We propose a two-stage procedure to estimate conditional beta pricing models that allow for flexibility in the dynamics of assets' covariances with risk factors and market prices of risk (MPR). First, conditional covariances are estimated nonparametrically for each asset and period using the...

In this paper we propose a new method to estimate nonparametrically a time varying parameter model when some qualitative information from outside data (e.g. seasonality) is available. In this framework we make two main contributions. First, the resulting estimator is shown to belong to the class...

This paper proposes a semiparametric option pricing model with liquidity, as proxied by the relative bid-ask spread. The nonparametric volatility function with liquidity as an explanatory variable is estimated using the Symmetrized Nearest Neighbors (SNN) estimator rather than the traditional...

In the analysis of longitudinal data it is of main interest to investigate the existence of group and individual effects under correlated observations across time. In this paper, we develop a nonparametric two-step procedure that enables us to estimate group effects under a very general form of...

In this work we study the effect of several covariates X on a censored response variable T with unknown probability distribution. A semiparametric model is proposed to consider situations where the functional form of the effect of one or more covariates is unknown. We provide its estimation...

This paper investigates original issuers of high yield bonds in Chapter 11 bankruptcy to determine which factors affect the length of time spent in Chapter 11. In order to do this analysis we propose a flexible new duration model, the censored partial regression model. This model allows us to...