Stock returns are often modeled as having infinite second or fourth moments with consequences for test statistics which have not yet been fully explored. Conclusions on the existence of moments are usually drawn from a generalized Pareto or simple Pareto tail index estimate. In a recent study...

We argue against the view that it is mostly the peaks of the empirical densities of stock returns (and of other risky returns as well) that set such data aside from quot;normalquot; variables. We show that peaks depend on sample size and on the way returns are standardized, and that for given...

We try to replicate the findings in Saunders (1993) that stock prices are quot;systematically affected by local weatherquot;. Using German data, we find that whether or not the null hypothesis of no relationship can be rejected depends mostly on the way the null hypothesis is phrased, and that...

Two different estimation techniques for the spectrum of a nonstationary time series are compared empirically. Both of them are assuming a time-dependent autoregressive (AR-) model for the data. The first estimation technique used is the Frequency State Dependent Model (FSDM-) technique (Schmitz...

We argue against the view that it is mostly the peaks of the empirical densities of stock returns (and of other risky returns as well) that set such data aside from "normal" variables. We show that peaks depend on sample size and on the way returns are standardized, and that for given data sets...

We consider empirical autocorrelations of residuals from infinite variance autoregressive processes. Unlike the finite-variance case, it emerges that the limiting distribution, after suitable normalization, is not always more concentrated around zero when residuals rather than true innovations...