Abstract
This study conducts careful interpretations of the model parameters from the full Baba-Engle-Kraft-Kroner (BEKK) model with asymmetric effects. This study also includes a case study, in which we interpret the full BEKK model parameter estimates from the empirical examinations using French and German stock index returns. More concretely, in this paper, we firstly examine the model formula and obtain general interpretations of the full BEKK model parameters. This shall be particularly helpful to understand not only the structure of the full BEKK model but also the mechanisms of similar multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) models. After the above general considerations, this study also interprets the case results, in which the full BEKK model is applied to French and German stock index returns. The concrete illustrations demonstrated in this case study shall be also very useful for future related research.
Highlights
In recent studies of asset pricing, multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) models are often employed to analyze financial time-series
The concrete illustrations demonstrated in this case study shall be very useful for future related research
We examine the parameter estimates obtained from a case study, which uses two European stock index returns
Summary
In recent studies of asset pricing, multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) models are often employed to analyze financial time-series. In order to clearly understand the empirical results derived from these models, it is highly important to grasp how we can interpret the estimates from these econometric models Based on this viewpoint, this paper attempts careful interpretations as to the model parameters of an interesting model, the full Baba-Engle-Kraft-Kroner (BEKK) model with asymmetric effects (Baba, Engle, Kraft, and Kroner, 1990; Engle and Kroner, 1995). As for the procedures more concretely, this paper firstly investigates the model formula, and shows how we can generally interpret the model parameters This shall be helpful for understanding the structures of MGARCH models. The concrete illustrations presented via this case study shall be very useful for future related research This is another contribution of this article.
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