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The Application in the Portfolio of China's A-share Market with Fama-French Five-Factor Model and the Robust Median Covariance Matrix

机译:Fama-French五因素模型和鲁棒中值协方差矩阵在中国A股市场投资组合中的应用

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In the traditional portfolio model, investors calculate the expected return of assets and the covariance matrix for optimal asset allocation. This paper divides market sentiment period into three states and selectes the securities in the Chinese stock market to construct portfolios. We implement both the Fama-French five-factor model and the robust median covariance matrix approach for predicting the expected return of the selected stocks and portfolio optimization respectively. Then we compare the performance of the portfolio constructed by the Fama-French three-factor model with that by the traditional covariance matrix in different market sentiment periods. The empirical results indicates that the performance of the portfolio constructed by the Fama-French five-factor model is more sensitive to the fluctuation of stock market sentiment, and that the robust median covariance matrix approach tends to have relatively stable portfolio return, while ineffective in the bull market. The main contribution of this paper is having empirically tested different model combinations in portfolio theory using the data of Chinese market where market sentiment has unique impact. To some extent, this paper provides a reference to the portfolio strategy.
机译:在传统的投资组合模型中,投资者计算资产的预期回报率和协方差矩阵以优化资产配置。本文将市场情绪期分为三个状态,并选择中国股市中的证券来构建投资组合。我们同时实施了Fama-French五因子模型和稳健的中位数协方差矩阵方法,分别用于预测所选股票的预期收益和投资组合优化。然后,我们比较了Fama-French三因素模型和传统协方差矩阵在不同的市场情绪时期构建的投资组合的绩效。实证结果表明,由Fama-French五因素模型构建的投资组合的绩效对股票市场情绪的波动更为敏感,而稳健的中值协方差矩阵方法往往具有相对稳定的投资组合收益,而在牛市。本文的主要贡献是使用市场情绪具有独特影响力的中国市场数据,对投资组合理论中的不同模型组合进行了经验检验。在某种程度上,本文为投资组合策略提供了参考。

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