The Volatility Characteristics Of Soybean Futures Prices

The futures market is influenced by the domestic market environment and international financial system. In recent years, the process of globalization has accelerated and the domestic financial market has achieved rapid development. The financial risk at home and abroad has a greater and clearer impact on the futures market than before, which appears that the futures price fluctuates frequently. And therefore, it is especially important to analyze the volatility characteristics of futures. Unlike other futures, agricultural commodity futures are affected not only by the market factors, but also by the natural environment. It is necessary to analyze the volatility characteristics and market risk of the agricultural commodity futures, which will help to guarantee the healthy operation of the futures market and ensure the sustainable and healthy development of agriculture in our country.The Dalian Commodity Exchange launched the yellow soybean one futures which is an active future with big trading volume. This paper examined the volatility of daily returns on soybean futures using a regime switching GARCH model. We conclude that the data is peaky and fat-tailed. The volatility clusting, highly persistence and GARCH effects are clearly present in the data. There are two different kinds of volatility state. The high volatility state has obvious clusting and longer duration, while the low volatility has homoscedasticity and shorter duration. It is easier for soybean futures to switch from the low volatility to high volatility. The paper indicates that the regime switching model performs noticeably better than non-switching model. Because of the relationship between supply and demand and financial crisis, there are two long periods of high volatility state in the sample period. However, there are many other reasons accounting for the fluctuation and regime switching, such as weather conditions, crude oil price, the domestic policy.This paper firstly uses Markov model to study the volatility of soybean futures that can portray the volatility characteristics more accurately. It finds the reason behind the high and low volatility and the duration of different volatility state, which paves the way for trend prediction. The previous papers selected the contract that has three or five months before the delivery month, which was not accurate. In this paper, according to the concept of the main contract, it selects the contract with the biggest trading volume and views its closing price as the futures price in every month. Thus, the data is more accurate and the results are more convincing.