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 ...

Expanding the realized variance concept through realized skewness and kurtosis is a straightforward process. We calculate one-day forecasts for these moments with a simple exponentially weighted ...

This library implements the cumulative distribution function of the normal inverse Gaussian (NIG) distribution. The code is written in C++ and includes an interface for Python via ctypes.

Abstract: Normal inverse Gaussian (NIG) distribution is a quit a new distribution introduced in 1997. This is distribution, which describes evolution of NIG process. It appears that in many cases NIG ...

Abstract: The normal inverse Gaussian (NIG) distribution is a recent flexible closed form distribution that may be applied as a model of heavy-tailed processes. The NIG distribution is completely ...

ABSTRACT: The calculation of the mean difference for the inverse normal distribution can be obtained by a transformation of variable or a hard integration by parts. This paper shows a simpler formula ...