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Volatility forecasting with Hybrid-LSTM models: Evidence from the COVID-19 period
Ao Yang
*
,
Qing Ye
,
Jia Zhai
*
Corresponding author for this work
Department of Finance
Xi'an Jiaotong-Liverpool University
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Social Sciences
Evidence
100%
Forecasting
100%
COVID-19
100%
Short-Term Memory
100%
Memory Model
100%
Performance
36%
Indexes
18%
Design
9%
Influence
9%
Markets
9%
Literature
9%
Testing
9%
Financial Market
9%
Attention
9%
Parameter
9%
Construction
9%
Time Series
9%
USA
9%
Risk Management
9%
Economics, Econometrics and Finance
Volatility
100%
Stock Index
28%
Financial Market
14%
Risk Modeling
14%
Management
14%
Financial Risk
14%
Time Series
14%
Mathematics
Forecasting
100%
Samples
28%
Modeling
14%
Time Series Model
14%
Estimated Parameter
14%
Input Value
14%