Pricing Of Soybean Futures And Options Based On Term Structure Model

As a large producer of agricultural products,the price fluctuation of agricultural products may affect the national economy and people's livelihood,while uncontrollable factors such as weather risks and natural disasters will affect the supply and demand of agricultural products and thus affect the price of agricultural products.Therefore,the demand for financial products that can avoid the risks of agricultural products market and protect the interests of farmers and investors in agricultural products market has always existed.Compared with the development degree of commodity derivatives market in western developed countries,as the world's second largest economic development body,China's commodity derivatives market is in the growth stage.In order to better provide the price discovery,risk aversion and hedging of agricultural product derivatives market,it is very important to study the pricing of agricultural product derivatives market.In the actual empirical research process,this paper studies soybean futures and soybean meal futures options.Different from traditional financial markets,the growth period of agricultural products and all the seasonal climate change leads to seasonal changes of supply and demand of agricultural products,agricultural derivatives market also should have seasonal characteristics.Therefore,in the study of soybean futures pricing,seasonal variables were added on the basis of the traditional Schwartz(1997)two-factor model,and the corresponding futures price analytical solutions were derived under the condition of risk neutrality.The model is estimated by Kalman filter algorithm,using lots of real historical data of soybean futures contracts with different maturities between January 2,2014 to December 28,2018.Since soybean futures option is American option,no specific analytical solution can be derived,so this paper adopts the method of Least Square Monte Carlo simulation to price soybean futures option.In general,the fitting effect of the model derived in this paper is good,and the gap between the model and the real soybean meal futures market is small.Meanwhile,the empirical results show that the soybean futures market in China has obvious seasonality,and the Least Square Monte Carlo simulation method has certain empirical validity for the soybean futures option market.