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Antinoise in US equity markets
被引:1
|作者:
Cheng, Enoch
[1
]
Struck, Clemens C.
[1
]
机构:
[1] Univ Colorado, Dept Econ, Denver, CO 80210 USA
关键词:
Noise traders;
Behavioral economics;
Machine learning;
Asset pricing;
CROSS-SECTION;
CORRELATION-MATRICES;
FINANCIAL-MARKETS;
BEHAVIOR;
HERD;
PERFORMANCE;
INVESTMENT;
MODEL;
D O I:
10.1080/14697688.2021.1923789
中图分类号:
F8 [财政、金融];
学科分类号:
0202 ;
摘要:
There are many well documented behavioral biases in financial markets. Yet, analyzing U.S. equities reveals that less than 1% of returns are predictable in recent years. Given the high number of biases, why are returns not more predictable? We provide new evidence in support of one possible explanation. In the long-run, low correlations across signals that trigger biases may create sufficient antinoise which mutes more sizable patterns in returns. However, in the short-run, correlation spikes coincide with market volatility indicating that behavioral biases may become more visible during crises.
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页码:2069 / 2087
页数:19
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