期刊名称：International Journal of Statistics and Probability
印刷版ISSN：1927-7032
电子版ISSN：1927-7040
出版年度：2021
卷号：10
期号：1
页码：58
DOI：10.5539/ijsp.v10n1p58
出版社：Canadian Center of Science and Education
摘要：The Black-Litterman model combines investor’s personal views with historical data and gives optimal portfolio weights. In (Andrei & Hsu, 2020), they reviewed the original Black-Litterman model and modified it in order to fit it into a Bayesian framework, when a certain number of assets is considered. They used the idea by (Leonard & Hsu, 1992) for a multivariate normal prior on the logarithm of the covariance matrix. When implemented and applied to a large number of assets such as all the S&P500 companies, they ran into memory allocation and running time issues. In this paper, we reduce the dimensions by considering Bayesian factor models, which solve the asset allocation problems for a large number of assets. In addition, we will conduct sensitivity analysis for the confidence levels that the investors have to input.
