Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers
The paper develops a novel realized matrix-exponential stochastic volatility model of multivariate returns and realized covariances that incorporates asymmetry and long memory (hereafter the RMESV-ALM model). The matrix exponential transformation guarantees the positivedefiniteness of the dynamic co...
| Autores: | , , |
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| Tipo de recurso: | informe técnico |
| Fecha de publicación: | 2016 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/27598 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/27598 |
| Access Level: | acceso abierto |
| Palabra clave: | C22 C32 C58 G32 Matrix-exponential transformation Realized stochastic covariances Realized conditional covariances Asymmetry Long memory Spillovers Dynamic covariance matrix Finite sample properties Forecasting performance. Econometría (Economía) 5302 Econometría |
| Sumario: | The paper develops a novel realized matrix-exponential stochastic volatility model of multivariate returns and realized covariances that incorporates asymmetry and long memory (hereafter the RMESV-ALM model). The matrix exponential transformation guarantees the positivedefiniteness of the dynamic covariance matrix. The contribution of the paper ties in with Robert Basmann’s seminal work in terms of the estimation of highly non-linear model specifications (“Causality tests and observationally equivalent representations of econometric models”, Journal of Econometrics, 1988, 39(1-2), 69–104), especially for developing tests for leverage and spillover effects in the covariance dynamics. Efficient importance sampling is used to maximize the likelihood function of RMESV-ALM, and the finite sample properties of the quasi-maximum likelihood estimator of the parameters are analysed. Using high frequency data for three US financial assets, the new model is estimated and evaluated. The forecasting performance of the new model is compared with a novel dynamic realized matrix-exponential conditional covariance model. The volatility and co-volatility spillovers are examined via the news impact curves and the impulse response functions from returns to volatility and co-volatility. |
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