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Cross-sectional return dispersion and volatility prediction
Tianlun Fei
,
Xiaoquan Liu
, Conghua Wen
Department of Finance, Accounting and Economics
Research output
:
Journal Publication
›
Article
›
peer-review
10
Citations (Scopus)
29
Downloads (Pure)
Overview
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Dive into the research topics of 'Cross-sectional return dispersion and volatility prediction'. Together they form a unique fingerprint.
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Keyphrases
Volatility Prediction
100%
Return Volatility
100%
Return Dispersion
100%
Cross-sectional Dispersion of Returns
100%
Volatility Dynamics
33%
Generalized Autoregressive Conditional Heteroscedasticity (GARCH)
33%
Economic Gain
33%
Mean-variance Utility
33%
Volatility Forecasting
33%
Forecast Error
33%
Information Content
33%
Chinese Equity Markets
33%
Intraday Data
33%
Sample Analysis
33%
Stock Index
33%
Daily Data
33%
Industry Level
33%
Volatility Proxy
33%
GJR-GARCH Model
33%
Dispersion Measure
33%
HAR Model
33%
Alternative Markets
33%
Economics, Econometrics and Finance
Volatility
100%
Generalized Autoregressive Conditional Heteroskedasticity
50%
Industry
25%
Investors
25%
Stock Index
25%
Information Value
25%