Price Risk Management Of Chinese Fuel Oil Based On Hedging

Fuel oil is a very important kind of products of petroleum. Oil can affect the stability and development of the world economy with its special position in the economic field. It is known that China is a country of considerable oil consumption, but also of great number of the petroleum import. China’s oil import dependency has already risen to a new height. Fuel oil price in China will appear the corresponding fluctuations as international oil prices. Price fluctuations are bound to bring market risks to the enterprises. In order to avoid market risks, to make oil industry both ends meet, oil futures came into being. Using fuel oil futures contracts to hedge is an important means of fuel oil market risk management. Fuel oil futures listed on the Shanghai futures exchange and East mixed sulfur 180 CST are used in the paper as the example of hedging to avoid risks.This paper consists of five chapters, and can be divided into three parts: the first part(chapter 1) mainly introduces background and significance, research methods and possible place of innovation and inadequate. The second part(chapter 2 to chapter 4) is the empirical analysis. It mainly used GARCH family models to analyze the characteristics of the fuel oil price fluctuations. Monte Carlo simulation and Historical simulation method were used to measure Va R values of the fuel oil spot market, and build static hedging model of OLS, ECM and dynamic hedging model BGARCH and ECM-BGARCH to calculate the optimal hedging resale value, and examine the effects of hedging with the return inspection method. Third part(chapter 5) draws the conclusions of the contents.In this paper, empirical analysis mainly reaches conclusions as following:(1)Fuel oil spot return series have obvious fat tail and the leverage effect characteristics, while the volatility memory and persistent volatility characteristics are not strong.(2) GARCH model can be better fitting of fuel price volatility characteristics, and it can better measure the market risk VaR value than Monte Carlo simulation and Historical simulation method.(3)Dynamic Hedging Model ECM-BGARCH draws a more significant hedging rate and has better hedging performance better than OLS, ECM static hedging model, while ECM-BGARCH performs better than BGARCH.(4)Through hedging, market risk VaR values decreases significantly. It confirmed that hedging can better manage market risks.