In this paper we are concerned with backward stochastic differential equations with random default time and their applications to default risk. The equations are driven by Brownian motion as well as a mutually independent martingale appearing in a defaultable setting. We show that these...

We investigate an evolutionary prisoner’s dilemma game among self-driven agents, where collective motion of biological flocks is imitated through averaging directions of neighbors. Depending on the temptation to defect and the velocity at which agents move, we find that cooperation can not...

We study the effects of mobility on the evolution of cooperation among mobile players, which imitate collective motion of biological flocks and interact with neighbors within a prescribed radius R. Adopting the the prisoner’s dilemma game and the snowdrift game as metaphors, we find that...

A generalized complex dynamical networks model with neutral-type coupling delay is proposed, which is an extension for the systems without time delay and with the retarded delay. By some transformation, the synchronization problem of the complex networks is transferred equally into the...

Generalized anticipated backward stochastic differential equations, studied for the first time in 2007, are equations with generator f depending on the future value of the solution (Y⋅,Z⋅). In this paper, we will study the existence and uniqueness of the reflected solutions to these...

Purpose – The purpose of this paper is to: first, test if information-adjusted noise model (IANM) can be applied in China; second, quantify noise trader risk, overreaction, underreaction and information pricing errors in that market; and third, explain the relationship between noise trader risk...

Incentive effects of performance-based compensation schemes for management may be weakened or biased by macroeconomic influences on remuneration. These influences can be seen as reflecting luck from the CEO’s perspective. In this chapter we present a model for how to avoid compensating CEO for...