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    Does Financial Development Enhance Economic Growth? The Case of Turkic Countries
    (Ahmet Yesevi Univ, 2023) Cetenak, Emin Huseyin; Haykir, Ozkan; Cetenak, Oezlem Ozturk
    In this study, we investigate whether financial development enhances economic growth in Turkic countries, namely, Azerbaijan, Kazakhstan, Kyrgyzstan, and Turkiye from 1995 to 2017. The financial development index is obtained from the International Monetary Fund to proxy for the level of financial development. The index shows the level of development of financial institutions and financial markets in terms of depth, access, and efficiency. The annual percentage growth rate of GDP per capita based on constant local currency is taken as an indicator of economic growth. The main result of the analysis shows that there is a positive relationship between financial development and economic growth. The result is robust using random effect regression, adding inflation, and including Banking Z Score. However, the main impact can be seen in the financial institution instead of the financial market proxy. The results support the supply-leading hypothesis for the economies of four Turkic countries.
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    Environmental pollution effects of economic, financial, and industrial development in OPEC: comparative evidence from the environmental Kuznets curve perspective
    (Springer, 2023) Demiral, Mehmet; Haykir, Ozkan; Aktekin-Gok, Emine Dilara
    Many studies examined the association between gross domestic production (GDP) and environmental pollution to test the inverted U-shaped environmental Kuznets curve (EKC) hypothesis for varied country groups. Although it has useful implications for achieving a climate-neutral world economy, the exploration of the relationship is yet limited for oil-rich economies. On the other hand, the ambiguity of the available EKC evidence addresses the consideration of other pillars of economic development. Therefore, this paper tests the EKC hypothesis comparatively in the separate non-linear effects of financial and industrial development, as well as the traditional GDP-based economic development, on per capita fossil carbon dioxide (CO2) emissions for the Organization of the Petroleum Exporting Countries (OPEC) bloc. Financial development is proxied by the financial institutions development index, industrial development is measured by per capita industry value-added, and traditional economic development is indicated by per capita GDP. The trade, financial, social, and political dimensions of globalization are also incorporated as control variables in these three models. The paper applies the cross-sectionally augmented autoregressive distributed lag (CS-ARDL) estimator to a dataset from ten OPEC members over the 1980-2019 period. The results clearly contradict the EKC hypothesis and reveal rather a persistent U-shaped pattern for all models in both the short-run and the long-run. In addition, financial globalization is negatively associated and political globalization is positively associated with CO2 emissions. The paper discusses how such oil-rich countries as OPEC may decouple economic growth, financial development, and industrialization trajectories from environmental pollution induced by fossil CO2 emissions.
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    Herding behavior in the European banking sector during the COVID-19 outbreak: The role of short-selling restrictions
    (Economics Bulletin, 2022) Yagli, Ibrahim; Haykir, Ozkan; Cetenak, Emin Huseyin
    The purpose of the current paper is twofold: (1) to examine the impact of uncertainty induced by COVID-19 pandemic on herding behavior, and (2) to understand whether short-selling restrictions have mitigating role in herding behavior. We employ both cross-sectional market deviation (CSSD) and cross-sectional absolute standard deviation (CSAD) approaches to detect herding in European capital markets. For robustness analysis, we estimate herding behavior under different market dynamics, namely high-low volatility periods and up-down markets. We find no strong evidence regarding herding in prior to pandemic; however, herding behavior is more common in the COVID-19 period, indicating triggering role of uncertainty in herding behavior. The results are robust to the herding models whereas they are sensitive to the asymmetric effects. Regarding the short-selling restrictions, we fail to support the impact of short-selling limitations on herding behavior since there is no difference between restricted and unrestricted periods. The overall results indicate that herding behavior prevails amid the pandemic, confirming that fear and uncertainty induced by COVID-19 causes less-informed investors to follow the actions of others. Investors should consider this inefficiency when investing in capital markets. Besides, short-selling restrictions do not have significant impact on herding, suggesting regulatory authorities should employ other tools rather than short-selling bans.
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    Oil price explosivity and stock return: Do sector and firm size matter?
    (Elsevier Sci Ltd, 2022) Haykir, Ozkan; Yagli, Ibrahim; Gok, Emine Dilara Aktekin; Budak, Hilal
    The paper examines whether the oil price series contains price explosivity and if price explosivity exists whether it offers excess return for oil-related, oil-substitute, and oil-user companies in US stock markets. Moreover, we investigate whether the size effect moderates the relationship between oil price explosivity and stock returns. We use monthly West Texas Intermediate crude oil prices between January 1986 and December 2019 and employ the Generalized Supremum Augmented Dickey-Fuller test to detect the price explosivity. Feasible Generalized Least Squares estimator is also implemented to capture the impact of oil price bubble on stock returns of US companies. The results indicate multiple episodes of price explosivity which mostly coincides with the 2008 financial crisis. The price explosivity leads to an excess return for oil-related companies; whereas, it negatively impacts oil-substitute and oil-user firms. However, the effect of oil price explosivity on stock returns is heterogeneous across size groups. The results provide key insightful information to policymakers and investors. Policymakers should prevent the occurrence of price explosivity to increase the efficiency of an oil futures market. Given the diverse impact of oil price explosivity on the stock return across sectors and sub-size groups, investors can maximize their profits by rebalancing their portfolio based on oil dependency and the firm's size.
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    Profit persistence in energy industry: A comparison between listed and unlisted companies
    (Econjournals, 2018) Iskenderoglu, Omer; Haykir, Ozkan
    In this paper, we examine the profit persistency for energy industry around the world during the sample period between 2010 and 2016. We distinguish our dataset into two groups: The listed and unlisted companies to see whether these groups show a different pattern. Profit is measured using four different proxies; namely, return on asset, return on equity, return on capital employed and profit margin. The results of this study indicates that profits do not persist. Where it means that competition in the energy industry is high. In addition, the competition is found to be higher in listed companies compare to unlisted companies. © 2018, Econjournals. All rights reserved.
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    Speculative bubbles and herding in cryptocurrencies
    (Springer, 2022) Haykir, Ozkan; Yagli, Ibrahim
    This study investigates speculative bubbles in the cryptocurrency market and factors affecting bubbles during the COVID-19 pandemic. Our results indicate that each cryptocurrency covered in the study presented bubbles. Moreover, we found that explosive behavior in one currency leads to explosivity in other cryptocurrencies. During the pandemic, herd behavior was evident among investors; however, this diminishes during bubbles, indicating that bubbles are not explained by herd behavior. Regarding cryptocurrency and market-specific factors, we found that Google Trends and volume are positively associated with predicting speculative bubbles in time-series and panel probit regressions. Hence, investors should exercise caution when investing in cryptocurrencies and follow both crypto currency and market-related factors to estimate bubbles. Alternative liquidity, volatility, and Google Trends measures are used for robustness analysis and yield similar results. Overall, our results suggest that bubble behavior is common in the cryptocurrency market, contradicting the efficient market hypothesis.
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    The effect of technological developments on the stock market: evidence from emerging market
    (Routledge Journals, Taylor & Francis Ltd, 2024) Celik, Mehmet Sinan; Ozturk, Mutlu Basaran; Haykir, Ozkan
    This study investigates the effect of High-Frequency Trading on stock liquidity and volatility in Borsa Istanbul, Turkey which is one of the largest emerging markets where high-frequency trading is newly developed. We employ a fixed effect panel estimation model with Driscoll and Kraay correction between January 2016 and December 2020. The finding shows that an increase in high-frequency trading increases the liquidity and volatility. Moreover, the results are similar before the pandemic period and rising market period, whereas the impact of high-frequency trading on liquidity disappears during the pandemic period.
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    Understanding Drivers of Boom and Bust in Cryptocurrency Markets
    (Springer Nature, 2024) Yagli, Ibrahim; Haykir, Ozkan
    The market capitalization of cryptocurrencies has significantly increased despite their high volatility, and professionals and scholars are interested in discovering their price dynamics. In this study, we examine the determinants of large-price swings (more than 10%, 15%, and 20%), given that price changes in the cryptocurrency market are of a large magnitude. More specifically, we aim to determine whether past or market return has the power to predict subsequent daily large price movements (“jumps” or “dumps”) in cryptocurrency. The study also investigates the impact of co-explosivity, size, and uncertainty on large price movements. To do so, we employ daily price, market capitalization, and volume of the largest 1200 cryptocurrencies (excluding stable coins) based on their market capitalization. Given that large price movements are recurring phenomena in the cryptocurrency market, we adopt the Cox proportional hazards model. The empirical findings reveal that the likelihood of experiencing large price increases is higher if cryptocurrency returns are positive on the previous day. On the other hand, the risk of facing significant price increases (decreases) is lower (higher) when the market return is positive on the previous day. Our results also show that price increases in large magnitude experienced in the ten highest cryptocurrencies based on market capitalization do not have a significant impact on the large price increases. When we turn our attention to the size, we find that one-day lag market returns are mostly insignificant for large price increases, whereas they are rather positive and significant (except for small-cap groups) for large price drops. Regarding uncertainty, we ascertain that there are no significant changes between high and low uncertainty periods, especially for large price increases. Our results are robust in relation to the variables used in the analysis. Both in-sample and out-of-sample assessments affirm that our estimation models exhibit comparable predictive power. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.