Research On Strategies Of Futures Hedging With Fuzzy Information

With the constant improvement of Chinese financial market system and the approximation to the international financial, our financial market in the development of economy is playing a more and more important role, even promote Chinese economic development. The financial crisis sweeping the global in 2008 makes the people not only pursue profits, but also treat the financial market in a more rational and correct eye.Now people pay more attention to the risk control, so the financial products that can control risk get more favor of people. Futures, one of the financial products, is studied in this paper.Stock index futures listed fill the blank of financial market in 2010, and Chinese future market is still improving. Now we use commodity futures mostly in China. The main function of futures market is price discovery and avoiding risk. More research is about hedging, and the research on future hedging existed has been complete. This paper studies futures hedging in a new angle.This paper studies fuzzy futures hedging, from another aspect of the certainty. Taking into account the influence of the historical data in statistical, we propose the fuzzy number that overcomes the data of limitation of the model. At the same time, in order to describe the satisfaction of the return and risk of futures hedging, we propose the membership function that depicts the satisfaction levels of return and risk of futures hedging through the adjustment of parameters. When return rates are predicted accurately, the information and experience belonged to the experts can be made full use of. Interval number can reflect this. We research dynamic futures hedging in interval number.Based on fuzzy information, we study futures hedging. Worst-case VaR depicts the hedging risk, and asymmetry of return rates is taken into consideration. We get futures fuzzy hedging strategies based on the control of total loss risk. Then this paper researches dynamic futures fuzzy hedging. Hedgers can adjust hedging ratios according to phase of expected return and risk, so that hedgers can obtain satisfactory optimal hedging strategies.