In observational studies, the estimation of a treatment effect on an outcome of interest is often done by controlling on a set of pre-treatment characteristics (covariates). This yields an unbiased estimator of the treatment effect when the assumption of unconfoundedness holds, that is, there...

We revisit the apparent historical success of technical trading rules on daily prices of the Dow Jones index. First, we use the False Discovery Rate as a new approach to data snooping. The advantage of the FDR over existing methods is that it is more powerful and not restricted only to the best...

This paper examines latent risk factors in models for migration risk. We employ thestandard statistical framework for ordered categorical variables and induce dependencebetween migrations by means of latent risk factors. By assuming a Markov process forthe dynamics of the latent factors, the...

While the relationship between volatility and risk is central to much of thefinancial literature it has not been incorporated systematically into assessment ofsovereign debt sustainability. This paper attempts to fill this gap by studying how the probability distribution of sovereign debt to GDP...

We consider testing for correct specification of a nonparametric instrumental variable regression. In this ill-posed inverse problem setting, the test statistic is based on the empirical minimum distance criterion corresponding to the conditional moment restriction evaluated with a Tikhonov...

This paper focuses on the robust Effcient Method of Moments (EMM) estimation of a general parametric stationary process and proposes a broad framework for constructing robust EMM statistics in this context. This extends the application field of robust statistics to very general time series...

We study the asymptotic properties of a Tikhonov Regularized (TiR) estimator of a functional parameter based on a minimum distance principle for nonparametric conditional moment restrictions. The estimator is computationally tractable and takes a closed form in the linear case. We derive its...

Driven by the rise in computational power, it has become popular to measure integrated variance with high-frequency squared returns. Though the squared return is a natural choice as a variance estimate, it is not the most efficient one for a given interval length. Extreme-value based estima-...

We propose a general robust semiparametric bootstrap method to estimate conditional predictive distributions of GARCH-type models. Our approach is based on a robust estimator for the parameters in GARCH-type models and a robustified resampling method for standardized GARCH residuals, which...

In this paper, we consider an investor who plays in a market that involves a risky asset whose instantaneous rate of return changes at unknown random times. This return rate is assumed to follow the law of a Compound Poisson Process. We construct optimal mathematical strategies in this context...