Due to global pandemics, political unrest and natural disasters, the stability of the supply
chain is facing the challenge of more uncertain events. Although many scholars have …

In this study, a multivariate ARMA–GARCH model with fractional generalized hyperbolic
innovations exhibiting fat-tail, volatility clustering, and long-range dependence properties is …

Rapidly decreasing tempered stable (RDTS) distributions are useful models for financial
applications. However, there has been no exact method for simulation available in the …

This paper explores Artificial Neural Network (ANN) as a model-free solution for a calibration
algorithm of option pricing models. We construct ANNs to calibrate parameters for two well …

In this paper we describe a methodology for parameter estimation of multivariate
distributions defined as normal mean-variance mixture where the mixing random variable is …

In this paper, we introduce a new time series model with a stochastic exponential tail. This
model is constructed based on the Normal Tempered Stable distribution with a time-varying …

In this paper, we introduce a fractional Generalized Hyperbolic process, a new stochastic
process with long-range dependence obtained by subordinating fractional Brownian motion …

Long-memory processes in the financial time series is an important research topic in
derivative pricing and risk management. Most of the past empirical research about the long …