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...

The paper investigates short-horizon individual stock returns; it exhibits statistically and economically significant autocorrelations, which for stock returns have so far been established mainly over long horizons, also for certain daily data, in particular between monday returns and various...

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...

We consider the finite-sample power of various tests against serial correlation in the disturbances of a linear regression model when these disturbances follow certain stationary long-memory processes. It emerges that the power depends on the form of the regressor matrix and that, for the...

The paper presents an approach to the analysis of data that contains (multiple) structural changes in a linear regression setup. We implement various strategies which have been suggested in the literature for testing against structural changes as well as a dynamic programming algorithm for the...

The paper discusses structural change as possible mechanism that generates the appearance of long memory in economic time series. It shows that there are no long memory effects in German stock returns and that long memory in squares of German stock returns disappears once shifting means are...

We consider the finite sample power of various tests against serial correlation in the disturbances of a linear regression when these disturbances follow a stationary long memory process. It emerges that the power depends on the form of the regressor matrix and that, for the Durbin-Watson test...