This paper investigates the dynamic tail dependence risk between BRICS economies and world energy market, in context of COVID-19 financial crisis 2020, order to determine optimal investment decisions based on metrics. For this purpose, we employ a combination novel statistical techniques, including Vector Autoregressive (VAR), Markov-switching GJR-GARCH, vine copula methods. Using data set cons...

We propose an extension of standard asymmetric volatility models in the generalized autoregressive conditional heteroskedasticity (GARCH) class that admits conditional nonGaussianities in a tractable fashion. Our “bad environment-good environment" (BEGE) model utilizes two gamma-distributed shocks and generates a conditional shock distribution with time-varying heteroskedasticity, skewness, and...

In the empirical finance literature findings on the risk-return tradeoff in excess stock market returns are ambiguous. In this study, we develop a new QR-GARCH-M model combining a probit model for a binary business cycle indicator and a regime switching GARCH-in-mean model for excess stock market return with the business cycle indicator defining the regime. Estimation results show that there is...

Discrete-time stochastic volatility (SV) models have generated a considerable literature in financial econometrics. However, carrying out inference for these models is a difficult task and often relies on carefully customized Markov chain Monte Carlo techniques. Our contribution here is twofold. First, we propose a new SV model, namely SV–GARCH, which bridges the gap between SV and GARCH models...

This paper proposes a simple test for threshold nonlinearity in either the mean or volatility equation, or both, of a heteroskedastic time series. Our proposal adopts existing Bayesian Markov chain Monte Carlo methods to fit a general double threshold GARCH model, which may have an explosive regime, then forms posterior credible intervals on model parameters to detect and specify threshold nonl...

A Bayesian estimation of a GARCH model is performed for US Dollar/Japanese Yen exchange rate by the Metropolis-Hastings algorithm with a proposal density given by the adaptive construction scheme. In the adaptive construction scheme the proposal density is assumed to take a form of a multivariate Student’s t-distribution and its parameters are evaluated by using the sampled data and updated ada...

In this paper we study a new class of nonlinear GARCH models. Special interest is devoted to models that are similar to previously introduced smooth transition GARCH models except for the novel feature that a lagged value of conditional variance is used as the transition variable. This choice of the transition variable is mainly motivated by the desire to find useful models for highly persisten...

It is well known that volatility asymmetry exists in financial markets. This paper reviews and investigates recently developed techniques for Bayesian estimation and model selection applied to a large group of modern asymmetric heteroskedastic models. These include the GJR-GARCH, threshold autoregression with GARCH errors, threshold GARCH and Double threshold heteroskedastic model with auxiliar...

This paper attempts to investigate the possibility of structural change in tanker freight volatilities pre-and during the financial crisis. The aim is to apply a Markov-switching general autoregressive conditional heteroskedasticity (MS-GARCH) model that identifies and estimates the parameters of high and low volatility states, which are associated with different stages in the business cycle. T...