嵌入GARCH波动率估计的B1ack-Litterman投资组合模型

doi:10.16381/j.cnki.issn1003-207x.2018.06.003

摘要/Abstract

摘要： 在B1ack-Litterman投资组合模型中，为了更有效地估计风险资产的期望收益和波动率，引入了投资者的主观观点，这种处理确实能提高均值-方差投资组合模型的性能。但是在实践中，如何度量投资者观点成了另一个难题。为了克服这一困难，我们将GARCH波动率估计嵌入到B1ack-Litterman模型中，通过使用GARCH模型的预测能力来替代投资者主观观点，从而获得一个新的投资决策模型。作为应用，分别考虑了国内外真实市场数据测试情形，通过实证结果发现，嵌入了GARCH波动率估计后，Black-Litterman模型的性能可进一步得到很好提高，样本外平均收益率、波动率和夏普比等指标，均要好于一些传统模型。

关键词: Black-Litterman投资组合模型, GARCH模型, 波动率估计

Abstract: The investor's subjective view is the key factor in B1ack-Litterman portfolio model and can improve the performance of the mean-variance portfolio. But, in practice, it is found that the opinions of investors are difficult to measure and compute.To overcome this difficulty, GARCH model is embedded to B1ack-Litterman model. The volatility prediction of GARCH model is used to estimate the paramaters in B1ack-Litterman model. Specially, we summary as follows.
Methods:In order to estimate the parameters of subjective views of investors, GARCH model is used to estimate the views' vectors and subjective volatility by the following predicting equation:

with all coefficients known.
Data:Two market data sets are considered. One is from China A share market, in which we take SSE 380 Index, and the portfolio consists of 10 different indices from SSE 380 Index. The data is from Jan 4^th 2005 to Dec 31^st 2016. Another is from US market, in which three indices, 10 Industry portfolio, 17 Industry portfolio and 25 Indusrty portfolio, are chosen, and all data is from French Library data.
Results:Comparisions with mean-variance model and BL model with modified by Idzorek(2002) are considered. Our numerical results show that (1) The BL model embedded GARCH can reduce the volatility of portfolio and obtain the smallest volatility among three models, (2) The largest Sharpe ratio can be obtained by the proposed model, and (3) the cumulative return (wealth) is highest among three model for the same investment period.

Key words: Black-Litterman portfolio model, GARCH model, volatility estimation

中图分类号:

F830.59

凌爱凡, 陈骁阳. 嵌入GARCH波动率估计的B1ack-Litterman投资组合模型[J]. 中国管理科学, 2018, 26(6): 17-25.

LING Ai-fan, CHEN Xiao-yang. The B1ack-Litterman Portfolio Model Embedded GARCH to Estimate Volatility[J]. Chinese Journal of Management Science, 2018, 26(6): 17-25.

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