| Full text | |
| Author(s): |
Trucios, Carlos
[1, 2]
;
Mazzeu, Joao H. G.
[3]
;
Hallin, Marc
[4, 5]
;
Hotta, Luiz K.
[3]
;
Valls Pereira, Pedro L.
[2]
;
Zevallos, Mauricio
[3]
Total Authors: 6
|
| Affiliation: | [1] Univ Fed Rio de Janeiro, Fac Business Adm & Accounting, Rio De Janeiro - Brazil
[2] Sao Paulo Sch Econ, FGV, Sao Paulo - Brazil
[3] Univ Estadual Campinas, Dept Stat, Sao Paulo - Brazil
[4] Univ Libre Bruxelles, Dept Math, Brussels - Belgium
[5] Univ Libre Bruxelles, ECARES, Brussels - Belgium
Total Affiliations: 5
|
| Document type: | Journal article |
| Source: | JOURNAL OF BUSINESS & ECONOMIC STATISTICS; DEC 2021. |
| Web of Science Citations: | 0 |
| Abstract | |
Based on a General Dynamic Factor Model with infinite-dimensional factor space and MGARCH volatility models, we develop new estimation and forecasting procedures for conditional covariance matrices in high-dimensional time series. The finite-sample performance of our approach is evaluated via Monte Carlo experiments and outperforms the most alternative methods. This new approach is also used to construct minimum one-step-ahead variance portfolios for a high-dimensional panel of assets. The results are shown to match the results of recent proposals by Engle, Ledoit, and Wolf and achieve better out-of-sample portfolio performance than alternative procedures proposed in the literature. (AU) | |
| FAPESP's process: | 18/04654-9 - Time series, wavelets and high dimensional data |
| Grantee: | Pedro Alberto Morettin |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 16/18599-4 - Modeling and forecasting volatility of high dimensional financial series |
| Grantee: | Carlos Cesar Trucios Maza |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 18/03012-3 - Robust dynamic dimension reduction techniques for volatilities |
| Grantee: | Carlos Cesar Trucios Maza |
| Support Opportunities: | Scholarships abroad - Research Internship - Post-doctor |