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5G and banking
(PressAcademia, 2021-12-31) Teker, Suat; Teker, Dilek; Orman, Irmak
Purpose- Technological developments in mobile telecommunications have evolved immensely after the transition from analog technologies that were widely used in 1980s to digital technologies connecting to globe with wireless cellular technologies. This study intends to review telecommunication technologies starting 1970s (1G technology) through 2020s (5G technology) and analyze the expected effects of 5G technology on the future of banking sector. In addition, it is envisioned how 5G technology will shape the future of the banking industry. Methodology- The study is conducted by having a comparative review of digital technology developments in the last 50 yearsThis study examines the effects of developments in communication technologies on the banking sector and banking services. The research design of this study is the relationship between the advancements in telecommunication technologies and the future of banking sector. The following section cover the comparison of 1G-2G-3G-4G-5G Technologies. Findings- 5G banking featuring video communication, data protection and digital wallets will create a permanent shift for banking customers and their habits. Globally, bank customers are adopting to digital apps as their primary touchpoint for their banks and this transformation will change the structure of bank branches as well as financial services industry. As a result of the analysis, it has been observed that an important innovation and structural transformation period has been entered in the banking sector with the use of 3G and 4G compared to the year before 2000, which we define as traditional banking era. Conclusion- With the wide use of 5G technology after year 2022, the banking sector is expected to enter a new and disruptive restructuring and service innovation. 5G is expected to carry the banking industry to another level where automation and machine-to-machine communication act as a game changer.
AB-27 ülkeleri ve Türkiye'de ekonomik büyümeyi etkileyen faktörlerin belirlenmesi: statik panel veri modeli uygulaması
(2014) Pala, Aynur; Teker, Dilek
Bu çalışmada, 2000-2011 yıllarına ilişkin EU-27 ülkeleri ve Türkiye için ekonomik büyümeyi etkileyen faktörlerin belirlenmesi amaçlanmıştır. Analizde, gayri safi milli hasıla (GSYİH) büyümesi, nüfus artışı, bankacılık sektörünün yurtiçine sağladığı kredilerinin GSYİH'ye oranı, özel sektör kredilerinin GSYİH'ye oranı, dış ticaret hacminin GSYİH'ye oranı, tüketici enflasyonu ve net tasarrufların Gayri Safi Milli Hasıla (GSMH)'ya oranı değişkenleri kullanılmıştır. Ekonometrik model statik panel veri regresyonu ile tahmin edilmiştir. Model sonuçlarına göre, ekonomik büyüme üzerinde, nüfus artışı, özel sektör kredilerinin GSYİH'ye oranı, net tasarrufların GSMH'ye oranı değişkenleri pozitif yönde etkili iken, tüketici enflasyonu ve bankacılık sektörünün yurtiçine sağladığı kredilerinin GSYİH oranı gibi değişkenler negatif yönde etkilidir.
Backcasting Bitcoin volatility: ARCH and GARCH approaches
(Suat Teker, 2024-12-31) Teker, Dilek; Teker, Suat; Demirel Gümüştepe, Esin
Purpose- The primary purpose of this study is to model Bitcoin price volatility and forecast its future price returns using advanced econometric models such as ARCH and GARCH. The study aims to enhance risk management strategies and support informed investment decisions by addressing the time-varying nature of Bitcoin’s volatility. The research explores the persistence of volatility shocks and the clustering of price movements to provide insights into market dynamics. Methodology- This research examines daily Bitcoin closing prices over the period from January 2020 to October 2024. The data was preprocessed to ensure reliability, including applying logarithmic transformations to standardize the data and eliminate trends. Stationarity tests, such as the Augmented Dickey-Fuller (ADF), Phillips-Perron (PP), and KPSS tests, were conducted to confirm the series' stationarity. The ARCH-LM test was utilized to detect volatility clustering which is essential for validating the use of ARCH and GARCH models. Following this, ARIMA models were employed to define mean equations and GARCH models were used to estimate conditional variance and capture volatility dynamics. The dataset was split into training and validation subsets with data from July to October 2024 reserved for validation. Findings- The findings demonstrate that Bitcoin’s price movements exhibit significant volatility clustering and persistence of shocks which are key characteristics effectively captured by ARCH and GARCH models. These models provide valuable insights into the volatility patterns of Bitcoin, supporting their application in cryptocurrency analysis. Despite their robustness, the models face limitations in precise return forecasting during highly volatile periods, suggesting the need for further refinement or integration with advanced approaches. Conclusion- The research concludes that ARCH and GARCH models are effective tools for understanding and forecasting Bitcoin’s volatility. The study underscores the importance of acknowledging volatility persistence and clustering effects when analyzing cryptocurrency price behavior. However, it also highlights areas for improvement in econometric modelling by including the exploration of hybrid models and the integration of macroeconomic factors to enhance forecasting accuracy.
The Covid 19 effect on macroeconomic indicators
(PressAcademia, 2020-12-31) Deniz, E. Asena; Teker, Dilek
Purpose- From the moment covid 19 started to spread in the world, its effects began to be seen simultaneously in financial markets and economy.The purpose of this study is to observe Covid 19 effect on EURO/USD,gold ,oil and wheat prices. Methodology- The database includes the Daily prices of EUR/USD, wheat ,gold , brent oil prices and COVİD 19 numbers between the period of 31.12.2019-04.09.2020 which consist of 180 daily data. Natural logaritm for each indicator is used. First, the stationarity of the series were analyzed with ADF (Augmented Dickey Fuller) unit root test. Lag lengths are determined. Interactions between the series were analyzed by theARDL, Impulse- Response Function and Variance Decomposition method. Findings- The series are found out to not to be stationary as a result of Unit root test.After, the lag length criteria using VAR models were checked and this lag length criteria for them were determined as one . According to the ARDL test result, cointegration could not be found between our data. Impulse response graphs indicate that all variables respond in a reducing way to reducing shocks occurred in each indicator. Shocks have lost their effect on average in 2 days. Conclusion- The results indicate that the effect of COVID 19 on EUR/USD , gold , brent oil and wheat prices do not have a strong effect. The results may be beneficial for only literatüre.
Crypto currency applications in financial markets: factors affecting crypto currency prices
(PressAcademia, 2020-07-30) Deniz, E. Asena; Teker, Dilek
Purpose- As the cryptocurrency market is beginning to attract investors, a new portfolio of cryptocurrencies has been published in the literature on macro-economic factors affecting these currencies. This research also aimed to identify the interaction between gold, brent oil, Bitcoin, Ethereum and Ripple. Methodology- The database includes the Daily prices of Bitcoin, Ethereum, Ripple, gold and brent oil prices between the period of 03.04.2018-31.12.2020 which consist of 500 daily data. Natural logaritm for each indicator is used. First, the stationarity of the series were analyzed with ADF (Augmented Dickey Fuller) unit root test. Lag lengths are determined. Interactions between the series were analyzed by the Johansen Cointegration test, Granger Causality test, Impulse- Response Function and Variance Decomposition method. Findings- The series are found out to be stationary at first difference. According to the cointegration test result, cointegration could not be found between our data. According to Granger causality analysis, only one-way relationship was found from bitcoin to gold. Impulse response graphs indicate that all variables respond in a reducing way to reducing shocks occurred in each indicator. Shocks have lost their effect on average in 2 days. Conclusion- The results indicate that the effect of gold and brent oil prices on bitcoin, ethereum, ripple daily prices do not have a strong effect. The results may be beneficial for investors to consider diversification for the portfolios.
Cryptocurrencies and regulations: a comparative framework for international implementations
(PressAcademia, 2023-02-01) Ozak, Ceyda; Teker, Dilek
Purpose- The recent developments in technology have created a remarkable increase in the financial markets. The decentralization of crypto assets and the price movements attract investors attention as an demanding financial instrument. Since the beginning of pandemics, inflation is one of the major macroeconomic issue in the globe that push the investors to seek for new investment opportunities. Perhaps the positive perception regarding the cryptocurrency investment is its protection from inflation. In addition cost-effective mode of transaction and easy transfer of funds make these instruments unique. On the other hand, it can also lead to unsolicited consequences such as money laundering, illegal purchases, and the elimination of corruption. In this context, regulations are being formed to bring crypto assets, which attract the attention of experts, into compliance with the tax and trade-related laws of countries in the financial system. In this study, it is aimed to convey the importance of regulation and regulations on the world. Methodology- Since the first launch of Bitcoin as a cryptocurrency in 2009; the recent discussion came forward on how to regulate this market. Understanding cryptocurrency takes time and effort while they are extremely volatile investment. The crypto money applications of the countries and their taxation and approaches towards these applications have been evaluated by examining the official reports of the countries. Findings- Countries' perspectives on crypto money, the concept and definitions of crypto money vary. Some accept the cryptocurrencies as legal investment tools and draw a legal framework, while some announce that they eliminate these investments. Perhaps developing a framework can help to regulate both actors and also the transactions in the crypto ecosystem. National authorities plan to take a position how technology can be used to create cryptoassets. Conclusion- Regulations are important for making the financial system safe, protecting individual investors and ensuring an orderly environment in enterprises. Countries need to accept the crypto currency system and keep up with the innovations of crypto money by changing the current standards if necessary.
Determinants of Bitcoin price movements
(Suat Teker, 2024-07-30) Teker, Dilek; Teker, Suat; Demirel, Esin
Purpose- Investors want to include Bitcoin in their portfolios due to its high returns. However, high returns also come with high risks. For this reason, the volatility prediction of Bitcoin prices is the focus of attention of investors. Because Bitcoin's volatility is used as an important input in portfolio selection and risk management. This means that the models to be used in predicting Bitcoin volatility increases the importance of performance. In this research; A comparative examination of the models applied for Bitcoin shows an effective performance in volatility prediction. It is very important for evaluation. The aim of this study is to model Bitcoin price returns and to examine future return predictions and return directions using historical Bitcoin prices. Methodology- Many models have been used in studies on financial instruments and price predictions. Models such as linear and nonlinear regression, Random Walk Model, GARCH and ARIMA fall into this category. Nonlinear econometric models such as ARCH and GARCH are used for financial time series with variable volatility. These models assume that the variance is not constant. In this study, first Bitcoin price returns for the period between January 2020 and December 2023 will be modeled with the GARCH model, and then the ARCH-GARCH models will be used for future prediction of returns for the period between January 2024 and June 2024. Finally, the actual values will be compared with the forecasted values. In other words, the primary aim of this study is to use the daily Bitcoin closing price between May 2020 and December 2023 to estimate the returns for the periods of 2024 and compare it with the actual returns. Findings- The analysis reveals that GARCH Model results showed that in the mean and variance equations, it is seen that all variables are except intercept of the mean equation significant according to the error level of 0.05. Namely, the reaction and persistence parameters are significant accourding to 0.05 in the variance equation. Both the coefficient of the reaction parameter and the coefficient of the persistent parameter are higher than zero (positive). Also, the coefficient of the reaction parameter plus the coefficient of the persistent parameter approximately equals 0.72. That is, it is lower than 1 and higher than zero (positive). The level of persistence is not too high. So, we do not think about non-stationary variance in the model. Reaction parameter’s coefficient is 0.13. And persistence parameter’s coefficient is 0.58. As we can see, persistent parameter is much higher than reaction parameter. That is, when there is a new shock that creates the persistent parameter, that shock will be in effect for a long time, it will not disappear immediately. That is, a significant part of the shock that occurs in one period flows into the next period. After determining the appropriate mean and variance models, a forecast is made using Automatic ARIMA forecasting for BITCOIN return forecasting. This forecast is made for the first five months of 2024, without adding the actual values of the first five months of 2024 to the data. The program ranks the most appropriate model. The program chose GARCH(3,3) as the most appropriate model in "bitcoin return prediction". Conclusion- The results of the test applied in the study can be summarized that the unit root test results showed that it was necessary to work with return series. GARCH(1,1) model results show when there is a new shock that creates the persistent parameter, that shock will be in effect for a long time, it will not disappear immediately. That is, a significant part of the shock that occurs in one period flows into the next period. According to GARCH automatic forecasting results, the best GARCH model that models Bitcoin return is the GARCH(3,3) model. According to these model results, although the slopes of the actual and forecasted return series move in the same direction, the model remains weak for forecasting. In future studies, it may be recommended to estimate Bitcoin returns with non-linear models.
Determinants of Bitcoin prices
(PressAcademia, 2019-12-30) Deniz, E. Asena; Teker, Dilek
Purpose - The increase in the popularity of cryptocurrency market, various literature figure out the macroeconomic factors that effect the price movements of cryptocurrencies. This research aims to identify the interaction between gold, brent oil and bitcoin. Methodology - The database includes the Daily prices of Bitcoin, gold and brent oil prices between the period of 28.04.2013-23.07.2019 which consist of 484 daily data. Natural logaritm for each indicator is used. First, the stationarity of the series were analyzed with ADF (Augmented Dickey Fuller) unit root test. Lag lengths are determined. Interactions between the series were analyzed by the ImpulseResponse Function and Variance Decomposition methods. Findings- The series are found out to be stationary at first difference. Impulse response graphs indicate that all variables respond in a reducing way to reducing shocks occurred in each indicator. Shocks have lost their effect on average in 5 days. Conclusion- The results indicate that the effect of gold and brent oil prices on bitcoin daily prices do not have a strong effect. The results may be beneficial for investors to consider diversification for the portfolios.
Determinants of foreign direct investments: comparative analysis for Brazil, China, South Korea and Turkey
(PressAcademia, 2021-07-30) Kılıç, Fatih; Teker, Dilek
Purpose- With the globalization race gaining momentum after 1980, investments in developing countries increased significantly with the removal of obstacles to capital flows. With the effect of the globalization phenomenon in the world economy, developing countries have sought to meet the capitals they need with foreign investments. Until the 1980s, foreign direct investments were subject to serious restrictions. The priority of foreign direct investment was South Korea and Brazil in the early days. These two countries were followed by many emergency countries with development potential, and Turkey was trying to be included in this group. In the early 2000s, the biggest factor behind China's huge growth was the directing of foreign investments to China. In this study, inflation rate, unemployment rate and the index of industrial production, foreign direct investment coming to Brasil, China, South Korea and Turkey are examined on whether this is effective. Methodology- The data used in statistical tests are foreign direct investments, inflation, unemployment and the industrial production index, which has the largest share in GDP and allows interpretation without GDP being announced. All monthly data used in the tests are gathered from the Reuters, Bloomberg, UCTAD and the World Bank that covers periods from January 2012 to December 2020. Initially, unit root tests were performed to determine whether the data was stable.There are 3 basic critical points to understand whether unit root tests are stationary or not. After that, the VAR model has been applied. But before that coordinates all selected variables together and examines the integrity of the system, it is required to determine the appropriate lag length in order to make assumptions correct. The are five most common methods for determining lag lengths. In order to understand whether there is a long-term relationship between variables or not that are determined to be stationary, Johansen Cointegration test has been applied. Trace Statistics and the Max-Eigenvalue statistics were used in this test. And also impulse-response functions are obtained. Variance decomposition investigates which percentage of the change in a variable is caused by itself and which percentage is caused by other variables. Findings- All data have been converted into percentages by taking changes compared to the previous month. It has been modeled by getting the absolute values and logarithms of the data. For all 4 countries the series are found out to be stationary at level. ADF unit root test performed, then the appropriate length level determined. According to LR Test Statistics, Final Prediction Error, Akaike Information Criteria, Hannan-Quinn Information Criteria and Schwarz Information Criteria, the appropriate lang length appears as 1. According to the cointegration test result, cointegration was determined between all countries and all data. Impulse response graphs were indicated that all variables respond in a reducing way to decreasing shocks occurred in each indicator. Shocks have lost their effect on average in 4-5 months. According to the variance decomposition results, variables were the power of explanation over each other. Conclusion- In the Brasil, China, South Korea and Turkish economy, it is seen that there is a close relationship between foreign direct investment and economic growth indicators inflation, unemployment, industrial production index in the long term. According to the output of analyses, it is necessary to create the appropriate physical environment for increasing foreign capital investments, to ensure domestic economic, political and legal stability, to make arrangements that encourage foreign capital. Especially, a policy should be followed to decrease inflation and unemployment rates, which are indicators of economic growth and GDP should be risen by increasing industrial production. Coming from the foreign investments should become from the type of foreign direct investment and it should be supplied that these investments both create new markets and new employment areas by establishing a new facility.
Digital payment systems: a future outlook
(PressAcademia, 2022-07-30) Teker, Suat; Teker, Dilek; Orman, Irmak
Purpose- This study examines the development of digital payment systems with the evolution of communication technologies, financial institutions and fintech companies. Also, this study analyzes the expected effects of developing payment systems and fintech applications. Methodology- The study defines different types of digital payment systems, compares general characteristics of digital payments, provides a timeline of developments for digital payment systems and compares most used digital payment applications. Findings- The payments market is changing in line with consumer behavior. Cashless economies, mobile banking, instant payments, digital commerce, and the growing impact of regulatory agencies are a few trends affecting the payments market. Contactless payments also make the payment process easier and more convenient for consumers who benefit from shorter lines, cash-on-hand issue elimination, and faster moving queues.The Asia-Pacific region is anticipated to witness significant growth in the market such as China and India. Digital and mobile wallets account for 58% of regional e-commerce payments in the region and are expected to reach 68.2% by 2023. The e-commerce sector is witnessing a spike in demand as consumers order essential items such as food and clothes through e-commerce websites, where most consumers prefer the digital mode of payment.Transition towards the cashless economy, emergence of new online financial institutions, a decentralized monetary governance with the adoption of blockchain and cryptocurrencies are envisioned. Advancements in payment technologies as well as digital payment systems adoption will create momentum and create further investments towards digitalization of monetary exchange. Conclusion- It is concluded that evolution of digital payment systems will extend convenience, return, convergence, cross-border and timelimitless transaction. Inclusion of the unbanked is expected to drive growth and create new opportunities. There is a clear transition towards a cashless economy with the increasing adoption of digital payment systems by all spenders. Speed, privacy, convenience, security and decentralization will mean a wider inclusion for all global citizens; even including some unbanked population. Decentralization and blockchain will mean a blur in distribution of wealth, some money leaving the traditional banking systems. Digital payment systems provide a wide range of transaction options to its users; swiped credit cards, electronic checks, mobile wallets and contactless payment. By 2050s, the circulation of physical money is expected to vanish, leaving its place to virtual currencies changed on digital platforms.
Digital transformation and universities
(PressAcademia, 2022-07-30) Teker, Suat; Teker, Dilek; Tavman, Emine Başak
Purpose- This study aims to examine how digitalization has affected and changed higher education. It focuses on the current situation of universities and their current processes and what they need to do to become digital. It aims to present a roadmap for universities to integrate and organize these important changes into their strategies by examining the digital transformation that affects the vision of universities. Methodology- The study employs a literature review using secondary data analysis. Findings- The analysis reveals that the role of universities in many aspects such as society and economy has changed and is expected to change disruptively over the next decade. Universities need to make a differentiation through emerging business models in such a competitive higher education sector. Higher education institutions have to adapt to technological changes for sustainabilty. The pandemic dramatically accelerated the pace of technological adoption worldwide. The drivers of digital transformation in universiteis can be summarized as the increase compteteiveness, user experience and agility while reduction in operating expenses. Conclusion- It may be concluded that a university should be part of present technological trends and include digitalization in their strategies to be competitive in the future. Universities need to focus mainly on exploring more innovative measures to create technology development centres through research to deal with skills shortages. Universities should support those academics who lead the improvement of digital skills and innovative teaching methods, promote digital literacy in the academia and encourage the use of learning platforms. It is important to set a clear policy to adopt digital age in higher education. Universities will be competing globally for students, academic staff and funding. Adoption and implementation of new technologies in universities are inevitable.
Digital transformation in businesses: the process and its outcomes
(PressAcademia, 2022-07-30) Teker, Suat; Teker, Dilek; Örendil, Emre
Purpose- The purpose of this study is to serve as an extensive outlook about digital transformation. Its content comprises the elements of digital transformation, the ways of adapting to digital transformation, reasons for failure, means of digital transformation, and insights and discussions on new business environment. Methodology- In this study, a comprehensive literature review is followed to learn about the current business circumstances regarding digital transformation and have a deep understanding on the previous studies conducted about digital transformation. Findings- The literature review reveals that digital transformation has provided positive impract on businesses at different levels. Although challenges against digital transformation may arise, they can be tackled if the nature of digital transformation is understood well. The success of digital transformation is dependent on numerous factors from different aspect which should be studied carefully before and during the adoption of digital transformation. Conclusion- It may be concluded that the COVID-19 pandemic has accelerated the digital agenda of businesses. At first, it should be understood that digital transformation is not a mere upgrade of technology or technical equipment within an organization but requires time, curiosity, creativity, recognition of opportunities, and cultural transformation. A successful adoption of digital transformation requires the recognition of means of digital transformation, the steps for adaptation to digital transformation, the analysis of failure, the outcomes of digital transformation. The recent evolutions related to digital transformation is evident in different aspects of business. The most recent observed changes in businesses are required skills of employees, organisational culture, business models, and customer relationship management practices.
Doğrudan yabancı yatırımların Türkiye ekonomisi üzerindeki etkisinin incelenmesi
(PressAcademia, 2020-12-31) Kılıç, Fatih; Teker, Dilek
Amac?- Bu çalışmada enflasyon oranı, işsizlik oranı ve sanayi üretim endeksinin, Türkiye’ye gelen doğrudan yabancı sermaye yatırımları üzerinde etkili olup olmadığı incelenmektedir. Yo?ntem- Analize tabi tutulan datalar DYY, işsizlik oranı, enflasyon oranı ve GSYİH içindeki en yüksek paya sahip olan sanayi üretim endeksidir. Ocak 2005 - Mayıs 2020 arasındaki dönemleri kapsayan aylık veriler kullanılmıştır. Testlerdeki datalar TCMB EVDS, TÜİK ve Dünya Bankası’ndan alınmıştır. Bulgular- Serileimiz düzey değerde durağan çıkmıştır.Eş bütünleşme test sonucuna göre ,tüm değerlerimizin eş bütünleşik olduğu gözlemlenmiştir.Etki tepki grafiklerine göre tüm değişkenler, her göstergede meydana gelen şokları azaltmak için indirgeyici bir şekilde yanıt vermektedir. Şoklar etkisini ortalama 3 ayda kaybetmiştir. Sonuc?- Türkiye ekonomisinde doğrudan yabancı sermaye yatırımları ile ekonomik büyüme göstergeleri enflasyon, işsizlik, sanayi üretim endeksi arasında uzun dönemde sıkı ilişki içerisinde olduğu görülmektedir.
Economic value added and corporate firm value implications
(PressAcademia, 2018-12-30) Teker, Dilek; Alp, Elçin Aykaç
Purpose - Recent studies focus on the corporate firm value and relation with financial parameters. This study reveals the interaction between economic value added on corporate firm value and specific financial parameters such as P/E, WACC, ROE and ROIC. This analysis focuses primarily on how corporate value is effected by the other variables and the duration that this influence leads. Methodology – The quarterly data is derived for public banks in Turkish markets for the period 2006Q1-2018Q3. In the light of the data obtained, PE, ROE, ROIC, WACC and WACCEVA values calculated for seven public banks. Each financial indicator was analyzed in terms of trend and it was decided that the existing deterministic components should be eliminated in order not to affect the analysis result. Findings- The summarized results indicate different occasions for each stock such as economic value added has significant effect on firm value for couple of the firms and WACC and EVA variables have one period lagged effect for all stocks. Conclusion- We indicate that firm value is effected from financial measures and further analysis should focus on investor buy/sell behaviors in time lags.
The effects of policy rate announcements on the exchange rates
(PressAcademia, 2024-01-15) Teker, Suat; Teker, Dilek; Demirel, Esin
Purpose- Exchange rate is the value of a country's national currency against foreign national currencies. In this context, the exchange rate is considered an important macroeconomic indicator in evaluating the country's economy. The failure to control the exchange rate may damage economy significantly. It is possible to understand this from the 2001 crisis in Turkey, known as 'Black Wednesday', and the foreign Exchange crisis that started in Thailand in 1997 and affected many East Asian countries. Interest rate is one of the critical determinants affecting the exchange rates. Therefore, changes in interest rates are expected to affect the level of exchange rates. When there is an increase in interest rates, foreign capital flow is expected for that particular country. Hence, a decrease in exchange rates is expected for the excess capital flows. This study aims to analyze the relationship between exchange rates and interest rates, considering the last 10 announcements of the interest policy of the Central Bank of the Republic of Turkiye. These announcements are between January 19, 2023 and October 26, 2023. The study used the TL/USD exchange rates and 10-year government bond interest rates to measure the relationship in between these two variables. Methodology-The aim of this study is to analyze the relationship between the dollar exchange rate and government bond interest rates for Turkiye. For this purpose, data is collected for the days when the last 10 policy rates published by the CBRT were announced. Data is obtained investing.com. Vector Autoregression (VAR) is used to measure the relationship in between two variables. The VAR system is based on empirical regularities embedded in the data. The VAR model may be viewed as a system of reduced form equations in which each of the endogenous variables is regressed on its own lagged values and the lagged values of all other variables in the system. Vector Autoregressive models are widely used in time series research to examine the dynamic relationships exist in between variables that interact with one another. In addition, VAR models are viable forecasting tools used often by macroeconomic or policy -making institutions. . In this study first, the stationary levels of the variables are determined by using Unit Root Test. Second, pre-tests of autocorrelation, heteroscedasticity and normality are conducted for the validity of the VAR model. Third, the short-term relationship between variables is tested by using VAR Granger Causality Test. Fourth, VAR analysis is utilized by applying Impulse-Response Analysis and Variance Decomposition Analysis . And finally, the long-term relationship between variables is tested by using Johansen Cointegration Test. Vector Autoregressionmodel is employed in this study. Findings- According to the results of Granger Causality test, government bond interest rates strongly affect the changes of exchange rate. However, there is no causality from exhange rates to interest rates. Therefore, the changes of interest rates are the main determinants of the changes of exchange rates in this short period. The results of Impulse-Response Test show that an unexpected shock (an unexpected increase) in government bond interest rates affects the exchange rates and increases it significantly. More, an unexpected increase in the exchange rates causes the interest rates on government bond to increase. The results of the variance decomposition test show that 50% of the change in the variance of the exchange rates in the first period is explained by changes in bond interest while 30% of the change in the variance of bond interest rates is explained by the changes in exchange rates. The results of Johansen cointegration test support that there is a stable long-term relationship between dollar exchange rates and government bond interest rates. Conclusion-This study focuses on the relationship between government bond interest rates and the dollar exchange rates in Turkiye for the last 10 policy interest rates announcements by Cenral Bank of Turkiye. In summary, the changes in interest rates on bonds affect the changes in exchange rates more. Data for the days that the CBRT issued the last ten policy rates is gathered for this purpose. The association between two variables is measured using Vector Autoregression (VAR). According to overall results, the changes in interest rates on bonds affect the changes in exchange rates more.
Export potential of Turkish SMEs
(Suat Teker, 2024-07-30) Teker, Suat; Teker, Dilek; Orman, Irmak
Purpose- Digital channels are gaining more and more share from trade and commerce, especially after Covid 19 pandemic. People have adopted to online buying and marketplaces became important retailing tools for manufacturers. E-commerce is rising not only in closed commercial areas but also across different countries, even continents with developments in cross-border e-commerce. Governments, global digital platforms, consumer habits are creating and supporting the demand of buying online from anywhere and numbers are showing that this creates an opportunity for Turkish businesses to become exporters. This study aims to highlight the potential for small and medium sized businesses in Turkey to become exporters. Methodology- The study examines historical export growth data of Turkey in detail using secondary data. The historical data is used to make a projection for future and highlight the potential of growth for Turkish SMEs. Current marketplace platforms’ business models are also examined and carefully analyzed to present an understanding of the potential business models. Findings- The numbers are showing that Turkish exports are growing in Europe and USA. Capex heavy industries have the highest share among the exports but e-commerce is also growing. Some industries like textile, jewellry and small appliences has a higher growth potential withing cross border e-commerce. Conclusion- Adoption to online retail is getting higher and higher. More people are buying from online marketplaces and the origin of the transaction is losing its importance with one-day deliveries. It is important to open shops not only physical but also on different platforms. It is easier for business owners to sell across the world and become exporters. By having international customers, businesses distribute regional risks and also become financially stronger. It is important for Turkish SMEs to understand their risks and seek international growth opportunities, such as doing exports. Turkey’s unique geographical location is a very important asset but Turkish businesses should keep in mind that all international producers are now seeking opportunities to create through online platforms.
Financial inclusion and economic development: Turkey and Greece
(PressAcademia, 2023-02-01) Teker, Suat; Teker, Dilek; Güzelsoy, Halit
Purpose- Financial inclusion means individuals and businesses have access to useful and affordable financial products and services to deliver their needs in a responsible and sustainable way. A financial sector is measured and compared on four main features; debt is the size of financial institutions, access is the access and use of financial services by the users, efficiency is the efficiency in the provision of financial services, and stability is the stability in the provision of financial services. The purpose of this paper is to measure the level of financial inclusion of Turkey and Greece from 2000 to 2020 and compare its relationship with the economic growth and income inequality of both countries. Methodology- The World Bank data covering the 2000-2020 period is extracted from Turkey and Greece from the world bank report. The whole financial system for both countries is defined as a combination of banks, nonbanks financial institutions, and stock exchange markets. The related indicators for each of the subsectors of the financial system are determined for banks, nonbanks financial institutions, and stock exchange markets. Thus, 32 indicators for banks, 6 indicators for nonbanks, and 16 indicators for stock exchange markets are determined for the financial inclusion index. All indicators are in percentages. All individual indicators are summed for the computation of subsectoral indexes and then the growth rate in each subsectoral indexes are computed. The growth rates of each subsectoral index are summed and weighted by the subsectoral asset sizes or trading volüme. Finally, the causal relationship between the financial inclusion index, Gini coefficient, Poverty Headcount ratio, and GDP per capita was examined. Findings- The average growth rate for the financial inclusion index for the 21 years is 2,83% for Turkey and 0,97% for Greece. According to the analysis, we found that the financial inclusion index Granger-cause GDP per capita, Gini index Granger-cause financial inclusion index and there is a bidirectional relationship between the financial inclusion index and Poverty Headcount ratio for Turkey. On the other hand, there is a bidirectional relationship between GDP per capita and the financial inclusion index and a bidirectional relationship between the financial inclusion index and the Poverty Headcount ratio for Greece. Conclusion- Financial inclusion simply means a larger size of financial institutions and a variety of financial products and services available for the use of adult individuals, businesses, and governmental agencies. Economic growth is supported and accelerated by an increase in financial inclusion. The empirical analysis supports the literature that the growth in the financial inclusion index enhances a higher growth in GDP and a much higher growth in GDP per capita for both Turkey and Greece. The project titled “Istanbul as an International Financial Center” may easily improve the level of financial inclusion in Turkey.
Financial inclusion for selected OECD countries
(PressAcademia, 2023-07-30) Teker, Dilek; Teker, Suat; Güzelsoy, Halit
Purpose- Financial inclusion is defined as a process that ensures the ease of access, availability, and usage of the formal financial system for all members of an economy by emphasizing the use of accessibility and availability of financial services. A financial sector is measured and compared on four main features; debt is the size of financial institutions, access is the access and use of financial services by the users, efficiency is the efficiency in the provision of financial services, and stability is the stability in the provision of financial services. Financial inclusion, in short, is adults' access to and use of financial services. This study aims to measure the financial inclusion level for selected OECD countries from 2010-2021. Also, this study aims to estimate the effect of financial inclusion on economic growth and income inequality for selected countries. Methodology- The data used in this study cover a range of variables related to financial inclusion from various institutions, including the IMF-Financial Access Survey (IMF-FAS), the World Bank - World Development Indicators (WB-WDI), the World Bank - Global Financial Development Database (WB-GFDD) and the Standardized World Income Inequality Database (SWIID). These variables provide insights into the dimensions and determinants of financial inclusion and their impact on economic and social outcomes for selected OECD countries. In the study, we run panel data regressions for each group separately, using GDP per capita as the dependent variable to determine the impact of the Financial Inclusion Index on economic growth. We also construct two different models for each group of countries with and without the added control variables into the models. Findings- The analysis reveals that the effect of financial inclusion on economic growth is negative for all groups of countries. The impact is significant for Group 1 and Group 2. The magnitude of coefficients changes when we add control variables to the model. However, it does not change the significance level of the coefficients. The magnitude of the coefficients increases as countries’ per capita income increases. At the same time, the effect of financial inclusion on the GINI index is significant only in the model for Group 3 with control variables. The sign of the impact is negative. It implies that the GINI index decreases as the financial inclusion index increases. So, the effect of financial inclusion on income inequality is positive for countries in Group 3. Conclusion- The empirical results did not support the relationship between financial inclusion and economic growth (GDP per capita). These results may be explained by advocating the financial sector's quick and fundamental digital transformation. Hence, the rules for availability, accessibility, and usage of financial products and system are completely changed in the past ten years. On the other hand, the relationship between financial inclusion and income inequality, measured by GINI Index, is consistent with the literature only for Group 3 countries (developing countries). The increase in the gap between rich-developed and developing countries may explain these results. An increase in financial inclusion still supports adjustments in income inequality in developing countries, but its effect is disappeared in developed countries in the last 12 years.
Financial inclusion: the case of Turkey
(PressAcademia, 2021-12-31) Teker, Suat; Teker, Dilek; Güzelsoy, Halit
Purpose- Financial inclusion is defined as a process that ensures the ease of access, availability and usage of the formal financial system for all members of an economy by emphasizing the use of accessibility, availability of financial services. A financial sector is measured and compared on four main features; debt is the size of financial institutions, access is the access and use of financial services by the users, efficiency is the efficiency in the provision of financial services, stability is the stability in the provision of financial services. Financial inclusion, in short, is adults' access and use of financial services. The purpose of this paper is to measure the level of financial inclusion of Turkey for the period of 2000-2017. Methodology- The World Bank data covering 2000-2017 period is extracted for Turkey. The whole financial system of Turkey is defined to be a combination of banks, nonbanks financial institutions and exchange markets. The related indicators for each of the subsections of the Turkish financial system are determined for banks, nonbanks and exchange markets providing a continued data stream. Thus, 32 indicators for banks, 6 indicators for nonbanks and 16 indicators for exchange markets are determined for the financial inclusion index for Turkey. All indicators are in percentages. All individual indicators are summed for the computation of subsectional index and then the growth rate in each subsectional index is computed. Finally, the growth rates of each subsectional index are summed and weighted considering the subsectional asset sizes or trading volume. Findings- The highest growth years in financial inclusion of banks; 15.26% in 2002, 8.05% in 2009, and 4.42% in 2014. The lowest growth years in financial inclusion of banks; -10.36% in 2001 and -2.00% in 2008. The average growth rate for banks for the 17 year period is 2.14%. The highest growth years in financial inclusion of nonbanks; 24.47% in 2004, 28.37% in 2006, 26.34% in 2009, 53.07% in 2010, and 30.86% in 2014. The lowest growth years in financial inclusion of nonbanks; -18.74% in 2001, -22.95% in 2011 and -11.39% in 2016. The average growth rate for nonbanks for the 17 year period is 6.19%. Conclusion- Financial inclusion simply means a larger size of financial institutions and a variety of financial products and services available for the use of adult individuals, businesses and governmental agencies. The existing literature advocate that the economic growth can be accelerated by an increase in financial inclusion. The empirical analysis for Turkey supports the literature where the growth in financial inclusion index enhances a higher growth in GDP and a much higher growth in GDP per capita. The project titled “Istanbul as an International Financial Center” may easily improve the level of financial inclusion in Turkey. For a sustainable economic growth and a fair income distribution in Turkey, the policy makers and administrators should set the rules and regulations to improve the financial inclusion.
Financial performance of top 20 airlines
(Elsevier Science BV, 2016) Teker, Suat; Teker, Dilek; Güner, Ayşegül
This empricial research article intends to analyse the financial performance of the top 20 airlines in the Word for the period of year 2011 and 2014. In order to measure the financial performance of the airlines on a uniqie base, an hormonic index is propesed by considering performance areas of profitability, operating, efficiency and liquidity. Next, each performance area is defined by using a various of performance ratios. Finally, all airlines companies examined are listed by their harmonic index scores. The total assets of the 20 biggest airlines are amounted over $457 billion in 2014 and Delta Airlines with an assest size of $54 billion is the biggest ailines. On the other hand, the highest revenue generated by Luftansa in 2011, 2012 and 2013 over $40 billion per year The empricial results show that the worst scores of harmonic index refer American Airlines in 2011, Soutwest in 2012, China Eastern Airlines in 2013 and Quantas Airways in 2014, while the best scores of harmonic index point Delta in 2011, Hainan Airlines in 2012 and EasyJet in 2013 and 2014. This analysis supports that the measurement of financial performance based upon total revenuue or profitability is somehow weak and may be extented by including other indicators.

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