References
- Aielli, G. P. (2013). Dynamic conditional correlation: On properties and estimation, Journal of Business & Economic Statistics, 31, 171-194.
- Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, 31, 307-327. https://doi.org/10.1016/0304-4076(86)90063-1
- Bollerslev, T. (1990). Modelling the coherence in short-run nominal exchange rates: A multivariate gener- alized ARCH model, The Review of Economics and Statistics, 72, 498-505. https://doi.org/10.2307/2109358
- Bollerslev, T., Engle, R. F. and Wooldridge, J. M. (1988). A capital asset pricing model with time-varying covariances, The Journal of Political Economy, 96, 116-131. https://doi.org/10.1086/261527
- Dajcman, S. and Festic, M. (2012). Interdependence between the Slovenian and European stock markets-a DCC-GARCH analysis, Ekonomska Istrazivanja, 25, 379. https://doi.org/10.1080/1331677X.2012.11517513
- Ding, Z., Granger, C. W. and Engle, R. F. (1993). A long memory property of stock market returns and a new model, Journal of Empirical Finance, 1, 83-106. https://doi.org/10.1016/0927-5398(93)90006-D
- Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom in ation, Econometrica: Journal of the Econometric Society, 45, 987-1007.
- Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregres- sive conditional heteroskedasticity models, Journal of Business & Economic Statistics, 20, 339-350. https://doi.org/10.1198/073500102288618487
- Engle, R. F. and Kroner, K. F. (1995). Multivariate simultaneous generalized ARCH, Econometric Theory, 11, 122-150. https://doi.org/10.1017/S0266466600009063
- Glosten, L. R., Jagannathan, R. and Runkle, D. E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks, The Journal of Finance, 48, 1779-1801. https://doi.org/10.1111/j.1540-6261.1993.tb05128.x
- Kim, W. H. (2014). Time-varying comovement of KOSPI 200 sector indices returns, CSAM (Communications for Statistical Applications and Methods), 21, 335-347.
- Marcucci, J. (2005). Forecasting stock market volatility with regime-switching GARCH models, Studies in Nonlinear Dynamics & Econometrics, 9, 1-55.
- Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach, Econometrica: Journal of the Econometric Society, 59, 347-370. https://doi.org/10.2307/2938260
- Orskaug, E. (2009). Multivariate DCC-GARCH model with various error distributions, Working paper, Norwegian Computing Center, SAMBA/19/09.
- Pagan, A. R. and Schwert, G. W. (1990). Alternative models for conditional stock volatility, Journal of Econometrics, 45, 267-290. https://doi.org/10.1016/0304-4076(90)90101-X
- Schwert, A. (2010). Crisis period forecast evaluation of the DCC-GARCH Model yang ding, Doctoral dissertation, Duke University Durham.
- Sener, E., Baronyan, S. and Menguturk, L. A. (2012). Ranking the predictive performances of value-at-risk estimation methods, International Journal of Forecasting, 28, 849-873. https://doi.org/10.1016/j.ijforecast.2011.10.002
- Tsay, R. S. (2010). Analysis of Financial Time Series, Wiley.
- Xu, C. and Chen, H. (2012). Measuring portfolio value at risk, Working paper, Department of Economics, School of Economics and Management, Lund University.