Abstract：In this talk, I will show two applications of Stackelberg game in reinsurance contract. In a Stackelberg game framework, the reinsurer is the leader of the game and decides on an optimal reinsurance premium to charge, while the insurer is the follower of the game and chooses an optimal per-loss reinsurance to purchase. In the first application, the objective of reinsurer is the weighted sum of the insurer's and reinsurer's mean-variance criteria, which implies that the reinsurer takes both the insurer's interest and herself into consideration when choosing the reinsurance premium. We provide an intuitive way to identify the weight in the reinsurer's objective. In the second application, we consider a reinsurance problem for a mean-variance Stackelberg game with a random time horizon. We show that if the claim severity is light-tailed, in the sense that its hazard rate function is nondecreasing, then the equilibrium reinsurance is pure stop-loss reinsurance with no loading for the variance of the loss. Moreover, we show that if the claim severity is heavy-tailed, in the sense that its hazard rate function is decreasing, then the equilibrium reinsurance has a non-trivial coinsurance, with a positive loading for the variance of the loss.