This study investigates the dependence and risk spillovers in the short-, medium- and long-terms between natural gas (NG), crude oil and stock markets of top energy producer countries (Russia, Ukraine and US) and consumer countries (China, India and EU members). Using the wavelet coherence...

This paper investigates herding behavior and the connection between herding behavior and investor sentiment. We apply a Cross-Sectional Absolute Deviation (CSAD) approach and the quantile regression method to capture herding behavior in the KOSPI and KOSDAQ stock markets. The analysis results...

This study investigates the spillover effect of price returns and volatility between ADRs and their underlying Korean stocks, employing a Granger causality test and a bivariate GARCH model. First, the empirical results of Granger causality test suggest bi-directional transmission of price...

This study investigates the effects of volatility spillovers among five Asian stock markets (China, Hong Kong, Korea, Singapore, and Taiwan) and examines how the global financial crisis of 2008 has influenced volatility transmission among Asian stock markets. The results from a VAR(1)-bivariate...

This study proposes a GARCH copula quantile regression model to capture the downside and upside tail dependence between oil price change and stock market returns at different risk levels. In the model, ten copulas are provided to measure the nonlinearity of the tail dependence with the marginal...

We investigate the impact of extreme weather conditions on the stock market returns of the Hong Kong Stock Exchange and Shenzhen Exchange. For the weather conditions, we apply dummy variables generated by applying a moving average and moving standard deviation. Our study provides two interesting...

In this study, the dependence between Bitcoin (BTC) and economic policy uncertainty (EPU) of USA and China is estimated by applying the latest methodology of quantile cross-spectral dependence. Daily data comprising a total of 1947 observations and covering the period of 1 October 2013 to 31...