Bayesian analysis of the risk management of China´s futures markets—A Tobit-GJR-GARCH model based study

Taking daily price limits into account and supposing that the information is asymmetric on China´s futures markets, this paper constructs a Two-limit Tobit-GJR-GARCH model, and carries out Bayesian analysis by means of Monte Carlo simulation to evaluate the VaR and CVaR of the active trading commodities (e.g. soybean oil, copper and sugar) on China´s futures markets. Empirical evidence indicates that daily price limits have important impacts on the risk measure and the theoretical margin of commodities with larger volatility. It is easy to underestimate the risk without regard to the impact of price limits, and the theoretical margin may not be able to cover the market risk. It will be more reliable to measure the risk and determine the theoretical margin based on the Tobit-GJR-Garch model which considers the impact of price limits, and the method provided in the paper accord with the actual situation and may be applied to the risk management of China´s futures markets.