The goal of our study is to examine the impact of natural disasters on the South Pacific Stock Ex... more The goal of our study is to examine the impact of natural disasters on the South Pacific Stock Exchange. We use daily time-series data for Fiji’s stock market for the period 2000-2019. Our empirical framework is based on three factor regression models, namely the market model, the Fama and French three-factor model, and the Fama and French five-factor model. We find evidence that natural disasters in Fiji reduce abnormal returns in the most relevant five-factor model. Additionally, we provide evidence that different types of natural disasters have heterogeneous effects on Fiji’s stock market. Our findings are further supported by a robustness check.
This paper uses 15‐minute exchange rate returns data for the six most liquid currencies (i.e., th... more This paper uses 15‐minute exchange rate returns data for the six most liquid currencies (i.e., the Australian dollar, British pound, Canadian dollar, Euro, Japanese yen, and Swiss franc) vis‐a‐vis the United States dollar to examine whether a GARCH model augmented with higher moments (HM‐GARCH) performs better than a traditional GARCH (TG) model. Two findings are unraveled. First, the inclusion of odd/even moments in modeling the return/variance improves the statistical performance of the HM‐GARCH model. Second, trading strategies that extract buy and sell trading signals based on exchange rate forecasts from HM‐GARCH models are more profitable than those that depend on TG models.
This study investigates the determinants of carbon dioxide emissions (CO 2 ) for a global panel c... more This study investigates the determinants of carbon dioxide emissions (CO 2 ) for a global panel consisting of 69 countries using a dynamic panel data model. To make the panel data analysis more homogenous, we also investigate the determinants of CO 2 emissions for a number of sub-panels. These sub-panels are constructed based on the income level of countries. In this way, we end up with three income panels; namely, high income, middle income, and low income panels. The time component of our dataset is 1985-2005 inclusive. Our main findings are that trade openness, per capita GDP, and energy consumption, proxied by per capita electric power consumption and per capita total primary energy consumption, have positive effects on CO 2 emissions. Urbanisation is found to have a negative impact on CO 2 emissions in high income, middle income, and low income panels. For the global panel, only GDP per capita and per capita total primary energy consumption are found to be statistically significant determinants of CO 2 emission, while urbanisation, trade openness, and per capita electric power consumption have negative effects on the CO 2 emissions.
This study investigates the determinants of carbon dioxide emissions (CO 2 ) for a global panel c... more This study investigates the determinants of carbon dioxide emissions (CO 2 ) for a global panel consisting of 69 countries using a dynamic panel data model. To make the panel data analysis more homogenous, we also investigate the determinants of CO 2 emissions for a number of sub-panels. These sub-panels are constructed based on the income level of countries. In this way, we end up with three income panels; namely, high income, middle income, and low income panels. The time component of our dataset is 1985-2005 inclusive. Our main findings are that trade openness, per capita GDP, and energy consumption, proxied by per capita electric power consumption and per capita total primary energy consumption, have positive effects on CO 2 emissions. Urbanisation is found to have a negative impact on CO 2 emissions in high income, middle income, and low income panels. For the global panel, only GDP per capita and per capita total primary energy consumption are found to be statistically significant determinants of CO 2 emission, while urbanisation, trade openness, and per capita electric power consumption have negative effects on the CO 2 emissions.
In this study, we use dynamic panel data models to examine the impact of electricity and non-elec... more In this study, we use dynamic panel data models to examine the impact of electricity and non-electricity variables on economic growth for a global panel consisting of 66 countries. The time component of our dataset is 1986-2005 inclusive. We also estimate this relationship for four regional panels; namely, East/ South Asian and the Pacific region, Europe and Central Asian region, Latin America and Caribbean region, and Sub-Saharan, North Africa and Middle Eastern region. In total, we use six proxies for energy. The empirical analysis is based on a sound theoretical framework, in that we draw on growth theory and augment the classical growth model, which consists of inflation, capital stock, labour force and trade, with energy. Generally, the results on the impact of energy are mixed.
Review of Pacific Basin Financial Markets and Policies, 2015
In this paper, we examine evidence of herding behavior on the Chinese stock market. Our main find... more In this paper, we examine evidence of herding behavior on the Chinese stock market. Our main findings are as follows. First, we find strong evidence of herding behavior on both the Shanghai and Shenzhen stock exchanges. Second, we document evidence of asymmetric herding behavior with greater magnitude of herding behavior on up markets than on down markets. Third, our findings suggest that herding behavior is sectorspecific and predominant in the industrial and properties sectors. Finally, we unravel strong evidence suggesting that herding behavior is time-varying and in some sectors time-varying herding behavior is more prevalent than in other sectors.
We develop country-level governance indices using governance risk factors and examine whether or ... more We develop country-level governance indices using governance risk factors and examine whether or not such country-level governance can predict stock market returns. Given the heterogeneous nature of governance in different countries, this study provides evidence of stock market return predictability. We find that country-level governance only predicts stock market returns of countries characterised by poor governance quality. For countries with welldeveloped governance, there is no evidence that governance predicts returns. Our findings indicate that investors in countries with weak governance can utilise information contained in governance measures to devise profitable trading strategies.
ABSTRACT In this paper we take the forward premium and exchange rate literature forward by asking... more ABSTRACT In this paper we take the forward premium and exchange rate literature forward by asking whether data frequency matters in that relationship. We use four frequencies of data, namely, quarterly, monthly, weekly and daily. We find that data frequencies matter both statistically and economically. More specifically, we document that investors prefer the forward premium model over a constant returns model in most countries when models are estimated using daily, weekly, and quarterly data, but not when using monthly data.
Journal of International Financial Markets, Institutions and Money, 2015
ABSTRACT In this paper we investigate how differently stock returns of oil producers and oil cons... more ABSTRACT In this paper we investigate how differently stock returns of oil producers and oil consumers are affected from oil price changes. We find that stock returns of oil producers are affected positively by oil price changes regardless of whether oil price is increasing or decreasing. For oil consumers, oil price changes do not affect all consumer sub-sectors and where it does, this effect is heterogeneous. We find that oil price returns have an asymmetric effect on stock returns for most sub-sectors. We devise simple trading strategies and find that while both consumers and producers of oil can make statistically significant profits, investors in oil producer sectors make relatively more profits than investors in oil consumer sectors.
ABSTRACT The European Carbon Emissions Trading Scheme introduced in 2005 has led to both spot and... more ABSTRACT The European Carbon Emissions Trading Scheme introduced in 2005 has led to both spot and futures market trading of carbon emissions. However, despite seven years of trading, we have no knowledge on how profitable carbon emissions trading is. In this paper, we first test whether carbon forward returns predict carbon spot returns. We find strong evidence on both in-sample and out-of-sample predictability. Based on this evidence, we forecast carbon spot returns using both carbon forward returns and a constant. We consider a mean-variance investor and a CRRA investor, and show that they have higher utility and can make more statistically significant profits by following forecasts generated from the forward returns model than from a constant returns model.
In this paper, we test whether January and turn-of-the-month (TOM) affect firm returns and firm r... more In this paper, we test whether January and turn-of-the-month (TOM) affect firm returns and firm return volatility differently depending on their sector and size. We use time series data for 560 firms listed on the NYSE and find evidence of both January and TOM affecting returns and return volatility of firms. The effects are, however, different for different firms and are dependent on the sectoral location of firms and on firm sizes. These findings imply that January and TOM have an heterogeneous effect on firm returns and firm return volatility.
The goal of our study is to examine the impact of natural disasters on the South Pacific Stock Ex... more The goal of our study is to examine the impact of natural disasters on the South Pacific Stock Exchange. We use daily time-series data for Fiji’s stock market for the period 2000-2019. Our empirical framework is based on three factor regression models, namely the market model, the Fama and French three-factor model, and the Fama and French five-factor model. We find evidence that natural disasters in Fiji reduce abnormal returns in the most relevant five-factor model. Additionally, we provide evidence that different types of natural disasters have heterogeneous effects on Fiji’s stock market. Our findings are further supported by a robustness check.
This paper uses 15‐minute exchange rate returns data for the six most liquid currencies (i.e., th... more This paper uses 15‐minute exchange rate returns data for the six most liquid currencies (i.e., the Australian dollar, British pound, Canadian dollar, Euro, Japanese yen, and Swiss franc) vis‐a‐vis the United States dollar to examine whether a GARCH model augmented with higher moments (HM‐GARCH) performs better than a traditional GARCH (TG) model. Two findings are unraveled. First, the inclusion of odd/even moments in modeling the return/variance improves the statistical performance of the HM‐GARCH model. Second, trading strategies that extract buy and sell trading signals based on exchange rate forecasts from HM‐GARCH models are more profitable than those that depend on TG models.
This study investigates the determinants of carbon dioxide emissions (CO 2 ) for a global panel c... more This study investigates the determinants of carbon dioxide emissions (CO 2 ) for a global panel consisting of 69 countries using a dynamic panel data model. To make the panel data analysis more homogenous, we also investigate the determinants of CO 2 emissions for a number of sub-panels. These sub-panels are constructed based on the income level of countries. In this way, we end up with three income panels; namely, high income, middle income, and low income panels. The time component of our dataset is 1985-2005 inclusive. Our main findings are that trade openness, per capita GDP, and energy consumption, proxied by per capita electric power consumption and per capita total primary energy consumption, have positive effects on CO 2 emissions. Urbanisation is found to have a negative impact on CO 2 emissions in high income, middle income, and low income panels. For the global panel, only GDP per capita and per capita total primary energy consumption are found to be statistically significant determinants of CO 2 emission, while urbanisation, trade openness, and per capita electric power consumption have negative effects on the CO 2 emissions.
This study investigates the determinants of carbon dioxide emissions (CO 2 ) for a global panel c... more This study investigates the determinants of carbon dioxide emissions (CO 2 ) for a global panel consisting of 69 countries using a dynamic panel data model. To make the panel data analysis more homogenous, we also investigate the determinants of CO 2 emissions for a number of sub-panels. These sub-panels are constructed based on the income level of countries. In this way, we end up with three income panels; namely, high income, middle income, and low income panels. The time component of our dataset is 1985-2005 inclusive. Our main findings are that trade openness, per capita GDP, and energy consumption, proxied by per capita electric power consumption and per capita total primary energy consumption, have positive effects on CO 2 emissions. Urbanisation is found to have a negative impact on CO 2 emissions in high income, middle income, and low income panels. For the global panel, only GDP per capita and per capita total primary energy consumption are found to be statistically significant determinants of CO 2 emission, while urbanisation, trade openness, and per capita electric power consumption have negative effects on the CO 2 emissions.
In this study, we use dynamic panel data models to examine the impact of electricity and non-elec... more In this study, we use dynamic panel data models to examine the impact of electricity and non-electricity variables on economic growth for a global panel consisting of 66 countries. The time component of our dataset is 1986-2005 inclusive. We also estimate this relationship for four regional panels; namely, East/ South Asian and the Pacific region, Europe and Central Asian region, Latin America and Caribbean region, and Sub-Saharan, North Africa and Middle Eastern region. In total, we use six proxies for energy. The empirical analysis is based on a sound theoretical framework, in that we draw on growth theory and augment the classical growth model, which consists of inflation, capital stock, labour force and trade, with energy. Generally, the results on the impact of energy are mixed.
Review of Pacific Basin Financial Markets and Policies, 2015
In this paper, we examine evidence of herding behavior on the Chinese stock market. Our main find... more In this paper, we examine evidence of herding behavior on the Chinese stock market. Our main findings are as follows. First, we find strong evidence of herding behavior on both the Shanghai and Shenzhen stock exchanges. Second, we document evidence of asymmetric herding behavior with greater magnitude of herding behavior on up markets than on down markets. Third, our findings suggest that herding behavior is sectorspecific and predominant in the industrial and properties sectors. Finally, we unravel strong evidence suggesting that herding behavior is time-varying and in some sectors time-varying herding behavior is more prevalent than in other sectors.
We develop country-level governance indices using governance risk factors and examine whether or ... more We develop country-level governance indices using governance risk factors and examine whether or not such country-level governance can predict stock market returns. Given the heterogeneous nature of governance in different countries, this study provides evidence of stock market return predictability. We find that country-level governance only predicts stock market returns of countries characterised by poor governance quality. For countries with welldeveloped governance, there is no evidence that governance predicts returns. Our findings indicate that investors in countries with weak governance can utilise information contained in governance measures to devise profitable trading strategies.
ABSTRACT In this paper we take the forward premium and exchange rate literature forward by asking... more ABSTRACT In this paper we take the forward premium and exchange rate literature forward by asking whether data frequency matters in that relationship. We use four frequencies of data, namely, quarterly, monthly, weekly and daily. We find that data frequencies matter both statistically and economically. More specifically, we document that investors prefer the forward premium model over a constant returns model in most countries when models are estimated using daily, weekly, and quarterly data, but not when using monthly data.
Journal of International Financial Markets, Institutions and Money, 2015
ABSTRACT In this paper we investigate how differently stock returns of oil producers and oil cons... more ABSTRACT In this paper we investigate how differently stock returns of oil producers and oil consumers are affected from oil price changes. We find that stock returns of oil producers are affected positively by oil price changes regardless of whether oil price is increasing or decreasing. For oil consumers, oil price changes do not affect all consumer sub-sectors and where it does, this effect is heterogeneous. We find that oil price returns have an asymmetric effect on stock returns for most sub-sectors. We devise simple trading strategies and find that while both consumers and producers of oil can make statistically significant profits, investors in oil producer sectors make relatively more profits than investors in oil consumer sectors.
ABSTRACT The European Carbon Emissions Trading Scheme introduced in 2005 has led to both spot and... more ABSTRACT The European Carbon Emissions Trading Scheme introduced in 2005 has led to both spot and futures market trading of carbon emissions. However, despite seven years of trading, we have no knowledge on how profitable carbon emissions trading is. In this paper, we first test whether carbon forward returns predict carbon spot returns. We find strong evidence on both in-sample and out-of-sample predictability. Based on this evidence, we forecast carbon spot returns using both carbon forward returns and a constant. We consider a mean-variance investor and a CRRA investor, and show that they have higher utility and can make more statistically significant profits by following forecasts generated from the forward returns model than from a constant returns model.
In this paper, we test whether January and turn-of-the-month (TOM) affect firm returns and firm r... more In this paper, we test whether January and turn-of-the-month (TOM) affect firm returns and firm return volatility differently depending on their sector and size. We use time series data for 560 firms listed on the NYSE and find evidence of both January and TOM affecting returns and return volatility of firms. The effects are, however, different for different firms and are dependent on the sectoral location of firms and on firm sizes. These findings imply that January and TOM have an heterogeneous effect on firm returns and firm return volatility.
Uploads
Papers by Susan Sharma