New Heavy Models for Fat-Tailed Realized Covariances and Returns
Bibliographic Data
| ID | 19419652 |
|---|---|
| Authors | Anne Opschoor (0000-0002-2908-2260, Department of Finance, Vrije Universiteit Amsterdam and Tinbergen Institute, 1081 MS Amsterdam, The Netherlands ()), Pawel Janus (UBS Asset Management, Zürich, Switzerland ()), André Lucas (0000-0003-2807-1102, Department of Finance, Vrije Universiteit Amsterdam and Tinbergen Institute, 1081 MS Amsterdam, The Netherlands ()), Dick Van Dijk (0000-0002-1880-204X, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute, 3062 PA Rotterdam, The Netherlands ()) |
| Year | 2018 |
| Volume | 36 |
| Issue | 4 |
| Pages | 643-657 |
| Publication date | 2018-10-02 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07350015.2016.1245622 |
| OpenAlex | W2530684420 |
| Language | EN |
| Citations received | 3 |
| References cited | 37 |
We develop a new score-driven model for the joint dynamics of fat-tailed realized covariance matrix observations and daily returns. The score dynamics for the unobserved true covariance matrix are robust to outliers and incidental large observations in both types of data by assuming a matrix-F distribution for the realized covariance measures and a multivariate Student's t distribution for the daily returns. The filter for the unknown covariance matrix has a computationally efficient matrix formulation, which proves beneficial for estimation and simulation purposes. We formulate parameter restrictions for stationarity and positive definiteness. Our simulation study shows that the new model is able to deal with high-dimensional settings (50 or more) and captures unobserved volatility dynamics even if the model is misspecified. We provide an empirical application to daily equity returns and realized covariance matrices up to 30 dimensions. The model statistically and economically outperforms competing multivariate volatility models out-of-sample.
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| Citations per year | 1 |
|---|---|
| Citation span | 2023 - 2026 (4) |
| Highly cited | No |