Correlation　and　risk　measurement　are　important　for　reliability　and　safety　evaluation　of　many　practical　systems.　Clayton　copula　and　180　degrees　rotated　Clayton　copula　are　suitable　for　measuring　the　lower-lower　tail　correlation　and　the　upper-upper　tail　correlation　reflecting　positive　correlation,　respectively.　The　90　degrees　rotated　Clayton　copula　and　270　degrees　rotated　Clayton　copula　are　severally　appropriate　for　measuring　the　lower-upper　tail　correlation　and　the　upper-lower　tail　correlation　reflecting　negative　correlation.　In　this　paper,　considering　the　possibility　of　variable　correlation　state　transition　under　the　condition　of　unfixed　component　copula　function　weight,　a　mixed　Clayton　copula　function　of　Markov　transformation　is　constructed　by　using　the　above　four　kinds　of　Clayton　copula,　and　the　marginal　distributions　of　variables　are　modeled　by　combining　ARMA　(p,　q)　-　GARCH　(m,　n)　model,　then　the　correlation　and　its　corresponding　risk　measurement　models　are　constructed　based　on　mixed　Clayton　copula.　Finally,　the　empirical　results　based　on　crude　oil　futures　price　and　Chinese　CSI　300　stock　index　futures　price　show　that,　compared　with　time-varying　Normal　copula,　time-varying　T　copula　and　Markov-switching　GRG　copula,　Markov-switching　mixed-Clayton　copula　model　can　achieve　better　effect　of　parameter　estimation.　The　calculation　on　the　correlation　and　risk　measurement　further　verifies　the　validity　and　reliability　of　the　models.