Showing 1 - 10 of 2,323
Recently financial econometricians have shifted their attention from point and interval forecasts to density forecasts mainly to address the issue of the huge loss of information that results from depicting portfolio risk by a measure of dispersion alone. One of the major problems in this area...
Persistent link: https://www.econbiz.de/10005342281
It has been a conventional wisdom that the two-sample version of the goodness-of-fit test like the Kolmogorov-Smirnov, Cramér-von Mises and Anderson-Darling tests fail to have good power particularly against very specific alternatives. We show that a modified version of Neyman Smooth test that...
Persistent link: https://www.econbiz.de/10005702690
Fractile Graphical Analysis (FGA) was proposed by Prasanta Chandra Mahalanobis in 1961 as a method for comparing two distributions at two different points (of time or space) controlling for the rank of a covariate through fractile groups. We use bootstrap techniques to formalize the heuristic...
Persistent link: https://www.econbiz.de/10014332611
The two-sample version of the celebrated Pearson goodness-of-fit problem has been a topic of extensive research, and several tests like the Kolmogorov-Smirnov and Cramér-von Mises have been suggested. Although these tests perform fairly well as omnibus tests for comparing two probability...
Persistent link: https://www.econbiz.de/10011067395
Persistent link: https://www.econbiz.de/10001580209
Persistent link: https://www.econbiz.de/10001701974
Persistent link: https://www.econbiz.de/10009759997
The smooth test originally proposed by Neyman (1937) deserves a renewed attention in the context of the current applications in Econometrics. Our paper attempts to put Neyman's smooth test into perspective with the existing literature on goodness-of fit tests and other procedures based on...
Persistent link: https://www.econbiz.de/10012754708
Fractile Graphical Analysis (FGA) was proposed by Prasanta Chandra Mahalanobis in 1961 as a method for comparing two distributions at two different points (of time or space) controlling for the rank of a covariate through fractile groups. We use bootstrap techniques to formalize the heuristic...
Persistent link: https://www.econbiz.de/10013401813
Recently econometricians have shifted their attention from point and interval forecasts to density forecasts because at the heart of market risk measurement is the forecast of the probability density functions of various financial variables. In this paper, we propose a formal test for density...
Persistent link: https://www.econbiz.de/10012711992