Study On The Price Discovery Efficiency Of China’s Agricultural Commodity Futures With The Fractal Perspective

Recently, the position of price discovery function of China’s agricultural futures market has been increasingly highlighted in the domestic market, at the same time, its status is also rising in the world. The further improvement of the price discovery function will directly determines the new level of China’s agricultural commodity futures market. Based on this, within the framework of the fractal market hypothesis, this paper deeply analyses the relationship between the price discovery efficiency and the fractal structure of china’s main agricultural commodity futures market.This research has two main lines, one is the price discovery efficiency, the other is the fractal market analysis. First of all, the author combed several related theory concerning the two main lines, such as the holding cost, stochastic volatility, the fractal market hypothesis, etc. Next, with considering the turnover ratio and volume ratio, this article selected eight main agricultural products futures form three commodity futures market in China, respectively are:the bean oil, natural rubber, a number of cotton, sugar,1yellow soybeans, corn, soybean meal, palm oil. According to the China securities and futures statistical yearbook issued by China securities regulatory commission each year, the total turnover and total of8kinds of agricultural products futures trading volume respectively accounted for98.9%and96.81%of the total, which can be used to represent the overall situation of the agricultural product futures market in China. Then, the author tested the selected samples of agricultural products futures price and spot price with correlation test, unit root test, cointegration test, granger causality test and GS model test, so as to get the price discovery efficiency of various agricultural products futures. The empirical results show that the price discovery efficiency of China’s agricultural products futures from high to low is arranged as follows:palm oil, soybean oil, natural rubber, cotton, sugar, corn, for the soybean meal and soybean. However, because these two kinds of agricultural products futures don’t exist co-integration relationship, it’s impossible for them to use GS model calculation, namely, futures prices and spot prices of soybean meal and soybean does not exist guiding relationship between each other.The second main line of this article is parsing the fractal structure of the futures market for agricultural products. First of all, this paper analyzed eight main agricultural products in China’s futures market by using the R/S analysis method), so as to get the hurst index of various agricultural products, which can be used to reflect the single fractal structure of agricultural product futures market. The results show that:China’s agricultural products futures of hurst index from high to low is arranged as follows: cotton, soybean oil, natural rubber, palm oil, sugar, corn. In order to compare the results with the price discovery efficiency, soybean meal and soybean will not be ranked. Additionally, the hurst index of all agricultural products futures is less than0.3, which indicates that the sustainability is stronger. Then, this article used the method of multifractal castration (MFDA) to calculate the generalized hurst index, the agricultural products futures hurst sequence diagram, the scale index function analysis, the logarithm yield sequence small-scope fluctuation contribution, multifractal spectrum for each agricultural products futures.The empirical results show that:besides soybean and soybean meal, other agricultural products futures in China have typical multifractal characteristics; The logarithm yield sequence of China’s agricultural products futures multifractal intensity from strong to weak is as follows:corn, cotton, natural rubber, white sugar, palm oil, soybean oil; The logarithm yield sequence of China’s agricultural products futures fluctuated contribution from large to small is as follows:white sugar, palm oil, cotton, natural rubber, corn, soybean oil.After respectively calculating the price discovery efficiency and the fractal structure of main agricultural products futures market in China, this paper made horizontal comparison between them and made the following conclusions:the greater the degree of single fractal the price discovery efficiency is, the higher the price discovery efficiency of agricultural product futures market will be; the lower the degree of multifractal structure of the Agricultural futures market is, the higher the price discovery efficiency of agricultural product futures market will be; If the agricultural product futures market is not a fractal market, it does not exist between the futures price and spot price price guide.Based on the above empirical analysis and comparing the results, this paper puts forward to reduce the "noise" of futures markets, namely reducing its multifractal strength, thereby promoting the price discovery efficiency of agricultural product futures market. And the core of "noise" is to reduce the "intervention". The "people" on the agricultural product futures market mainly involve individuals, companies, futures trading organizations and government, therefore, the specific measures are:reduce the government direct intervene in the market; expand the scale of futures investors, improve the quality of the investors; encourage enterprise investors to actively participate in; promote the reform of the futures exchange; set out the agricultural options, realize the marketization of agricultural subsidies.