Showing 1 - 6 of 6
The capital-asset-pricing model (CAPM) is one of the most popular methods of financial market analysis. But, evidence of the poor empirical performance of the CAPM has accumulated in the literature. For example, based on their empirical results regarding the relation between market Beta and...
Persistent link: https://www.econbiz.de/10011431316
Since Mandelbrot's seminal work (1963), alpha-stable distributions with infinite variance have been regarded as a more realistic distributional assumption than the normal distribution for some economic variables, especially financial data. After providing a brief survey of theoretical results on...
Persistent link: https://www.econbiz.de/10003461221
This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of...
Persistent link: https://www.econbiz.de/10003608864
Logan et al. (1973) analyze the limit probability distribution of the statistic sn(p) = Σi=1 Xi/(Σi=1 Χj ) /p as n → ∞, when Xi is in the domain of attraciton of a stable law with stabilility index a. By simulations, we provide quantiles of the usual critical levels of the finite-sample...
Persistent link: https://www.econbiz.de/10011431987
of confidence interval for estimates is usually based. Statistical theory for the MC method is given. A simulation study … statistische Theorie für die Monte-Carlo-Methode wird abgeleitet. Anhand einer Simulationsuntersuchung wird die Effizienz von …
Persistent link: https://www.econbiz.de/10011432250
Under the symmetric á-stable distributional assumption for the disturbances, Blattberg et al (1971) consider unbiased linear estimators for a regression model with non-stochastic regressors. We consider both the rate of convergence to the true value and the asymptotic distribution of the...
Persistent link: https://www.econbiz.de/10003029711