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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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