Chinese Stock Market Return Predictability: Adaptive Complete Subset Regressions

被引:4
|
作者
Chen, Keqi [1 ]
Chen, Rui [2 ]
Zhang, Xueyong [2 ]
Zhu, Min [3 ]
机构
[1] Tsinghua Univ, PBC Sch Finance, Beijing, Peoples R China
[2] Cent Univ Finance & Econ, Sch Finance, 39 South Coll Rd, Beijing 100081, Peoples R China
[3] Queensland Univ Technol, Sch Business, Brisbane, Qld 4001, Australia
关键词
Chinese stock market; Forecast combination; Out-of-sample predictability; EQUITY PREMIUM PREDICTION; INVESTOR SENTIMENT; NESTED MODELS; FORECASTS; ACCURACY; TESTS; COMBINATION; SAMPLE;
D O I
10.1111/ajfs.12152
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This paper proposes a new combination framework to explore the Chinese stock market return predictability. While most well-known predictor variables and simple combinations fail to beat the historical average benchmark, our adaptive complete subset regressions deliver statistically and economically significant out-of-sample performance. The subset, in which each regression includes five predictors, produces a significant statistic of 8.00% for January 2006 to September 2014. A mean-variance investor who uses the adaptive subset regressions forecasts, instead of the historical average forecasts, can obtain sizable utility gains of 7.60% per annum. The results of our paper suggest that there is significant predictability in the Chinese aggregate stock market portfolio.
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页码:779 / 804
页数:26
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