2 resultados para Multidimensional DCT
em Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom
Resumo:
Pricing American options is an interesting research topic since there is no analytical solution to value these derivatives. Different numerical methods have been proposed in the literature with some, if not all, either limited to a specific payoff or not applicable to multidimensional cases. Applications of Monte Carlo methods to price American options is a relatively new area that started with Longstaff and Schwartz (2001). Since then, few variations of that methodology have been proposed. The general conclusion is that Monte Carlo estimators tend to underestimate the true option price. The present paper follows Glasserman and Yu (2004b) and proposes a novel Monte Carlo approach, based on designing "optimal martingales" to determine stopping times. We show that our martingale approach can also be used to compute the dual as described in Rogers (2002).
Resumo:
We study the screening problem that arises in a framework where, initially, the agent is privately informed about both the expected production cost and the cost variability and, at a later stage, he learns privately the cost realization. The speci c set of relevant incentive constraints, and so the characteristics of the optimal mechanism, depend nely upon the curvature of the principal s marginal surplus function as well as the relative importance of the two initial information problems. Pooling of production levels is optimally induced with respect to the cost variability when the principal's knowledge imperfection about the latter is sufficiently less important than that about the expected cost.