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 ...

James Chen, CMT is an expert trader, investment adviser, and global market strategist. Khadija Khartit is a strategy, investment, and funding expert, and an educator of fintech and strategic finance ...

Caroline Banton has 6+ years of experience as a writer of business and finance articles. She also writes biographies for Story Terrace. Carl Friedrich Gauss was a child prodigy and a brilliant ...

This article treats the analysis of factorial experiments under an inverse Gaussian distribution for the failure times. A reciprocal-linear model for the factor effects is motivated from the context ...

The scale parameter is 1 for Poisson and binomial distributions. SAS/INSIGHT software provides different scale parameter estimates for normal, inverse Gaussian, and gamma distributions: Note You can ...

Forecasting for any small business involves guesswork. You know your business and its past performance, but you may not be comfortable predicting the future. Using Excel is a great way to perform what ...

This is a preview. Log in through your library . Abstract In the classical Lee-Carter model, the mortality indices that are assumed to be a random walk model with ...

The normal distribution (also known as the Gaussian distribution) is arguably the most important distribution in Statistics. It is often used to represent continuous random variables occurring in ...

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 ...