We elaborate on the tail conditional expectation, the tail conditional variance, and the tail variance when the residuals follow the standardized Pearson type-IV distribution. If the probability density function describing the data generation process is continuous and the moments are finite,...

The cumulative distribution function of the Pearson type IV distribution is of complex form and includes a complex hypergeometric function. Although the mathematical form is complex, the resulting imaginary part is actually of the order which is attributed to the series summation of the...

We elaborate on a new distributional scheme resulting from the generalized Pearson distribution with application to financial modelling. As case studies we consider the major historical indices daily returns, DJIA, NASDAQ composite, FTSE100, CAC40, DAX and S&P500, as well as, high-frequency...

We examine the efficiency of the Asymmetric Power ARCH (APARCH) model in the case where the residuals follow the standardized Pearson type IV distribution. The model is tested with a variety of loss functions and the efficiency is examined via application of several statistical tests and risk...

Digital currencies and cryptocurrencies have hesitantly started to penetrate the investors, and the next step will be the regulatory risk management framework. We examine the Value-at-Risk and Expected Shortfall properties for the major digital currencies, Bitcoin, Ethereum, Litecoin, and...