Dynamic Model Averaging is a Bayesian model averaging method that extends static model averaging by allowing time-varying model probabilities and parameters through the incorporation of sequential updating mechanisms based on state-space models and filtering techniques.
67
Publications
5.5K
Citations
164
Authors
105
Institutions
Publications per year
2017–2026
28
Parents
Publications
67
Forecasting realized volatility in a changing world: A dynamic model averaging approach
Yudong Wang, Feng Ma, Yu Wei et al. · Journal of Banking & Finance · 2015 · 292 citations
1–5 of 67
Authors
164
- GK
5
h-index
- KD
5
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- RG
4
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- AE
3
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- YM
2
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1–5 of 164
Institutions
105
University of Warsaw
Warsaw, Poland
5 h-index
5 publications
176 citations
Tsinghua University
Beijing, China
4 h-index
21 publications
2K citations
University of Pretoria
Pretoria, South Africa
4 h-index
8 publications
398 citations
University of Washington
Seattle, United States
3 h-index
3 publications
606 citations
Southwest Jiaotong University
Chengdu, China
3 h-index
5 publications
753 citations
University of Strathclyde
Glasgow, United Kingdom
3 h-index
5 publications
1.1K citations
Aalborg University
Aalborg, Denmark
3 h-index
3 publications
150 citations
Konkuk University
Seoul, South Korea
2 h-index
2 publications
163 citations
1–8 of 105
Venues
- Journal of Hydrology
4 publications · 162 citations
4
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- SSRN Electronic Journal
Repository · 3 publications · 142 citations
3
h-index
- Journal of Forecasting
2 publications · 47 citations
2
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- Sustainability
2 publications · 32 citations
2
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- The North American Journal of Economics and Finance
2 publications · 76 citations
2
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1–5