Multivariate Dynamic Intensity Peaks-Over-Threshold Models
- Author(s)
- Nikolaus Hautsch, Rodrigo Herrera Leiva
- Abstract
We propose a multivariate dynamic intensity peaks-over-threshold model to capture extremes in multivariate return processes. The random occurrence of extremes is modeled by a multivariate dynamic intensity model, while temporal clustering of their size is captured by an autoregressive multiplicative error model. Applying the model to daily returns of three major stock indexes yields strong empirical support for a temporal clustering of both the occurrence and the size of extremes. Backtesting value-at-risk and expected shortfall forecasts shows that the consideration of clustering effects and of feedback between the magnitudes and the intensity of extremes results in better forecasts of risk.
- Organisation(s)
- Department of Statistics and Operations Research, Research Network Data Science
- External organisation(s)
- Universidad de Talca, Center for Financial Studies
- Journal
- Journal of Applied Econometrics
- Volume
- 35
- Pages
- 248-272
- No. of pages
- 25
- ISSN
- 0883-7252
- DOI
- https://doi.org/10.1002/jae.2741
- Publication date
- 2019
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 502025 Econometrics, 502009 Corporate finance
- Keywords
- ASJC Scopus subject areas
- Economics and Econometrics, Social Sciences (miscellaneous)
- Portal url
- https://ucris.univie.ac.at/portal/en/publications/multivariate-dynamic-intensity-peaksoverthreshold-models(4a924f16-b3b1-443c-8fc3-58a41e83e436).html