results for the participating SMEs. A secondary objective was to train people on the latest technologies in machine learning, as well as to disseminate and stimulate research in this field in Europe. The main result of the project is a platform for portfolio optimization and risk control in global markets. It has been complemented with a visualization tool that helps investors make more informed investment decisions. Advanced machine learning methods were implemented to offer small and medium enterprises, investment companies, pension funds, retail investors, large enterprises and even government agencies a complete solution to support their asset portfolio, optimization and protection against unexpected financial events (crisis). Methods and algorithms were also incorporated into the inbestMe Robo Advisor platform, bringing the latest AI advances to the retail investor platform.

We have developed a highly innovative solution for investment firms already using, or interested in using, advanced quantitative methods in asset management. It builds on recent advances in machine learning (ML) and reinforcement learning (RL), which have never been applied to solve complex quantitative finance problems. We positively verified the level of accuracy for time series prediction (10% improvement over reference methods), which clearly proves the breakthrough potential of advanced deep learning methods in investment management. The platform has been tested on real investments, proving the level of prediction accuracy and long-term rate of return, which showed low correlation with the underlying markets affected by the COVID-19 crisis. The Forecasting Module component can be used not only for financial time series forecasting, but also for time series forecasting in other industries such as transportation, sales, energy consumption, climate risk analysis and many others.

The AI Investment platform will be new solution offered in the financial market as Software as a Service. The new solution will be created based on the results of the proof of concept prepared in the project. AI Investment will use the state-of-the-art machine learning (ML) algorithms: both in financial time series prediction (multi-head neural networks based on combination of different types of networks: Wavenet, ResNet, Dilated LSTM, SFM, Differentiable Neural Computer and other; and reinforcement learning: differentiable neural trees, MCSnet, Alpha Zero, multi agent cooperation, meta learning and many more. Unlike some available solutions, AI Investment will use the potential of the latest achievements of machine learning and learn optimization methods and their parameters from data instead of deterministic work performed by the analysts that is optimized in the data mining process. Furthermore, the AI Investment platform will be capable of recursive self-improvement.