Narrow Results

In this article we examine the mean-reverting property in the Spanish stock market prices by means of looking at its order of integration. We use several semiparametric procedures proposed by P. M. Robinson in a number of papers. The results show that, though the unit root hypothesis cannot be rejected in the log of the stock prices, the estimated order of integration in the first differenced series, (i.e. in the stock market returns), is slightly below zero, implying that there exists a small degree of mean reversion in the behaviour of prices.

The onset of the novel coronavirus pandemic (COVID-19) and previous financial and currency crises have heightened interest in understanding the nature of the interaction of stock market and exchange rate volatility. This paper aims to investigate the interdependence and volatility transmissions between the stock and foreign exchange markets for South Africa over the period of 1979:01–2021:08, including the effect the COVID-19 pandemic has had on the interdependence and volatility transmissions. Through the use of bivariate Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) modeling, the empirical outcomes from this study provide strong evidence in support of the “stock-orientated” approach, where significant price and volatility spillovers propagate from the stock market into the foreign exchange market, whilst evidence of the “flow-orientated” approach is seen in the second moment and significant shock and asymmetric spillovers from the exchange to stock market are found. The results support the asymmetric and long-range persistence volatility spillover effect and show strong evidence of contagion between stock and foreign exchange markets. These spillovers became more pronounced during the COVID-19 pandemic, confirming heightened contagion in these markets during the periods of crisis. The results heed important implications for not only policymakers who are concerned by the contagion across financial markets and better regulations of these markets to promote economic growth, but also investors and fund managers who seek to hedge investment risks in South Africa.

The study investigates volatility transmissions of major financial market indices found in the Extended Greater China Region (EGCR): the Shanghai Stock Exchange Index (SSEI), the Hang Seng Stock Exchange Index (HSEI), the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX), and the Singapore Stock Exchange Index (STI). This paper utilizes three Multivariate Generalized Autoregressive Conditional Heteroskedasticity (MGARCH) models to determine variance persistence in the EGCR. The MGARCH approach applies the Baba–Engle–Kraft–Kroner (BEKK) model and the dynamic conditional correlation (DCC) and constant conditional correlation (CCC) estimations. This research found that the SSEI consistently has the highest volatility among the stock markets in the EGCR, and this can be explained by the poor acknowledgment of minority shareholders’ rights or having a weak so-called “common-law” regime. The paper also found that volatilities in the EGCR are determined strongly by their own lagged values more than the product of lagged cross-products of shocks. This means that financial market movements in the EGCR are still strongly influenced by internal factors more than the external influences. The paper contributes to the literature by understanding the potential changes in volatility relationships in low- and high-volatility regimes of the EGCR, which can be used to improve risk management practices and asset allocation techniques in the region.

This paper investigates the time-varying co-movements between stock market returns and oil price shocks, for both oil-importing and oil-exporting countries. To achieve this, we use data from 1998 until 2013 and employ a Scalar-BEKK model. Our findings are as follows: (i) the correlation between oil price shocks and index returns are showing some differences depending on whether a country is oil-importer or oil-exporter, (ii) the correlations are industry-specific and shock-specific, (iii) the aggregate demand shocks generate moderate positive correlations with stock market returns until 2011, (iv) stock market index returns have low to zero correlation with the supply-side shocks and (v) oil specific demand shocks have a moderate positive correlation with all indices in the post-2006 period. Our results have important implication for investor, as well as, policy makers.

The aim of this research is to examine how the daily growth in COVID-19 confirmed cases and deaths in 15 African nations affects stock market returns, employing both time series and panel methods. This study uses robust ordinary least squares (ROLS) and dynamic ordinary least squares (DOLS) for time series. It uses Pooled OLS, Fixed Effects, Feasible Generalized Least Squares, Two-Stage Least Squares (2SLS), and panel vector autoregressive (PVAR) with respect to panel data. These methodologies help in addressing some econometric issues regarding the relationship between COVID-19 confirmed cases, deaths and stock returns in the panel of 15 African nations, which enhances our research and findings. The effects of confirmed COVID-19 cases and deaths on stock returns are not uniform among countries, according to the results of a time series analysis. Precisely, the rise of COVID-19 confirmed cases has had a detrimental impact on stock returns in nations including Botswana, Cote d’Ivoire, Morocco, Uganda, and Zambia. Similarly, COVID-19 confirmed deaths have a detrimental impact on the stock returns of nations like Botswana, Morocco, and Zambia. Even though COVID-19 confirmed cases have a negative impact on stock returns in the 15 African countries that make up the panel study, this effect is not statistically significant except when FGLS is applied. In a similar vein, stock returns in African nations are not significantly impacted by COVID-19 confirmed deaths. The results of FEVD support these findings. According to IRF findings, stock returns respond unfavorably to the shock of COVID-19 confirmed cases. The negative, nevertheless, quickly subsided as stock returns bounced back to positive returns until eventually reaching equilibrium. The stock returns, on the other hand, initially respond favorably to the shock of the COVID-19 confirmed deaths, then take a negative turn before returning to normal returns. Our study emphasizes the significance of examining each country’s socioeconomic response to the COVID-19 epidemic rather than grouping countries together.

There is twofold contribution in this paper. First, by using monthly data for 16 industrialized countries for the period 1973–2011 we find evidence of time-varying cointegration relationship between effective exchange rates and national stock market indices. Second, we present that the cointegration relationship affects exchange rate exposure. We propose that the exchange rate exposure effect changes when the connection between the exchange rate and stock market emerges. This is a new result and reflects importance of these markets’ joint role in international risk sharing.

This research paper aims to examine the predictability of the Spanish Stock Market returns. Earlier studies suggest that stock market returns in developed countries can be predicted with a noise term but this study has specifically covered two time horizons; one pre-crisis period and the other one current crisis period to evaluate the stock market returns predictability. Since mean returns cannot prove all the time to be efficient predictor, variance of such returns do, hence various autoregressive models have been used to test the existence of persisting volatility in the Spanish Stock Market. The empirical results show that higher order of autoregressive models such as ARCH(5) and GARCH(2, 2) can be used to predict future risk in Spanish Stock Market both in pre-crisis and current crisis period. The paper also reveals that there is a positive correlation between Spanish Stock Market returns and the conditional standard deviations as produced by ARCH(5) and GARCH(2, 2), implying that the models have some success in predicting future risk on Spanish Stock Market. The predictability of stock market returns during crisis period is not found to be affected contrary though the degree of predictability may be.