Purpose The paper evaluates the cross-transmission of returns and volatility shocks between Nigeria South Africa stock markets to infer extent interdependence two markets. also makes inference optimal portfolio weights holding assets in Design/methodology/approach uses an asymmetric vector autoregressive-exogenous generalised autoregressive conditional heteroscedasticity (VAR-X GARCH) model ass...

Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mini...

Currently, the world suffers from COVID-19 pandemic, which affects almost every aspect of daily life, giving rise to recession and affecting prices crude oil. The study aims model high uncertainty volatility as well forecast oil during pandemic. One econometric applied in this is Generalised Autoregressive Conditional Heteroscedasticity (GARCH) that allows more accurate appropriate statistical ...

Dispersion measurement and tuning constants are critical aspects of a model's robustness efficiency. However, in the presence outliers, standard deviation is not reliable measure dispersion Huber's weight. This research aimed to assess efficacy Huber weight function terms constant. The simulation study was conducted on hybrid autoregressive (AR) model generalized conditional heteroscedasticity ...

The economic and financial chaos caused by COVID-19 has been a discussion topic since the beginning of 2020. This study intends to provide parallel comparison volatility change external shock persistence Islamic conventional stock indexes Pakistan Stock Exchange. daily index was extracted from Eikon Thomson Reuters for Jan 2018 April 2021, which further divided in three periods, i.e., full, pre...

Economic and financial time series typically exhibit time varying conditional (given the past) standard deviations and correlations. The conditional standard deviation is also called the volatility. Higher volatilities increase the risk of assets, and higher conditional correlations cause an increased risk in portfolios. Therefore, models of time varying volatilities and correlations are essent...

This paper employs a bivaraite vector autoregressive-generalized autoregressive conditional heteroscedasticity (VAR-GARCH) model recently developed by Ling and McAleer (2003) to examine the impact of oil price fluctuations on stock market returns in the Kingdom of Saudi Arabia over the period from January 1, 2007 to December 31, 2011. The proposed model is estimated using maximum likelihood met...

return maximization or risk minimization is goal in portfolio optimization based on mean variance theory. the structure of correlation matrices and individual variance of each asset are two main factors in optimization with risk minimization object. it’s necessary to use appropriate variance and correlation coefficient for time series with clustering volatilities feature, too. in this research,...

This paper presents an empirical analysis of volatility and contagion across 19 emerging and developed stock markets in the 1990s. First, using an efficient estimate of unconditional stock return volatility we show that contemporaneous return and volatility correlation across stock markets have increased substantially in the 1990s. Second, using simple rolling regressions and goodness of fit me...

The evolution of financial markets is a complicated real-world phenomenon that ranks at the top in terms of difficulty of modeling and/or prediction. One reason for this difficulty is the well-documented nonlinearity that is inherently at work. The state-of-the-art on the nonlinear modeling of financial returns is given by the popular ARCH (Auto-Regressive Conditional Heteroscedasticity) models...