Statistical models are usually thought of as means for describing statistical regularities. Concerning stock returns, many empirical regularities have been documented in the literature together with their corresponding models. The main task of this paper is to investigate, under the prism of the...

The Single Factor Model (SFMT) of stock returns in its simplest form, namely the one that assumes time-invariant beta and homoskedastic error has been found to be empirically inadequate.The beta coefficient and the error process exhibit signi��cant time-variation and dynamic...

In this paper we investigate whether the empirical regularities of stock returns are independent of each other or whether any one of them implies all the others. If such a regularity exists, it is called 'fundamental' and is usually thought of as a 'deductive explanation' of the others. We...

This paper investigates the implications of time-varying betas in factor models for stock returns. It is shown that a single-factor model (SFMT) with autoregressive betas and homoscedastic errors (SFMT-AR) is capable of reproducing the most important stylized facts of stock returns. An empirical...

The purpose of this paper is twofold: first, to survey the statistical models of stock returns that have been suggested in the finance literature since the middle of the twentieth century; second, to examine under the prism of the contemporary philosophy of science, which of the aforementioned...

This paper evaluates the Morningstar mutual fund ranking system. We find that indeed higher Morningstar ratings are associated with higher returns on the portfolios including respectively five-, four-, three-, two- and one-star funds only (STAR5 to STAR1). We then perform an unconditional and...

This paper evaluates the Morningstar mutual fund ranking system. We find that indeed higher Morningstar ratings are associated with higher returns on the portfolios including respectively five-, four-, three-, two- and one-star funds only (STAR5 to STAR1). We then perform an unconditional and...

This article investigates the problem of testing for a unit root in the case that the error, {u_t}, of the model is a strictly stationary, mixing process with just barely infinite variance. Such errors have the property that for every &dgr; such that 0 = &dgr; 2, the moments E|u_t|-super-&dgr; are finite....

This paper focuses on first-order autoregressive models in which the noise variance increases without bound. Although this specification violates a standard assumption made in the relevant literature, namely that of bounded noise variance, it is proved that the well-known Eicker-White estimator...

This paper investigates the performance of the OLS estimator in the context of a cointegrating system, which exhibits a single variance shift. It is shown that the limiting distribution of OLS and that of the associated t-statistic depend on the time, the size and the direction of the break.