The paper studies the cooperative hedging problem of contingent claims in an incomplete financial market. Firstly we give the characterization of the optimal cooperative hedging strategy for the Black-Scholes model and the Volatility Jump model explicitly, then we consider the problem of...

Causal networks are graphically represented by directed acyclic graphs (DAGs). Learning causal networks from data is a challenging problem due to the size of the space of DAGs, the acyclicity constraint placed on the graphical structures, and the presence of equivalence classes. In this article,...

With the increasing of labor salaries, the RMB exchange rate, resource product prices and requirements of environmental protection, inexpensive labor and land are no longer the decisive factor of regional competitiveness. From this perspective, China needs to shift from the extensive development...

Dynamic panel models play an increasingly important role in numerous areas of corporate finance research, and a variety of (biased) estimation methods have been proposed in the literature. The biases inherent in these estimation methods have a material impact on inferences about corporate...

In this paper we apply the martingale approach, which has been widely used in mathematical finance, to study the optimal investment problem for an insurer. When the risk and security assets are described by the Lévy processes and utility is CARA, the closed-form solutions to the maximization...

In this paper, we establish the existence and uniqueness of the solution for a class of reflected backward stochastic differential equations with time delayed generator (RBSDEs with time delayed generator, in short) for a sufficiently small Lipschitz constant of the generator.

Whether bilateral trade barrier data conform with the Grossman-Helpman (1995) model’s predictions about “trade talks” is examined in this article. A simple form of the prediction from the model is tested. Bilateral US-Japan and US-EU data from the 1990s are employed. The results are the...