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1 – 4 of 4Sabri Burak Arzova, Ayben Koy and Bertaç Şakir Şahin
This study investigates the effect of the day of the week on the volatility of cryptocurrencies. Thus, we reveal investors' perceptions of the day of the week.
Abstract
Purpose
This study investigates the effect of the day of the week on the volatility of cryptocurrencies. Thus, we reveal investors' perceptions of the day of the week.
Design/methodology/approach
The EGARCH model consists of the day of the week for 2019–2022 and the volatility of 11 cryptocurrencies.
Findings
Empirical results show that the weekend harms cryptocurrency volatility. Also, there was positive cryptocurrency volatility at the beginning of the week. Our findings show that weekdays and weekends significantly impact cryptocurrency volatility. Besides, cryptocurrency investors are sensitive to market movements, disclosures, and regulations during the week. Holiday mode and cognitive shortcuts may cause cryptocurrency traders to remain passive on weekends.
Research limitations/implications
This study has some limitations. We include 11 cryptocurrencies in the analysis by limiting cryptocurrencies according to market capitalizations. Further studies may analyze a larger sample. In addition, further studies may examine the moderator and mediator effects of other financial instruments.
Practical implications
The empirical results have research, social and practical conclusions from different aspects. Our analysis may contribute to determining trading strategies, risk management, market efficiency, regulatory oversight, and investment decisions in the cryptocurrency market.
Originality/value
The calendar effect in financial markets has extensive literature. However, cryptocurrencies' weekday and weekend effect needs to be adequately analyzed. Besides, studies analyzing cryptocurrency volatility are limited. We contribute to the literature by investigating the impact of days of the week on cryptocurrency volatility with a large sample and current data.
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Sabri Burak Arzova and Bertaç Şakir Şahin
The purposes of this study are to contribute to the limited green growth (GG) literature in emerging markets, to analyze GG from a financial economy perspective and to determine…
Abstract
Purpose
The purposes of this study are to contribute to the limited green growth (GG) literature in emerging markets, to analyze GG from a financial economy perspective and to determine the contribution of financial development and innovation to GG in Brazil, Russian Federation, India, China and South Africa and Türkiye (BRICS-T). BRICS-T countries significantly impact the world population, international politics, energy resources and economy. In addition, BRICS-T countries are one of the leading countries in the world with their sustainability efforts. Investigating the GG model in these countries may contribute to structuring emerging economies around the principles of GG and advancing global green transformation efforts.
Design/methodology/approach
The authors applied panel data analysis from 2001 to 2019. GG is economic growth free from environmental depletion in the model. National income, personnel expenditure and foreign direct investments are macroeconomic variables. These variables measure economic development and promote economic and social progress, which is essential for GG. Capital accumulation and innovation are essential tools in GG transformation. Therefore, financial development and patent applications represent the moderating variables. The authors estimate the fixed effect model with Parks-Kmenta robust.
Findings
Empirical results show that national income growth and foreign direct investments positively affect GG. Personnel expenditure negatively affects GG. On the contrary, financial development and patent growth have little moderating role.
Originality/value
This study contributes to the literature on creating a GG model in emerging countries. The study is original in its model and sample.
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Sabri Burak Arzova and Bertac Sakir Sahin
The present study investigates the impact of financial soundness variables on bank performance in emerging countries.
Abstract
Purpose
The present study investigates the impact of financial soundness variables on bank performance in emerging countries.
Design/methodology/approach
This study uses macro-level panel data from 17 countries from 2011 to 2020. The analysis adopts six models. While four models include bank profitability, the dependent variable of the other models is Bank Z Scores. Regulatory Capital to Risk-Weighted Assets, Liquid Assets to Total Assets, Non-Performing Loans to Total Gross Loans and Non-Interest Expenses to Gross Income are proxies of financial soundness variables.
Findings
The authors estimate fixed and random effects models with the Arellano, Froot and Rogers methods. Empirical results show that Non-Performing Loans to Total Gross Loans harm ROA and ROE. Regulatory Capital to Risk-Weighted Assets negatively affects ROE. Non-Interest Expenses to Gross Income on Bank Z Scores have a significant and negative effect. Moreover, Inflation, Foreign Direct Investment and GDP are macroeconomic variables that increase bank profitability.
Originality/value
This study contributes to the literature in different aspects. The first is the model of the study. The authors contribute to the literature regarding the variables used to measure financial soundness. Secondly, emerging countries are samples in the study. A significant part of the studies on financial soundness has focused on developed countries. Finally, the authors analyze the macro-level data. Bank soundness studies mainly investigate country-level variables. Macro-level analysis may provide an advantage in combating global financial crises.
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Sabri Burak Arzova, Ayben Koy and Bertaç Şakir Şahin
This study investigates the effect of unproven energy reserve news on the volatility of energy firms' stocks. Thus, investors' perception of unproven energy reserves is revealed…
Abstract
Purpose
This study investigates the effect of unproven energy reserve news on the volatility of energy firms' stocks. Thus, investors' perception of unproven energy reserves is revealed. Additionally, the study aims to determine whether the effect of the news changes according to time and volatility level.
Design/methodology/approach
The general autoregressive conditional heteroskedasticity (GARCH) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH) models consist of the energy reserve exploration news in Turkey for the period 2009–2022 and the volatility of 14 energy stocks.
Findings
The results indicate energy exploration news's negative and significant effect on volatility. According to empirical results, energy stock volatility is most affected in the first ten days. Besides, the results show that the significant models of energy reserve news in low-volatility stocks are proportionally higher than in high-volatility stocks.
Research limitations/implications
Only unproved reserve news is included in the analysis, as sufficient confirmed reserves could not be reached during the sampling period. Further studies can compare proven and unproved reserve news effects. Additionally, a similar analysis can be conducted between Turkey and another country with a similar socio-economic character to examine different investor behaviors.
Practical implications
This research includes indications on managing investors' reactions to unproven energy reserve news.
Originality/value
This study contributes to the literature by analyzing unproven reserves. Contrary to previous studies, examining stock volatility also makes the study unique.
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