首页|Black-Litterman portfolio optimization based on GARCH-EVT-Copula and LSTM models
Black-Litterman portfolio optimization based on GARCH-EVT-Copula and LSTM models
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NETL
NSTL
Springer Nature
In constructing diversified portfolios, the investors might be interested in incorporating some quantifiable views or opinions. The Black-Litterman model is a useful approach to integrate investors' views into the Markowitz allocation model. In this paper we utilize a deep learning model to estimate the investors's views and use GARCH-EVT-Copula to model the dependence structure between stock market returns in a large portfolio. The findings show that the Black-Litterman model for portfolio optimization based on GARCH-EVT-Copula and LSTM (Long Short Term Memory) models gives better performances as compared with the traditional max-Sharpe and the original Black-Litterman portfolio problems.
NETL
NSTL
Springer Nature
