The Empirical Research On The Price Discovery Function And Hedging Function Of Fuel Oil Futures Market In China

Crude oil prices plummet in 2014. Although the price seems to be bottoming out from a terrible recession, the global economy shows a weak trend in 2015. The demand of market is low. Crude oil price still have a downward trend. As the downstream petroleum products, fuel oil was not immune. The uncertainty of the price brings a lot of risks to investors and manufacturers. Therefore, the use of appropriate financial hedging tools is particularly important. The trading of fuel oil future starts in August 2004 on the Shanghai Futures Exchange. So if we want to build a well-behaved fuel oil futures market. It is necessary to conduct an in-depth investigation on price discovery function and hedging function of fuel oil futures market. This will not only help regulators to take reasonable and effective control measures in a timely manner, but also can help market participants to use the two major functions of the fuel oil futures to make decisions.The structure of this paper is as follows: The first chapter states the research background, research significance, research methods and the structure of the thesis. The second chapter introduces the literature review and theoretical basis, respectively, from the fuel oil price discovery function and the function of hedging. The third chapter is the empirical analysis of the price discovery function of the fuel oil futures market based on the method of continuous wavelet transform. The fourth chapter is the empirical analysis of the function of the fuel oil futures market.First of all, In this paper, a method of continuous wavelet analysis which combines time domain and frequency domain is adopted to study the price discovery function of fuel oil futures market. The proposed method can be used to analyze the linkage between two time series in time domain and frequency domain, and the problem of structure mutation is also considered. In order to determine whether the fuel oil futures market has price discovery function, we use wavelet coherence analysis the dynamic linkage between the fuel oil futures and fuel oil spot, then take advantage of wavelet phase difference to analysis the lead-lag relationship between the fuel oil futures price and spot price, The empirical results show the fuel oil futures market has played some price discovery function, but the market is not perfect. In the whole sample period, the relationship between the fuel oil futures and spot price has a positive correlation. The changing of frequency will make the fuel oil spot and futures prices interact in the short and long term. In the short term, there are bi-directional lead relations between the fuel oil futures and spot price. But it can be known from the phase difference image that the phase difference between the spot and the futures price of the fuel oil is gradually decreasing, therefore, in the longer term, most of the lead lag relationship is disappearing. In the dynamic process, the phase difference between the fuel oil futures and the spot price series is about zero. This reveals that the fuel oil futures and spot market has a two-way feedback mechanism, both of which have contributed to the dynamic change of the long-term equilibrium price. Although in the different time and frequency domain, the fuel oil futures and spot prices show a bi-directional lead relation, the effect of fuel oil spot on the futures is stronger, this can be seen from the phase difference, this shows that although China’s fuel oil futures market has a certain price discovery function, but the market is not very perfect.Finally, based on the portfolio hedging theory and the minimum variance hedge ratio model, the research on the hedging function of the fuel oil futures market is studied. In this paper, we first calculate the static hedging rate(VECM hedging rate) and the dynamic hedging rate(DCC-GARCH hedging rate, Copula GARCH hedge ratio, MRS Copula hedging rate). And then analyze the hedging effect of China’s fuel oil futures under different models. The traditional GARCH model is used in this paper. Most of the dynamic GARCH models assume the joint distribution between asset returns follow a multivariate normal distribution, however, the characteristics of the peak fat tail of financial return series are not consistent with the actual situation. The Copula model lets loose the assumption of normal distribution, and the edge distribution can be used in any form, in this way, we can construct a more flexible multivariate distribution function. This paper adopts GARCH(1, 1) model to estimate the fuel oil futures and spot return marginal distribution. In fact, the futures market tends to show the characteristics of the state transition between the bull market and the bear market, high volatility and low volatility. The single state measurement methods used by scholars before may not be able to better illustrate the transformation characteristics of the market under different conditions. However, the Markov switch model is a very important and recognized nonlinear state transition model. The model can explain the correlation between the futures and the spot in different conditions. So in order to better describe the hedge ratio of Shanghai fuel oil futures market, this paper introduces the Markov chain transfer model. We combine it with the Copula model to form a new MRS Copula model. The empirical results show that the fuel oil futures market plays a certain hedging function, but hedge ratio is relatively low. In terms of hedging performance, the hedging performance of MRS Copula model is the highest, and the hedging performance of VECM model is the worst one.