Gul Huyuguzel Kisla | Ege University (original) (raw)
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Papers by Gul Huyuguzel Kisla
International Journal of Energy Economics and Policy
This paper examines the effects of oil and natural gas prices on the oil and gas sectors of the B... more This paper examines the effects of oil and natural gas prices on the oil and gas sectors of the BRIC countries (Brazil, Russia, India, and China) over the period over from 20013 to 2022. Unlike previous studies, it employs a time-varying capital asset pricing model based on the estimation of state-space mode. In brief, the findings highlight significant changes in the asset-pricing model parameters across all countries, indicating the limitations of using time-invariant estimates. Specifically, Brazil shows the highest volatility in oil price risk, followed by Russia, both being oil-exporting countries, while market beta values remain relatively stable. Time-varying estimates further suggest that natural gas parameters are relatively lower and less significant than those of oil prices. The Russian-Ukrainian conflict's energy crisis adversely affects the performance of oil and gas sectoral stock returns. This war has had a negative and significant impact on China's oil-gas st...
Computational Economics
The level of financial risk spread out to the world during the COVID-19 pandemic has shown that n... more The level of financial risk spread out to the world during the COVID-19 pandemic has shown that none of the countries are immune to financial uncertainty and the vast changes it brings to economic stability. The contagiousness of sovereign risk is a result of the interdependent structure of countries’ financial networks. Yet the analysis of sovereign CDS risk spread using the network view is both new and limited. With this study, we want to use the network view to prove the interconnectedness of the financial systems in Europe and its effect on the spread of the risk throughout the COVID-19 pandemic. The objective of this study is threefold: First, using the Bayesian networks learned from the daily CDS values of 17 European Union countries, we demonstrate the dependent network structure of countries and the movement of the sovereign risk over this network with a cascading behavior. Second, we explore how the probabilistic dependency structure changes over the different phases of the COVID-19 pandemic, leading to alterations on the behavior of the sovereign risk spread. The previous studies on the sovereign risk spread during the COVID-19 pandemic employs the data over the whole period of the pandemic. However, during the pandemic the behavior of the spread was changing, and to capture that change the consideration of shorter intervals becomes crucial. Therefore, in this study, the COVID-19 crisis period from December 2019 until February 2021 is divided into five phases of 3-month time intervals. As the third and last objective, this study intends to be a roadmap for policy makers as well as for researchers to understand the true nature and connectedness of sovereign risk transmissions. For that purpose, we provide a benchmark procedure for the evaluation of the sovereign risk of countries using Bayesian networks which involves a comprehensive analysis involving several steps conducted on each of the learned Bayesian networks for the different phases of the pandemic. In terms of policy implications, this study aims to be helpful for investors that want to diversify sovereign risk in their bond portfolios and be explanatory for the changing behavior of the risk spread during crisis periods. Moreover, this study exemplifies the use of artificial intelligence methods to understand the working mechanism of economic systems.
Resources Policy, Dec 1, 2020
Sustainability and climate change, Aug 1, 2022
Journal of Asset Management, Mar 11, 2022
Tourism Analysis
This paper examines the effects of the COVID-19 pandemic on the travel-tourism stock markets. Spe... more This paper examines the effects of the COVID-19 pandemic on the travel-tourism stock markets. Specifically, it considers the five most visited countries: France, Spain, the US, China, and Italy. Unlike previous studies, it estimates time-varying VAR (TVP-VAR) models, including daily observations of confirmed COVID-19 cases, economic activity, CDS spreads and the returns of travel-tourism sectors. In brief, our findings indicate that the effects of COVID-19 vary across countries, as well as over time. Specifically, increasing numbers of cases initially had a negative and significant impact on the travel-tourism stock returns of all countries. However, this effect had become insignificant by early April 2020. The travel-tourism markets of the European countries were seen to be more heavily affected by COVID-19 when compared to China and the US, with China seeming to have been the least affected country of all. Overall, our results are essential in understanding the impact of the COVID...
The Economics of Gender Equality in the Labour Market, 2021
SSRN Electronic Journal, 2021
Journal of Asset Management, 2022
ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, 2021
The effects of oil price exposure of oil-gas sectors of the countries largely affected by Covid-1... more The effects of oil price exposure of oil-gas sectors of the countries largely affected by Covid-19 is analyzed with a time-varying parameter model. Estimation results suggest that market risk of all countries' oil-gas sector excluding China has increased remarkably compared to the period before the spread of the virus. Positive and significant effects of the oil price factor become negative and significant for most countries during the pandemic. The results further indicate that the oil-gas sector of China is not affected by the outbreak of Covid-19, even though the virus has first appeared in that country.
İktisadi ve İdari Bilimler Dergisi, 2016
This paper investigates the existence of the Environmental Kuznets Curve (EKC) for Turkey by cons... more This paper investigates the existence of the Environmental Kuznets Curve (EKC) for Turkey by considering pollution spillovers among the provinces by using annual data covering the period 1990-2001. Spatial econometrics techniques are employed to account for pollution spillovers. Spatial interactions are measured by means of weight matrices based on contiguity and distance between the neighboring provinces. Our results show that exclusion of spatial heterogeneity among the regions may lead to specification bias in EKC estimations. The significance of pollution spillovers in the spatial estimates suggest that the relationship between pollution and per capita income is also affected by the localities of regions. Our results also imply that environmental quality cannot be sustained at the expense of neighboring regions. Therefore environmental policies should be accommodated by both regional and national policies to achieve sustainable development.
Financial Innovation, 2021
This study analyzes oil price exposure of the oil–gas sector stock returns for the fragile five c... more This study analyzes oil price exposure of the oil–gas sector stock returns for the fragile five countries based on a multi-factor asset pricing model using daily data from 29 May 1996 to 27 January 2020. The endogenous structural break test suggests the presence of serious parameter instabilities due to fluctuations in the oil and stock markets over the period under study. Moreover, the time-varying estimates indicate that the oil–gas sectors of these countries are riskier than the overall stock market. The results further suggest that, except for Indonesia, oil prices have a positive impact on the sectoral returns of all markets, whereas the impact of the exchange rates on the oil–gas sector returns varies across time and countries.
Finance Research Letters, 2018
Spatial model displays the spatial dependency among the emerging markets. Quarterly data from... more Spatial model displays the spatial dependency among the emerging markets. Quarterly data from fourth quarter of 2004 to fourth quarter of 2015 are employed. Results show that there is a strong spatial linkage between the emerging markets. In addition, indirect effects of macroeconomic variables are found.
International Journal of Energy Economics and Policy
This paper examines the effects of oil and natural gas prices on the oil and gas sectors of the B... more This paper examines the effects of oil and natural gas prices on the oil and gas sectors of the BRIC countries (Brazil, Russia, India, and China) over the period over from 20013 to 2022. Unlike previous studies, it employs a time-varying capital asset pricing model based on the estimation of state-space mode. In brief, the findings highlight significant changes in the asset-pricing model parameters across all countries, indicating the limitations of using time-invariant estimates. Specifically, Brazil shows the highest volatility in oil price risk, followed by Russia, both being oil-exporting countries, while market beta values remain relatively stable. Time-varying estimates further suggest that natural gas parameters are relatively lower and less significant than those of oil prices. The Russian-Ukrainian conflict's energy crisis adversely affects the performance of oil and gas sectoral stock returns. This war has had a negative and significant impact on China's oil-gas st...
Computational Economics
The level of financial risk spread out to the world during the COVID-19 pandemic has shown that n... more The level of financial risk spread out to the world during the COVID-19 pandemic has shown that none of the countries are immune to financial uncertainty and the vast changes it brings to economic stability. The contagiousness of sovereign risk is a result of the interdependent structure of countries’ financial networks. Yet the analysis of sovereign CDS risk spread using the network view is both new and limited. With this study, we want to use the network view to prove the interconnectedness of the financial systems in Europe and its effect on the spread of the risk throughout the COVID-19 pandemic. The objective of this study is threefold: First, using the Bayesian networks learned from the daily CDS values of 17 European Union countries, we demonstrate the dependent network structure of countries and the movement of the sovereign risk over this network with a cascading behavior. Second, we explore how the probabilistic dependency structure changes over the different phases of the COVID-19 pandemic, leading to alterations on the behavior of the sovereign risk spread. The previous studies on the sovereign risk spread during the COVID-19 pandemic employs the data over the whole period of the pandemic. However, during the pandemic the behavior of the spread was changing, and to capture that change the consideration of shorter intervals becomes crucial. Therefore, in this study, the COVID-19 crisis period from December 2019 until February 2021 is divided into five phases of 3-month time intervals. As the third and last objective, this study intends to be a roadmap for policy makers as well as for researchers to understand the true nature and connectedness of sovereign risk transmissions. For that purpose, we provide a benchmark procedure for the evaluation of the sovereign risk of countries using Bayesian networks which involves a comprehensive analysis involving several steps conducted on each of the learned Bayesian networks for the different phases of the pandemic. In terms of policy implications, this study aims to be helpful for investors that want to diversify sovereign risk in their bond portfolios and be explanatory for the changing behavior of the risk spread during crisis periods. Moreover, this study exemplifies the use of artificial intelligence methods to understand the working mechanism of economic systems.
Resources Policy, Dec 1, 2020
Sustainability and climate change, Aug 1, 2022
Journal of Asset Management, Mar 11, 2022
Tourism Analysis
This paper examines the effects of the COVID-19 pandemic on the travel-tourism stock markets. Spe... more This paper examines the effects of the COVID-19 pandemic on the travel-tourism stock markets. Specifically, it considers the five most visited countries: France, Spain, the US, China, and Italy. Unlike previous studies, it estimates time-varying VAR (TVP-VAR) models, including daily observations of confirmed COVID-19 cases, economic activity, CDS spreads and the returns of travel-tourism sectors. In brief, our findings indicate that the effects of COVID-19 vary across countries, as well as over time. Specifically, increasing numbers of cases initially had a negative and significant impact on the travel-tourism stock returns of all countries. However, this effect had become insignificant by early April 2020. The travel-tourism markets of the European countries were seen to be more heavily affected by COVID-19 when compared to China and the US, with China seeming to have been the least affected country of all. Overall, our results are essential in understanding the impact of the COVID...
The Economics of Gender Equality in the Labour Market, 2021
SSRN Electronic Journal, 2021
Journal of Asset Management, 2022
ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, 2021
The effects of oil price exposure of oil-gas sectors of the countries largely affected by Covid-1... more The effects of oil price exposure of oil-gas sectors of the countries largely affected by Covid-19 is analyzed with a time-varying parameter model. Estimation results suggest that market risk of all countries' oil-gas sector excluding China has increased remarkably compared to the period before the spread of the virus. Positive and significant effects of the oil price factor become negative and significant for most countries during the pandemic. The results further indicate that the oil-gas sector of China is not affected by the outbreak of Covid-19, even though the virus has first appeared in that country.
İktisadi ve İdari Bilimler Dergisi, 2016
This paper investigates the existence of the Environmental Kuznets Curve (EKC) for Turkey by cons... more This paper investigates the existence of the Environmental Kuznets Curve (EKC) for Turkey by considering pollution spillovers among the provinces by using annual data covering the period 1990-2001. Spatial econometrics techniques are employed to account for pollution spillovers. Spatial interactions are measured by means of weight matrices based on contiguity and distance between the neighboring provinces. Our results show that exclusion of spatial heterogeneity among the regions may lead to specification bias in EKC estimations. The significance of pollution spillovers in the spatial estimates suggest that the relationship between pollution and per capita income is also affected by the localities of regions. Our results also imply that environmental quality cannot be sustained at the expense of neighboring regions. Therefore environmental policies should be accommodated by both regional and national policies to achieve sustainable development.
Financial Innovation, 2021
This study analyzes oil price exposure of the oil–gas sector stock returns for the fragile five c... more This study analyzes oil price exposure of the oil–gas sector stock returns for the fragile five countries based on a multi-factor asset pricing model using daily data from 29 May 1996 to 27 January 2020. The endogenous structural break test suggests the presence of serious parameter instabilities due to fluctuations in the oil and stock markets over the period under study. Moreover, the time-varying estimates indicate that the oil–gas sectors of these countries are riskier than the overall stock market. The results further suggest that, except for Indonesia, oil prices have a positive impact on the sectoral returns of all markets, whereas the impact of the exchange rates on the oil–gas sector returns varies across time and countries.
Finance Research Letters, 2018
Spatial model displays the spatial dependency among the emerging markets. Quarterly data from... more Spatial model displays the spatial dependency among the emerging markets. Quarterly data from fourth quarter of 2004 to fourth quarter of 2015 are employed. Results show that there is a strong spatial linkage between the emerging markets. In addition, indirect effects of macroeconomic variables are found.