A0507
Title: A modified VAR-deGARCH model for asynchronous multivariate financial time series via variational Bayesian inference
Authors: Shih-Feng Huang - National Central University (Taiwan) [presenting]
Wei-Ting Lai - National Central University (Taiwan)
Ray-Bing Chen - National Cheng Kung University (Taiwan)
Abstract: A modified VAR-deGARCH model is proposed, denoted by M-VAR-deGARCH, for modeling asynchronous multivariate financial time series with GARCH effects and simultaneously accommodating the latest market information. A variational Bayesian (VB) procedure is developed to infer the M-VAR-deGARCH model for structure selection and parameter estimation. Extensive simulations and empirical studies are conducted to evaluate the fitting and forecasting performances of the M-VAR-deGARCH model. The simulation results reveal that the proposed VB procedure produces satisfactory selection performances. In addition, empirical studies find that the latest market information in Asia can provide helpful information for predicting market trends in Europe and South Africa, especially when momentous events occur.
