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AbstractThis study tests for calendar anomalies in returns for petroleum and petroleum products via the futures market, specifically, the day-of-the-week (DOW) effect. The energy future contracts in this study are the WTI (West Texas Intermediate), Brent, RBOB (Reformulated Blendstock for Oxygenate Blending) Gasoline, Heating Oil, and Natural Gas. Futures provide a more liquid insight into price movements relative to spot prices, where financial market participants can engage. We ensure the most appropriate price is used by focusing on the most liquid contracts by combining the front two months of the studied commodities nearing expiration. Our research shows that the DOW effect varies across the respective energy commodities; however, for investors engaged in trading these futures, our results may help time their trade decisions.

The Russia-Ukraine military conflict, commencing on February 24, 2022, notably impacted the international community. This study aims to quantify the volatility engendered by the conflict, drawing from the analysis of stock market indices across 40 countries. Time-series returns data from January 1 to December 31, 2022, were examined utilizing EGARCH econometric models. The relationship between volatility and news regarding the conflict was analyzed through a vector autoregression model, and associations between variables were examined using the Granger causality test. Findings suggest that some markets proximate to Ukraine, notably in Hungary, Polassnd Poland, Serbia, Bosnia and Herzegovina, and the Czech Republic, reacted in anticipation of the conflict, days prior to February 24. Remote markets experienced comparatively lower volatility, along with the primary stock markets. Additionally, a decline in volatility was observed as war-related information became available. Notably, the period between March 2 and March 16, 2022, recorded the highest volatility in 21 countries. Conversely, the value markets of the US, China, Japan, the UK, and Germany navigated the analyzed period with lower volatilities. These results demonstrate that conflict shocks influence stock markets globally. The implications of these findings are significant for investors, decision-makers, portfolio managers, investment funds, and central banks. [ABSTRACT FROM AUTHOR]

AbstractThe Russia-Ukraine military conflict, commencing on February 24, 2022, notably impacted the international community. This study aims to quantify the volatility engendered by the conflict, drawing from the analysis of stock market indices across 40 countries. Time-series returns data from January 1 to December 31, 2022, were examined utilizing EGARCH econometric models. The relationship between volatility and news regarding the conflict was analyzed through a vector autoregression model, and associations between variables were examined using the Granger causality test. Findings suggest that some markets proximate to Ukraine, notably in Hungary, Polassnd Poland, Serbia, Bosnia and Herzegovina, and the Czech Republic, reacted in anticipation of the conflict, days prior to February 24. Remote markets experienced comparatively lower volatility, along with the primary stock markets. Additionally, a decline in volatility was observed as war-related information became available. Notably, the period between March 2 and March 16, 2022, recorded the highest volatility in 21 countries. Conversely, the value markets of the US, China, Japan, the UK, and Germany navigated the analyzed period with lower volatilities. These results demonstrate that conflict shocks influence stock markets globally. The implications of these findings are significant for investors, decision-makers, portfolio managers, investment funds, and central banks.

This study tests for calendar anomalies in returns for petroleum and petroleum products via the futures market, specifically, the day-of-the-week (DOW) effect. The energy future contracts in this study are the WTI (West Texas Intermediate), Brent, RBOB (Reformulated Blendstock for Oxygenate Blending) Gasoline, Heating Oil, and Natural Gas. Futures provide a more liquid insight into price movements relative to spot prices, where financial market participants can engage. We ensure the most appropriate price is used by focusing on the most liquid contracts by combining the front two months of the studied commodities nearing expiration. Our research shows that the DOW effect varies across the respective energy commodities; however, for investors engaged in trading these futures, our results may help time their trade decisions. [ABSTRACT FROM AUTHOR]

This paper examines the effect of real-time global geopolitical risks (GPRs), acts (GPAs), and threats (GPTs) indices on monthly returns and volatility of several American commodity futures. By modeling volatility via an Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH), we provide evidence that GPRs and GPTs do not only impact but trigger adverse effects on the returns of crude oil, gold, platinum, and silver, while GPAs negatively affect the returns of crude oil, heating oil, platinum, and sugar futures. Furthermore, GPTs have a weak positive effect on corn futures volatility. Overall, our findings provide portfolio diversification benefits by showing how the impact of global GPRs, GPAs and GPTs on portfolio returns could be mitigated.

This paper examines the effect of real-time global geopolitical risks (GPRs), acts (GPAs), and threats (GPTs) indices on monthly returns and volatility of several American commodity futures. By modeling volatility via an Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH), we provide evidence that GPRs and GPTs do not only impact but trigger adverse effects on the returns of crude oil, gold, platinum, and silver, while GPAs negatively affect the returns of crude oil, heating oil, platinum, and sugar futures. Furthermore, GPTs have a weak positive effect on corn futures volatility. Overall, our findings provide portfolio diversification benefits by showing how the impact of global GPRs, GPAs and GPTs on portfolio returns could be mitigated. [ABSTRACT FROM AUTHOR]

The Black’s leverage effect hypothesis postulates that a negative stock return innovation increases the financial leverage of a firm since the value of equity decreases at a given level of debt, which, in turn, creates a higher equity return volatility in the future. The paper is aimed at investigating the authenticity of the Black’s leverage effect hypothesis and the relationship between negative stock returns and the financial leverage of the UK oil and gas stocks from 2004 to 2015. For each stock, exponential generalised autoregressive conditional heteroscedasticity model was estimated using Fama–French–Carhart 4-factor asset pricing model to extract the difference between the effects of negative and positive stock return innovations, regarded as leverage effect. The leverage effect parameter was further regressed on the financial leverage ratios of the book value of long-term debt to total assets, interest expenses to total assets and long-term debt to market value of equity to examine whether variation in the leverage parameter was as a result of variation in the firm’s financial leverage. The findings of the study show that Fama-French-Carhart four risk factors of market, size effect, value and momentum were significant in the stock returns of most of the oil and gas companies. The mixed results in the significance level of the factors were attributed to the differences in individual firm characteristics. An evidence of leverage effect was also found in all the oil and gas stock returns but no evidence to suggest it was derived from the changes in the financial leverage of the companies. The implication of these findings for financial managers in the oil and gas industry was that while asset pricing frameworks such as CAPM and its extensions are relevant in determining oil stock returns, the level of gearing is irrelevant, albeit it has been recognised as one of the determinants of the firm’s level of risk.

This paper examines the determinants of the South African rand/US dollar (ZAR/USD) exchange rate based on demand and supply analysis. Applying the EGARCH method, the paper finds that the ZAR/USD exchange rate is positively associated with the South African government bond yield, US real GDP, the US stock price and the South African inflation rate and negatively influenced by the 10-year US government bond yield, South African real GDP, the South African stock price, and the US inflation rate. The adoption of a free floating exchange rate regime has reduced the value of the rand vs. the US dollar.

This paper investigates linkages among equity market returns and volatility spillovers in the following countries: Germany, United Kingdom, China, Russia, and Turkey. MARMA, GARCH, GARCH-in-mean, and exponential GARCH (EGARCH) methodologies are applied to daily data on country exchange-traded funds (ETF) based on the MSCI indices from 31 March 2011 to 11 March 2016. The results of the analysis show the existence of significant co-movements of returns among the countries in the sample. ETF returns in Germany, UK, and Russia affect returns in all of the other sample countries. Implications of these findings are explored in terms of portfolio diversification. In addition, the highest volatilities are exhibited by Russia and Turkey. On the other hand, the UK and the Chinese markets have the lowest volatilities. Also, there is a strong evidence of volatility spillovers. All of the countries in the sample, with the exception of UK and Turkey, experience volatility spillovers from other markets. Finally, because of the risk-return trade-off, we analyzed the effect of volatility of the market on its returns and found that only in the UK volatility of the market had a positive effect on its future returns: that an increase in volatility leads to a rise in future ETF returns in the UK.

The Black’s leverage effect hypothesis postulates that a negative stock return innovation increases the financial leverage of a firm since the value of equity decreases at a given level of debt, which, in turn, creates a higher equity return volatility in the future. The paper is aimed at investigating the authenticity of the Black’s leverage effect hypothesis and the relationship between negative stock returns and the financial leverage of the UK oil and gas stocks from 2004 to 2015. For each stock, exponential generalised autoregressive conditional heteroscedasticity model was estimated using Fama–French–Carhart 4-factor asset pricing model to extract the difference between the effects of negative and positive stock return innovations, regarded as leverage effect. The leverage effect parameter was further regressed on the financial leverage ratios of the book value of long-term debt to total assets, interest expenses to total assets and long-term debt to market value of equity to examine whether variation in the leverage parameter was as a result of variation in the firm’s financial leverage. The findings of the study show that Fama-French-Carhart four risk factors of market, size effect, value and momentum were significant in the stock returns of most of the oil and gas companies. The mixed results in the significance level of the factors were attributed to the differences in individual firm characteristics. An evidence of leverage effect was also found in all the oil and gas stock returns but no evidence to suggest it was derived from the changes in the financial leverage of the companies. The implication of these findings for financial managers in the oil and gas industry was that while asset pricing frameworks such as CAPM and its extensions are relevant in determining oil stock returns, the level of gearing is irrelevant, albeit it has been recognised as one of the determinants of the firm’s level of risk. [ABSTRACT FROM AUTHOR]

This paper investigates linkages among equity market returns and volatility spillovers in the following countries: Germany, United Kingdom, China, Russia, and Turkey. MARMA, GARCH, GARCH-in-mean, and exponential GARCH (EGARCH) methodologies are applied to daily data on country exchange-traded funds (ETF) based on the MSCI indices from 31 March 2011 to 11 March 2016. The results of the analysis show the existence of significant co-movements of returns among the countries in the sample. ETF returns in Germany, UK, and Russia affect returns in all of the other sample countries. Implications of these findings are explored in terms of portfolio diversification. In addition, the highest volatilities are exhibited by Russia and Turkey. On the other hand, the UK and the Chinese markets have the lowest volatilities. Also, there is a strong evidence of volatility spillovers. All of the countries in the sample, with the exception of UK and Turkey, experience volatility spillovers from other markets. Finally, because of the risk-return trade-off, we analyzed the effect of volatility of the market on its returns and found that only in the UK volatility of the market had a positive effect on its future returns: that an increase in volatility leads to a rise in future ETF returns in the UK. [ABSTRACT FROM AUTHOR]

This paper examines the determinants of the South African rand/US dollar (ZAR/USD) exchange rate based on demand and supply analysis. Applying the EGARCH method, the paper finds that the ZAR/USD exchange rate is positively associated with the South African government bond yield, US real GDP, the US stock price and the South African inflation rate and negatively influenced by the 10-year US government bond yield, South African real GDP, the South African stock price, and the US inflation rate. The adoption of a free floating exchange rate regime has reduced the value of the rand vs. the US dollar. [ABSTRACT FROM AUTHOR]