Volatility Transmission in Chinese Trucking Markets: An Application Using BEKK, CCC and DCC-MGARCH Models

This paper aims at investigating whether volatility spillover effects exist among sub-segments in heavy truck trucking market of Southwest China based on trading data from online freight exchange (OFEX) platform, in which the sub-segments are classified by truck length, roughly as short bed sub-segment and long bed sub-segment. Model conditional correlations were modeled via the Multivariate Generalized Autoregressive Conditional Heteroskedasticity (MGARCH) model in the paper, followed by the analysis of volatility spillovers between sub-segments. Firstly, a Student's t distribution based BEKK (Baba, Engle, Kraft and Kroner) model is applied to analyzing the persistence effect as well as the volatility spillovers between sub-segments. Secondly, the change of interdependence degree between abovementioned markers is evaluated via the constant and dynamic conditional correlation models. We observed the constant long-term cross-volatility within the short bed sub-segment while multiple dynamic one-way volatility transmissions are observed, from the long bed sub-segment to the short bed sub-segment. In addition, an indication weight based on estimations of dynamic conditional correlation model is proposed to help marketing researchers to determine the weights of indices components when constructing trucking index in the future.