Realized BEKK-CAW Models
Author:
Affiliation:
1. Faculty of Economics , Soka University , Hachiōji , Japan
2. Department of Information Systems, Business Statistics and Operations Management , The Hong Kong University of Science and Technology , Clear Water Bay , Hong Kong
Abstract
Funder
Japan Society for the Promotion of Science
Publisher
Walter de Gruyter GmbH
Subject
Economics and Econometrics
Link
https://www.degruyter.com/document/doi/10.1515/jtse-2022-0009/pdf
Reference45 articles.
1. Asai, M., and M. McAleer. 2022. “Bayesian Analysis of Realized Matrix-Exponential GARCH Models.” Computational Economics 59: 103–23. https://doi.org/10.1007/s10614-020-10074-6.
2. Asai, M., and M. K. P. So. 2013. “Stochastic Covariance Models.” Journal of the Japan Statistical Scociety 43: 127–62. https://doi.org/10.14490/jjss.43.127.
3. Asai, M., and M. K. P. So. 2021. “Quasi-Maximum Likelihood Estimation of Conditional Autoregressive Wishart Models.” Journal of Time Series Analysis 42: 271–94. https://doi.org/10.1111/jtsa.12566.
4. Asai, M., R. Gupta, and M. McAleer. 2020. “Forecasting Volatility and Co-volatility of Crude Oil and Gold Futures: Effects of Leverage, Jumps, Spillovers, and Geopolitical Risks.” International Journal of Forecasting 36: 933–48. https://doi.org/10.1016/j.ijforecast.2019.10.003.
5. Asai, M., C. Chang, and M. McAleer. 2022. “Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Higher-Moment Spillovers.” Journal of Econometrics 227: 285–304. https://doi.org/10.1016/j.jeconom.2021.06.008.
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