Research On Futures Hedging Model Based On Geometric Spectral Measure Of Risk

The key issue of the futures markets is the determination of hedge ratio. The research of the hedge model is essential for the hedger and is a key issue of futures markets. Through hedge model to determine the hedge ratio can improve the hedge efficiency and effectively averse the risk of cash markets. The fifth chapter is the empirical study and the comparison analysis the last chapter is the conclusion.There are five chapters in this paper. The first chapter is about the significant of the research, introduction for the basic theory of hedging, frame of the paper and main content. The second chapter is the present research review. In the third chapter, we introduce the theory of the optimal hedging model based on Geometric spectral measure of risk. In the fourth chapter, we establish the optimal hedging model based on Geometric spectral measure of risk.There are three works in this paper. Firstly, the optimal hedging model based on Geometric spectral measure of risk is established. Larger weights are distributed to larger extreme losses by the function of the risk aversion, which controls the risk of extreme losses. and the optimal ratio of futures hedging is obtained by minimizing the extreme losses risk of the portfolio. Secondly, the empirical researches are done by the optimal hedging model based on Geometric spectral measure of risk. The last one is the relationship among traditional hedging ratio, minimum variance hedging ratio, VaR hedging ratio and the GM hedging ratio is shown.The innovations and characteristics are as follows: firstly, traditional hedging ratio, minimum variance hedging ratio and VaR hedging ratio are only special examples of this model. Secondly, larger weights are distributed to larger extreme losses by the function of the risk aversion, which controls the risk of extreme losses. This function of risk aversion fits the investors' risk aversion characters. Thirdly, objective weights were given to the extreme losses which avoid personal choices. Fourthly, the optimal hedging ratio of the model was composed of speculative demand and hedging demand, which reflect the real need of the hedging.