Most dimension reduction methods based on nonparametric smoothing are highly sensitive to outliers and to data coming from heavy tailed distributions. We show that the recently proposed MAVE and OPG methods by Xia et al. (2002) allow us to make them robust in a relatively straightforward way...

We develop inference tools in a semiparametric partially linear regression model with missing response data. A class of estimators is defined that includes as special cases: a semiparametric regression imputation estimator, a marginal average estimator and a (marginal) propensity score weighted...

This paper studies empirical issues of one-factor yield curve models. We focus on the models by Hoand Lee (1986), Hull and White (1990) and Moraleda and Vorst (1996). To be consistent in thecomparison of the models, we derive them all within the Ritkchen and Sankarasubramanian (1995)framework,...

In this paper we introduce a new methodology to price American put options under stochastic interestrates. The method is a combination of an analytic approach and a binomial tree approach. We constructa binomial tree for the forward risk adjusted tree and calculate analytically the expected...

In this paper we compare market prices of credit default swaps with model prices. We showthat a simple reduced form model with a constant recovery rate outperforms the market practice ofdirectly comparing bonds' credit spreads to default swap premiums. We find that the model workswell for...