The effects of investment horizon on the estimate of the systematic risk are first investigated by Brennan et al,(2012). In general, the true investment horizon is unknown. The empirical work will overestimate the coefficient of the systematic risk based on the observed horizon. The copula Bayesian estimation approach is proposed to get the posterior distribution of the coefficients of the system risk beta and the investment horizon ratio gama in the Fama-French three factor model. The potent problem of the traditional Bayesian estimation is that the assumption of normal likelihood function ignores some fluctuations such as high peak and fat tail relative to kurtosis and skewness, which have been frequently, reported in financial data analyses. The copula Bayesian approach instead of the traditional Bayesian estimation is built to consider the pattern of the data with the strong correlation and the non-normal distributions. The reason why the copula function is chosen is to fit the pattern of the data. In the empirical work,the interaction of the system risk and the investment horizon is analyzed in 25 portfolios from 150 different data. Compared with the U.S. data, the correlation of the systemic risk and investment horizon is negative, and the frequency of the true horizon is higher than observed one in China. With the increase of the size of the company, the effect of the investment horizon is obviously magnified. And the appearance leads to the estimation bias of the systemic risk.
ZHAO Ning, YU Fang-kun, YOU Shen, WANG Zhen-shuang
. Investment Horizon, System Risk Value and the Sensitive Effect[J]. Chinese Journal of Management Science, 2018
, 26(1)
: 72
-80
.
DOI: 10.16381/j.cnki.issn1003-207x.2018.01.007
[1] Brennan M J, Zhang Yuzhao, Capital asset pricing with a stochastic horizon[R]. Working Paper. University of California, 2012.
[2] 林建浩,李幸,李欢. 中国经济政策不确定性与资产定价关系实证研究[J]. 中国管理科学,2014,22(S1):222-226.
[3] 简志宏, 李彩云. 系统性跳跃风险与贝塔系数时变特征[J]. 中国管理科学, 2013,21(03):20-27.
[4] Longstaff F A. Temporal aggregation and the continuous-time capital asset pricing model[J]. Journal of Finance, 1989,44(4):871-887.
[5] Lee C F, Patro D K,Liu Bo. Functional forms for performance evaluation:Evidence from closed-end country funds[M]//Lee C F,Lee A C,Lee J. Handbook of quantitative finance and risk management, 2010:1523-1553.
[6] Handa P, Kothari S P, Wasley C. Sensitivity of multivariate tests of the capital asset-pricing model to the return measurement interval[J]. Journal of Finance, 1993, 48(4):1543-1551.
[7] Kamara A, Korajczyk R A, Lou Xiaoxia, et al. Horizon pricing[J]. Journal of Financial and Quantitative Analysis, 2015, 51(6):1769-1793.
[8] Darollesa S, Gourierouxb C. Conditionally fitted Sharpe performance with an application to hedge fund rating[J]. Journal of Banking & Finance, 2010, 34(3):578-593.
[9] Lina C, Liub Y. Genetic algorithms for portfolio selection problems with minimum transaction lots[J]. European Journal of Operational Research, 2008, 185(1):393-404.
[10] Lin W T, Chen Y H. Investment horizon and beta coefficient[J]. Journal of Business Research, 1990, 21(1):19-37.
[11] 杨宏林, 张兴全,多标度投资组合绩效度量非系统误差及校正[J]. 系统工程理论与实践, 2013, 33(9):2187-2194.
[12] 赵宁,Lin W T,孙雪卿,基于Copula贝叶斯估计的风险值行业差异[J]. 数学的实践与认识,2015, 45(10):17-27.
[13] 邓超, 陈学军, 基于多主体建模分析的银行间网络系统性风险研究[J]. 中国管理科学, 2016,24(01):67-75.
[14] Darollesa S, Gourierouxb C. Conditionally fitted Sharpe performance with an application to hedge fund rating[J]. Journal of Banking & Finance, 2010,34(3):578-593.
[15] Shih Y C, Chen S S, Lee C L, et al. The evolution of capital asset pricing models[J].Review of Quantitative Finance and Accounting 2014, 42(3):415-448.
