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Publicação
Asset allocation using machine learning
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Autores
Orientador(es)
Resumo(s)
This paper,Asset Allocation using Machine Learning, proposes a two step model,
forecasting rst volatility through an GJR-GARCH model and using a Support Vec-
tor machine to do the investment decision between the market portfolio and a risk
parity portfolio. Besides the volatility forecast, the Support Vector Machine is
based on economic, price, fundamental and sentiment data. It manages to outper-
form both the market (S&P 500) and a risk parity portfolio in terms of returns and
risk adjusted returns.
Descrição
Palavras-chave
Support vector machine Asset allocation Risk parity Volatility forecast