The present study investigated whether the crypto market is a safe haven. The study argues that during the first wave of the COVID-19 crisis, gold and oil, as typical global commodities, could have been diversifiers. The study developed a unique COVID-19 global composite index that measures COVID-19 pandemic time-variant movements on each day. The study used OLS (ordinary least squares), quantile, and robust regressions to check whether the COVID-19 crisis has had any significant direct influence on the crypto market. The OLS, quantile, and robust regressions estimates confirmed that there was no statistically significant direct influence of the COVID-19 crisis on the crypto market in the first wave period. However, the study found spillovers from risky assets (S&P 500) on the crypto market, with Tether as an exception. Due to this special characteristic, Tether might present a safe haven within the crypto market.

In this study the return spillovers and volatility spillovers between South-East European (SEE) stock markets are investigated as well as vis-à-vis regional and global stock markets (e.g. Europe, Japan, China and the US). By using Frequency Domain Causality approach, the evidence is found of significant spillover effects between markets. The results of study indicate both short-and long-run intra- and inter-regional return and volatility spillovers detected between South-East European (SEE) stock markets and the emerging and the mature markets around the globe, implying limited diversification benefits for international investor portfolios allocated to these markets. Thus, these results should be taken into account by portfolio managers, investors and policy makers before making any investment decision into region’s stock markets. The policy makers and regulators of these markets should consider the nature and frequency of regional and global integration of their stock markets.

The present study is on the five cryptocurrency daily mean return time series linearity dynamics during the Covid-19 period. These cryptocurrencies were chosen based on their influence on the market, primarily driven by its market capitalisation. Tether is included as the most important stable coin on the market, nominally pegged to the U.S. dollar (USD). The reason to investigate it is that there are some inconsistencies in its behaviour as opposed to the other four cryptocurrencies. This study found that the behaviour of Tether cryptocurrency daily average return time series pattern is highly nonlinear and chaotic in nature, whereas the other four cryptocurrencies (namely Bitcoin, Ethereum, XRP and Bitcoin Cash) daily average return time series were found to be linear in nature. To further study Tether’s nonlinear time series rich dynamics, this study deployed one category of the regime switching models popularly known as the threshold regressions. The study estimates fairly suggest that both the threshold autoregression (TAR) and smooth transition autoregressive (STAR) models with lag 1 are adequate to capture the rich nonlinear and chaotic dynamics of Tether’s daily average return time series.

The present study analyses BRICS (Brazil, Russia, India, China, South Africa) capital markets in both time and frequency domain using wavelets. We used artificial neural network techniques to forecast the co-movement among BRICS capital markets. Wavelet coherence and clustering estimates uncover the interesting dynamics among the BRICS capital markets co-movement. A wavelet coherence diagram shows a clear contagion effect among BRICS nations, and it favors short period investments over longer period investments. Overall study estimates indicate that co-movement among BRICS nations significantly differs statistically at different levels. Except for China during the great financial crisis period, significant levels of co-movement were observed between other BRICS nations and that lasted for a longer period of time. A wavelet clustering diagram demonstrates that investors would not get any substantial benefits of diversification by investing only in the ‘Russia and China’ or ‘India and South Africa’ capital markets. Lastly, the study attempts to forecast the BRICS capital market co-movement using two different types of neural networks. Further, RMSE (Root Mean Square Error) values confirm the correctness of the forecasting model. The present study answers the key question, “What kind of integration and globalization framework do we need for sustainable development?”.

This study investigates the relationship between profitability and market power in the banking sector using data from the financial reports of the banks that operated in Serbia and Montenegro, covering the period from the first quarter of 2010 to the last quarter of 2019. In order to investigate this relationship, determinants of bank profitability are split between internal and external. As the external determinants, selected ratios of concentration were calculated and used in order to measure market power. The total of sixteen panel regression models were applied, eight for each country. The results indicate that variations of return on assets and return on equity in Serbia can be explained by the variations of the ratios of concentration. On the other hand, results of the panel regression model applied for the banking sector of Montenegro does not give enough argument to support such explanation, and bank profitability can be explained by bank efficiency to some extent.

This study first investigates the short and long-run effects of exchange rate, output gap and output gap volatility on inflation volatility in Turkey by using the ARDL bounds testing approach. Second, we also examine the causal relationship among these variables by using Toda-Yamamoto and frequency domain causality tests developed by Breitung and Candelon. The results of the ARDL estimates indicate that the exchange rate, output gap and output gap volatility have statistically significant effects on inflation volatility. Also, causality tests results indicate that changes in the exchange rate, output gap volatility, and output gap will have permanent and temporary causal effects on inflation volatility. The policymakers should carefully consider these results to implement appropriate policies to reduce inflation volatility. The finding that the shocks are of temporary nature will have particularly important implications on the policies fighting against the inflation. This study contributes to the empirical inflation literature by identifying both short run and long run effects of the exchange rate and output gap volatility and output gap together, as well as by providing evidence about the structure of the shocks created by these variables on inflation volatility. This study also identifies the sources of temporary and permanent shocks of inflation volatility.