2026-06-28T10:32:15Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/275982023-08-11T07:24:12Zcom_20.500.14352_14col_20.500.14352_17
Docta Complutense
author
Asai, Manabu
author
Chang, Chia-Lin
author
McAleer, Michael
2023-06-18T10:26:03Z
2023-06-18T10:26:03Z
2016
2341-2356
https://hdl.handle.net/20.500.14352/27598
https://www.ucm.es/icae
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.
eng
Atribución-NoComercial-CompartirIgual 3.0 España
Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers
technical report
URL
https://docta.ucm.es/bitstreams/8ecd85a3-ec62-42f9-a9e3-70107c224279/download
File
MD5
0a0b5ac95a60fddaa04d572d7c159471
337809
application/pdf
1615.pdf