Generalized Clayton Copula And Its Application In Futures Data Analysis

The shortcomings of traditional risk analysis methods is that it may underestimate the risk seriously, Copula function can reflect the dependence structure between variables and describe peak heavy-tail and unsymmetric of financial data and so on, therefore, it has been developed rapidly in the financial analysis. This paper mainly discusses the Copula theory and its dependence structure in financial analysis, In particular, a special class of Archimedean Copula-generalized Clayton Copula and its application in the futures exchange.The article first introduces the research background of Copula, the main properties and some conclusions; In the third chapter, the paper discusses the relations between Kendall's tau, Spearman's Rho, as well as the tail of the dependence coefficient and Copula, introduces the generalized Clayton Copula which has both upper and lower tail dependence, the function can describes both upper and lower tail dependence structure of financial data. Finally, in the forth chapter, the paper studies the data from 0:00, June 24,2008 to 2:00, April 18,2009 of Nymex 2009 July crude oil futures contracts and 2009 Cobt July corn futures contracts, compared with the generalized Clayton Copula and the common Normal Copula, t-Copula and Frank Copula, etc., we calculate the tail dependence coefficient as well as Monte Carlo VaR under different confidence level, the results shown that the generalized Clayton Copula can reflect the dependence structure of crude oil futures returns and corn futures' properly, measure the risk effectively, perform good feasibility and effectiveness.The paper also discusses some issues such as negative tail dependence function. Using the Copula properties, buy-sell and sell-sell Copula Expression can be calculated by the buy-buy Copula model.