Application of Ensemble Learning for Views Generation in Meucci Portfolio Optimization Framework

Review of Business and Economics Studies Volume 1, Number 1, 2013

11 Pages Posted: 10 Sep 2014  

Alexander Didenko

Finance University under the Government of the Russian Federation

Svetlana Demicheva

Government of the Russian Federation - Financial University (Moscow Branch)

Date Written: September 1, 2013

Abstract

Modern Portfolio Theory assumes that decisions are made by individual agents. In reality most investors are involved in group decision-making. In this research we propose to realize group decision-making process by application of Ensemble Learning algorithm, in particular Random Forest. Predicting accurate asset returns is very important in the process of asset allocation. Most models are based on weak predictors. Ensemble Learning algorithms could significantly improve prediction of weak learners by combining them into one model, which will have superiority in performance. We combine technical fundamental and sentiment analysis in order to generate views on different asset classes. Purpose of the research is to build the model for Meucci Portfolio Optimization under views generated by Random Forest Ensemble Learning algorithm. The model was backtested by comparing with results obtained from other portfolio optimization frameworks.

Keywords: Random Forest, Ensemble Learning, Meucci portfolio optimization, fundamental analysis, technical analysis

Suggested Citation

Didenko, Alexander and Demicheva, Svetlana, Application of Ensemble Learning for Views Generation in Meucci Portfolio Optimization Framework (September 1, 2013). Review of Business and Economics Studies Volume 1, Number 1, 2013. Available at SSRN: https://ssrn.com/abstract=2493362

Alexander Didenko (Contact Author)

Finance University under the Government of the Russian Federation ( email )

Leningradsky avenue, 49
Moscow, 125993
Russia

Svetlana Demicheva

Government of the Russian Federation - Financial University (Moscow Branch) ( email )

Leningradsky Prospect, 49
Moscow
Russia

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