Modeling the Volatility in China's Railway Freight Volume Based on Conditional Volatility Model.

China's railway is an important component of logistics transportation to promote the rapid development of modern logistics. It also facilitates the growth of economy. How to improve the efficiency of railway freight is becoming a crucial issue for the development of modern logistics. This paper uses symmetric and asymmetric conditional volatility models, GARCH (1, 1), GJR-GARCH (1, 1) and EGARCH (1, 1), to estimate the volatility in monthly railway freight volume. The volatility estimated results indicate that it has an asymmetric effect on risk from positive and negative shocks of equal magnitude. Moreover, there is a leverage effect in the monthly growth rate of railway freight volume, whereby negative shocks increase volatility but positive shocks of very similar magnitude decrease volatility. These empirical results seem to be similar to a wide range of financial stock market prices, so that the models used in financial economics are also applicable to railway freight volume. Volatility experienced by logistics transportation industry has significant implications for capital investment, resource allocation and yield management. The empirical findings of this paper provide useful insights which can be expected to be of interest to the private and public sectors in the formulation of logistic management policy especially on railway transportation. [ABSTRACT FROM AUTHOR]