Due to the non-normality of stock returns, nonparametric rank tests are gaining accceptance relative to parametric tests in financial economics event studies. In rank tests, financial assets’ multiple day cumulative abnormal returns (CARs) are replaced by cumulated ranks. This paper proposes...

Because of non-normality of stock returns nonparametric rank tests are gaining incremental popularity over parametric tests in financial economics event studies. In rank tests financial assets' multiple day cumulative abnormal returns (CARs) are replaced by cumulated ranks. This paper proposes...

This paper is concerned with tests of restrictions on the sample path of conditional quantile processes. These tests are tantamount to assessments of lack of fit for models of conditional quantile functions or more generally as tests of how certain covariates affect the distribution of an...

This chapter discusses the formal and informal techniques that are commonly used to give quantitative answers in the field of distributional analysis. To this end, it covers subjects including inequality, poverty, and the modeling of income distributions. It also deals with parametric and...

This paper compares the finite sample performance of three non-parametric threshold estimators via the Monte Carlo method. Our results indicate that the finite sample performance of the three estimators is not robust to the position of the threshold level along the distribution of the threshold...

We propose a new semiparametric observation-driven volatility model where the form of the error density directly influences the volatility dynamics. This feature distinguishes our model from standard semiparametric GARCH models. The link between the estimated error density and the volatility...