JSTOR Daily

Symmetrizing and Variance Stabilizing Transformations of Sample Coefficient of Variation from Inverse Gaussian Distribution

Coefficient of variation (CV) plays an important role in statistical practice; however, its sampling distribution may not be easy to compute. In this paper, the distributional properties of the sample ...
Risk

Risk estimation using the multivariate normal inverse Gaussian distribution

Appropriate modeling of time-varying dependencies is very important for quantifying financial risk, such as the risk associated with a portfolio of financial assets. Most of the papers analyzing ...
JSTOR Daily

K-Sample Likelihood Ratio Tests on the Inverse-Gaussian Distribution

Journal of the Royal Statistical Society. Series D (The Statistician) The Statistician joined the Journal of the Royal Statistical Society as its Series D from the journal of the Institute of ...
Risk

Risk estimation using the normal inverse Gaussian distribution

It may be misleading to estimate value-at-risk (VAR) or other risk measures assuming normally distributed innovations in a model for a heteroscedastic financial return series. Using the t-distribution ...