Research On Hedging Risk Management Of China's Fuel Oil Futures Market

As an important financial derivative, futures have the hedging function. In recent years, more and more domestic enterprises began to hedge in futures market in order to avoid the risk of spot market. However, due to lack of the objective identification and management ability on heging risk, high loss events of heging frequently occur. As the downstream product of crude oil, fuel oil price has a strong correlation with international crude oil price and fluctuates heavily. Domestic fuel oil enterprises urgently need to avoid spot market risk through fuel oil hedging. However, how to identify and evaluate hedging risk of fuel oil futures correctly, how to use historical price data to measure and control hedging risk, and how to build effective dynamic risk monitoring system, are urgently needed to be solved for fuel oil enterprises.This paper systematically studies hedging risk management of China's fuel oil futures from three aspects of hedging risk identification, measurement and control. First, we identify and evaluate hedging risk of China's fuel oil futures and deeply analyzes the reasons of various risks. The results show that hedge ratio risk, futures price extreme risk and basis risk are the most fundamental objective risk for heging. Second, under the condition of minimizing portfolio returns risk, we first calculate the minimum risk hedge ratio of China's fuel oil using various static and dynamic hedging models, and analyze the influence of different hedging periods and different hedging models on hedge ratio and hedge effectiveness. The results show that hedge effectiveness of ECM-BGARCH model with a period of four weeks is the best. Then, we focus on the measurement problems of futures price extreme risk and basis risk. Based on VaR theory, we first build the VaR model which can measure extreme upside risk and extreme downside risk. And we estimate conditional expectation and conditional variance of the rate of return using GARCH model, which are used to calculate VaR sequence. Back-testing show that, at a certain confidence level, the VaR model built in this paper can effectively measure futures price extreme risk and basis risk of China's fuel oil. This paper provides a effective hedging risk measurement method for China's fuel oil.According to the empirical results, this paper deeply studies the corresponding hedging risk management strategy. In practice, fuel oil enterprises can establish hedging risk monitoring system using the VaR models built in this paper. And they can develop a strict stop-loss program, select the appropriate time for hedging and timely adjust hedge ratios and reserve ratio of venture capital according to daily VaR value estimated, to improve hedge effectiveness.