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The nexus between the yield curve and economic activity: Empirical evidence from emerging markets (EMs)
The yield curve has been widely considered a powerful predictor of economic activity. This study primarily looks at the nexus between the yield curve and economic activity, using the latent factor approach, to study nine (9) MSCI Emerging Markets. Monthly data, covering the period from November 2007 to June 2022 (2007:M11 to 2022:M06), are employed. The main objective is to study the relationship between the yield curve and economic activity. The specific objectives include, for instance, how the spread impacts economic activity when controlled for the local stock markets, i.e., the All Share Index (ASI) or Composite Index (CI); how the spread impacts economic activity when controlled for an international stock market index, i.e., the iShares MSCI Emerging Markets Index (MSCI); and how the spread impacts economic activity when controlled for an alternative international or global benchmark like the global oil price, i.e., the West Texas Intermediate (WTI). The Fully-Modified OLS (FMOLS), Dynamic OLS (DOLS), and Canonical Cointegrating Regression (CCR) estimators are respectively employed to test for the long-run heterogeneous relationship between the yield curve and economic activity. Among other things, it is found that the spread is negatively related to the economic activity, which is represented by the industrial production index, suggesting that, in the long run, an inverted yield curve retards the economic activity of the MSCI Emerging Markets. The result is robust to both the international equity index and the global oil price. Among other things, it is recommended that the 10-year long-term bond rate could be replaced with the 5-year long-term bond rate to check the accuracy of the yield spread in predicting the economic activity of the MSCI Emerging Markets. Keywords: Economic Activity, Long-run Relationship, MSCI Emerging Markets, Panel Data, Yield Curve.
Finance-inequality nexus in emerging countries
This study intends to empirically test the relationship between financial development and income inequality in advanced emerging and secondary emerging countries. To study the impact of financial development on income inequality, we cover five bankbased and market-based dimensions of financial development. These are access, depth, efficiency, stability, and liberalization. We use a panel of 20 countries for the time period between 2000-2017 and estimate the empirical model by employing dynamic panel data method of Generalized Method of Moments (GMM). Our findings suggest that only one dimension of bank-based financial development namely depth is significant in reducing income inequality. In case of stock market-based financial development three dimensions namely depth, efficiency, and stability are important to alleviate income inequality. We also find strong support for income inequality reducing impact of financial liberalization. We conclude that, in our sample of emerging countries, stock market-based financial development plays a more significant and effective role in abridging income inequality than the bank-based financial development. Keywords: Banking System Development, Emerging Countries, Generalised Method of Moments, Income Inequality, Stock Market Development
Effect of macroeconomic news announcement on bond market
The primary aim of this dissertation is to explain the factors effecting the behavior of the bond markets, with a specific focus on the elements affecting the local currency-denominated government bond yields in emerging markets. This analysis involves distinguishing the impact of both domestic and international factors and explaining the connections between foreign ownership and worldwide risk appetite. The first research question of this dissertation examines how foreign participation and global risk appetite affect the yields of government bonds with long-term maturity issued in local currencies within emerging markets. We use a novel approach by utilizing the panel two threshold variable model. Our analysis of panel data shows that foreign participation in the domestic government bond market leads to a decrease long-term government yield, and there is a threshold level in foreign participation. We also look at the global risk appetite interaction with the level of foreign participation. The analysis incorporates 19 emerging market countries, contributing to an understanding of the factors driving bond yields in these economies. This study concludes at the Federal Reserve's interest rate hike in 2015. The timing is pivotal, as it marks a shift in global financial conditions, offering a natural boundary for our analysis of emerging market economies' bond yields in relation to foreign ownership and debt levels. The second research question explores the impact of macroeconomic news and risk appetite on local currency government bond yields in Türkiye, utilizing an event study with data from 2005 to 2023. We explore the influence of unexpected macroeconomic news, monetary policy announcements, and risk events on the average and conditional volatility of Turkish bond returns. The research extends beyond the reaction of bond prices to unexpected news by exploring the dynamic response of the bond market to variations in risk appetite. The study reveals significant impacts of inflation and other domestic indicators on bond returns, a pattern consistent with mature markets, while also highlighting the intricate interplay between domestic economic conditions and global shifts. By incorporating a Risk State variable derived from the VIX index and considering local geopolitical events, the research provides an understanding of the dynamic bond market responses to varying risk perceptions and news events. This study contributes to the literature by utilizing a novel model to explain the determinants of domestic bond yields. The focus on is emerging markets, which is a segment that has been relatively ignored in past research. Also, this study explores the global and local news impact of government bond markets at a country level specifically focusing on the Turkish market. This part also addresses a gap in the existing literature by examining the effects on various bond maturities, offering insights into the entire yield curve's sensitivities in Türkiye. This analysis is facilitated by utilizing a comprehensive dataset consisting of economic forecast survey data. Overall, this comprehensive approach provides insights for investors, policymakers, and academics interested in the complex dynamics of emerging market bonds and the various domestic and international factors shaping their yields. Keywords: Emerging Market, Sovereign Bond Yield, Local Currency Bond Markets, Foreign Ownership Threshold, Global Risk Aversion, News Impact
Precious metals as a safe haven asset in the Islamic stock market
With the recent economic downturns exhibited as a result of the Covid pandemic, this research is developed through the motivation of investment tools that are resistant to negative effects brought about by changes in the economy. This brings out the current research being performed on whether precious metals can act as safe-haven assets in the Islamic stock market through the investigations using Granger causality, Impulse response analysis, stationarity testing as well as exploration of the Vector Autoregressive models to observe and outline the relationship between the precious metals and the Islamic stock indices. Using a substantial dataset that ranges from 1997-2023, the research uses stationary testing to ascertain whether the model is fit to be analysed using the impulse response method. The main concentration however of course would be on the impulse response method as that method tells us the direction of the relationship as opposed to the granger causality approach that outlines whether the relationship is present. The results suggest that there are causal relationships exhibited between majority of the precious metals and the Islamic stock indices through the use of the Granger causality method. There are some exceptions due to other factors that can affect the relationship such as uncertainty of the length of the pandemic among others. More notably, the impulse response function develops the notion that the precious metals have exhibited safe-haven attributes in the short run during the considered Coronavirus pandemic however overall, a positive relationship was observed during the time period of the dataset.
Return and volatility spillovers among trading partners: Evindence from Turkish market
In this thesis, the dynamic structures of returns, volatility spillovers, and conditional correlations between Turkish stock and bond indices and the relevant indices of countries with which Turkey has both high and low trade relationships in terms of exports, imports, foreign direct investment inflows, and foreign direct investment outflows during the period from January 1, 2015, to December 31, 2022, are examined. The specific indices used for the study, from each selected country include the primary stock indices representing the overall market, four sectoral indices representing manufacturing, finance, technology, and telecommunications, and a 10-year bond index. The countries in the High-Trade group are Germany, UK, Italy, Netherlands, USA, and China, while the Low-Trade group includes Australia, Sweden, and Canada. Another significant aspect of this work is the examination of how the global Covid-19 pandemic has affected the variability of returns, volatility spillovers, and conditional correlations for these indices among Turkey and its trading partners. The exact date of the Covid-19 pandemic is determined by relevant structural break tests. Finally, the effects of the returns of four different exogenous variables, namely the Volatility Index (VIX), Brent Crude Oil (BRENT), Currency Exchange (USD/TRY), and Credit Default Swap (CDS), on conditional correlations are separately examined. Structural break tests (ICSS) were applied to determine the exact date of the Covid-19 pandemic. Vector Autoregressive-Asymmetric Dynamic Conditional Correlation (VAR- ADCC-GARCH) method was used to examine returns and volatility spillovers. The Generalized Autoregressive Conditional Heteroskedasticity with External Variables (GARCHX) method was applied to analyze the effect of external variables on conditional correlations. The contributions of the study are five-fold: First, the existence of connections between Turkey's financial indices and those of countries with high or low trade volumes. Second, determining the actual break dates in each Turkish financial market instead of relying on the Covid dates announced by the Turkish Ministry of Health, and subsequently identifying the effects of Covid. Third, considering sectoral indices for portfolio diversification purposes for market makers and decision-makers. Fourth, integrating 10- year bond indices, which serve as a significant indicator of countries' macroeconomic data, into the system alongside stock indices. Lastly, measuring the impact of exogenous variables on conditional correlations between countries. The results of this study may help identifying contagion effects of spikes in returns and volatility in financial markets, and, therefore, providing investors with insights to diversify their portfolios and hedge risks effectively.
Time-frequency analyses on the relationship of Islamic indices with financial assets
Islamic financial assets have become an indispensable tool in today's financial ecosystem. The purpose of this study is to examine whether a portfolio manager using Islamic financial products effectively uses the methods used for traditional risk protection and to reveal possible solutions. As a result of the examinations, it was concluded that especially equity-weighted Islamic financial assets could not show a significant difference from normal equity-weighted conventional financial assets on an index basis, and since they could not show this difference, they could not be used effectively in risk diversification. Following this result, research was carried out to create an index with new Islamic criteria and it was found that it performed relatively better than the Islamic financial indices used today in terms of risk allocation and performance.
The influence of innovation on corporate performance: An empirical study of Turkey in manufacturing sector
This paper explores how innovation changes corporate performance in developing environments. The analysis focuses on manufacturing companies listed on Borsa Istanbul (BIST) from 2011 to 2020. By applying panel data techniques, the research evaluates how three key innovation indicators—R&D intensity, patent filings, and intangible assets excluding goodwill—relate to financial outcomes, specifically ROA, ROE, and ROS. The empirical data reveal that continuous R&D activities positively affect performance, especially ROE. The analysis finds that intangible assets affect company performance, while patent applications have no statistically significant link to short-term financial results. The study also notes that cutting-edge technologies such as AI and Industry 4.0 increasingly drive innovation and influence how companies plan their strategies. The findings indicate that they need to make continuous innovation investments to maintain their competitiveness and respond to changes in the industrial environment.
Effect of technology on return and risk metrics for insurance firms
The advent of Insurtech is catalyzing a transformative shift in the operational landscape of the insurance industry, reshaping its entire value chain. From product development, market strategies, and distribution channels to fundamental functions like pricing, underwriting, and claims processing, Insurtech has become ingrained in every facet of the industry. Insurtech's influence extends to addressing inherent weaknesses within the insurance industry. By pushing forward the construction of industry infrastructure, enhancing risk management practices of insurance companies, and fortifying regulatory capabilities and supervisory tools, Insurtech is not merely a technology-driven innovation but a catalyst for systemic improvement. A key facet of Insurtech's impact lies in its facilitation of collaboration among industry participants, enabling the sharing of infrastructure. This collaborative approach signifies a departure from traditional models and holds the potential to create a more robust and interconnected insurance ecosystem. Furthermore, Insurtech is steering the insurance industry towards high-quality development. It facilitates advancements such as scenario-based insurance, tailored product customization, optimized services, targeted underwriting processes, and instantaneous claims settlement. These innovations address longstanding challenges that were a source of public discontent, paving the way for an era of high-quality development within the industry. In essence, this research explores the pervasive influence of Insurtech, not only as a technological enabler but as a driving force behind the evolution of the insurance industry. It analyzes how Insurtech is contributing to the creation of a new operational paradigm, fostering collaboration, mitigating weaknesses, and propelling the industry towards a future marked by high-quality, customer-centric, and technologically advanced insurance solutions.
Intersectoral linkages among non-performing loans
Bank loans are known as the most basic element for the advancement of markets and sectors and the turning of economic wheels. The existence of bank loans in different sectors or business sectors is of high importance, and the non-payment of these loans creates a great problem for the economic functioning. This unpaid loan is defined as a non-performing loan. The existence of unpaid loans not only affects the economic functioning, but also emerges as a situation in which market reliability is damaged on a sectoral basis. Loans of banks or financial institutions play a critical role in order to keep the economic wheels turning in free market conditions in Turkey. For this reason, it is possible to easily say that loans serve as a great support at some point. However, in countries with sensitive economies such as Turkey, non-performing loans cause the functioning of the markets to deteriorate and economic crises to arise. In this sensitive market environment, the risks of the sectors in benefiting and repaying bank loans are related. Methodologically examining this relationship in the light of statistical data is the healthiest method. In this work we examine whether there is an intersectoral relationship among NPL ratios of bank in Turkey, and if there is, whether this relationship depend on the bank type. We found that there are strong correlations among the NPL ratios of various sector and bank type seems to matter in intersectoral relationships during our sample period 2007-2022.
Essays on the relationship between investor sentiment and stock returns
This dissertation investigates the relationship between investor sentiment, sovereign credit ratings, and sectoral index returns within G20 countries that are members of the OECD, for the period from June 2018 to April 2024. Employing a panel data analysis framework, the study explores how consumer and business confidence affect stock market performance across five major index categories: prime, energy, finance, industry, and technology. It extends previous research by integrating sovereign credit ratings alongside sentiment indices to evaluate their combined impact on the stock exchanges of G20 nations within OECD countries. Regarding sovereign credit ratings, four types of dummy variables were constructed: (i) standalone ratings, (ii) rating upgrades (iii) rating downgrades, and (iv) all rating-related changes, including outlook revisions and watchlist adjustments Although most of the existing literature typically focuses on either sovereign ratings or consumer sentiment, this research integrates both consumer and business sentiment measures alongside sovereign credit ratings to evaluate their individual, interaction, and triple interaction effects on equity returns. The analysis includes macroeconomic control variables such as CPI, exchange rates, and industrial production and incorporates the effects of COVID-19 pandemic and the Mortgage Crisis. Empirical results show that while sovereign credit ratings do not display a consistent direct impact on sectoral returns, investor sentiment, particularly business confidence plays an important and positive effect in shaping market outcomes. Consumer confidence is also found significant in the majority of cases. Moreover, sovereign credit ratings have notable interaction effects mostly observed in the energy and prime sectors through carrying sentiment effect into stock prices. Triple interaction terms involving rating, consumer and business confidence indices demonstrate a statistically significant negative effect on the energy sector. This finding indicates that the joint deterioration in sovereign credit quality, consumer sentiment, and business confidence may increase downward pressure on returns in this sector. Additionally, the study finds that among macroeconomic variables, CPI influence all sector returns whereas exchange rates influence sector-specific returns, while industrial production do not demonstrate statistical significance in general. Among the two crisis periods covered, the COVID-19 crisis dummy reveals a significant effect solely on the energy sector, highlighting its sector-specific sensitivity during the pandemic period while the mortgage crisis does not show any statistically significant effect on the performance of the analyzed indices. This thesis contributes to the literature by demonstrating a comprehensive cross-country, cross-sectoral analysis that gathers sentiment and sovereign credit risk perspectives, providing new insights into how financial markets process macroeconomic information and behavioural signals. The findings carry implications for investors, policymakers, and credit rating agencies in understanding how structural and psychological factors interact to shape equity market patterns in advanced economies.
Wavelet denoising and detrending analysis of gold prices and usd/try exchange rates
For this thesis, nonlinear dynamics of gold prices and USD/TRY exchange rates between January, 03 2005 and February 18, 2015 have been investigated through wavelet based denoising and detrended methods. Four different types of wavelet family namely, Haar, Daubechies, Meyer and Symlet have been employed within the stationary wavelet transform (SWT) framework. The purpose of this thesis is twofold. Firstly, we compared different wavelet thresholding methods of universal, Stein's unbiased risk estimator (SURE), false discovery rate (FDR) and global cross validation (GCV) thresholding algorithms for both hard and soft thresholding to remove the noise inherent gold price and USD/TRY exchange rate data. According to signal-to-noise (SNR) and peaked signal-to-noise (PSNR) ratio, hard thresholding method provides better performance in extracting noise from the original data. Moreover, SURE method seems to be superior compared to other methods in terms of SNR and PSNR values. Another important empirical finding is that Symlet wavelet with 8 vanishing moments have higher SNR and PSNR values. Secondly, cyclical behaviour of gold price and USD/TRY exchange rate dynamics have been uncovered via wavelet map indexing. The results suggest that SWT based detrending models provide good cyclical components for gold price and USD/TRY exchange rate data.
Concentration and economic growth in the automotive sector in Turkey: An econometric approach
The automotive industry has a connection between other sectors, due to this reason the automotive industry is accepted as a leader sector in country`s economy. In our study economic growth is defined and is focused on an improvement of automotive industry in planned period, export, import, employment and economic growth theory. The aim of this study is to determine the concentration trends in the different parameters of the business organisation in the sector, to observe its effect on the economy. The concentration ratio was analyzed by Herfindahl Index and concentration rate index. The value of concentration affects the technological efficiency and affects economic growth. The measurement of concentration has been made in this study in order to examine the growth of the automotive sector.In the next section, the releation between automotive sector`s export, import, turnover, employment, concentration and economic growth is analysed with panel data analysis method. This study`s data, which is contained 18 companies`s data that are providing in Turkey, is based on Uludağ Automotive Industry Exporters' Association (OIB) and Automotive Manufacturers Association (OSD) Bulluteins and panel data analysis were analysed with E-views. The results obtained of this of this analyses are determined in the conclusion. Keywords: Panel Data Regression Analysis, Concentration Ratio Analysis, Economic Growth Models, Economic Growth Factors
Empirical essays on stock market linkages
Understanding the dynamics of stock market linkages is of paramount importance for global investors, portfolio managers and policy makers. The main objective of this doctoral dissertation is to analyze the time-varying co-movement dynamics across international equity markets. The thesis consists of four independent empirical essays. The first essay investigates the dynamic correlations between emerging and developed markets, paying special attention to the effects of recent and extant financial and debt crises. The results show that the level of correlations significantly increases during the crisis episodes and these crises induce contagion effects. The second essay focuses on extending a directional spillover methodology by using asymmetric price ranges. The empirical findings suggest that downside risks dominate upward risks in cross-market spillovers. We also find that asymmetric spillovers are episodic; the magnitude of asymmetries is quite small after the global crisis of 2008 compared to the pre-crisis period. The third essay examines stock market integration at the regional level and conducts an equicorrelation measure. Focusing on six different regions, the results provide evidence of increased intra-regional linkages over the entire study period. We also investigate conditional diversification benefits and find that these benefits significantly diminish in the last years, particularly for the developed regions. The last essay focuses on the macroeconomic, cultural and geographic determinants of stock market synchronization in G7 economies. The results reveal that real macroeconomic convergence, global shocks and geographical proximity are more important in determining equity return linkages than cultural distance.
Bayesian estimation of the parameters of the ARCH and GARCH models using lindley's approximation
Autoregressive conditionally heteroscedastic (ARCH) and Generalised ARCH (GARCH) models are used to analyze empirical financial data and capture various stylized facts in financial econometrics. The procedure that is most commonly used for estimating the unknown parameters of ARCH and GARCH model is the maximum likelihood estimation (MLE) method. In this study, it is assumed that the parameters of the ARCH and GARCH models are random variables having known prior probability density functions, and therefore they will be estimated using Bayesian methods. The Bayesian estimators are not in a closed form, and thus Lindley's approximation will be used to estimate them. The Bayesian estimators are derived under squared error loss (SEL) and linear exponential (LINEX) loss functions. Examples are given in order to illustrate the findings. Furthermore, Monte Carlo simulations are performed in order to compare the ML estimates to the Bayesian ones. Finally, conclusions on the findings are given.
Towards better protection from superiority by increased precision in detection: The case of financial markets with informed and high-frequency trading
This study progresses towards the improvements and developments of measurement methodologies for informed trading and high-frequency trading (HFT) in financial markets. First chapter suggests an unbiased computation methodology for the broadly implemented PIN (Probability of Informed Trading) (Easley et al., 1996) measure. Multiple initial parameter sets are strategically determined by a developed clustering algorithm. Besides, computing time is reduced to one seventeenth. In the next chapter, a new measure, Multilayer Probability of Informed Trading (MPIN) is proposed. This rests on demonstrating that only 3.59% of empirical datasets have single information type as assumed by PIN model. Number of information layers in the model is not constant but exogenously determined by a clustering algorithm searching for separate Skellam distributions in daily numbers of absolute order imbalances. Respective solutions are provided for extended computational problems. While PIN estimates are heavily biased for simulations with multiple layers, MPIN estimates are bias-free regardless of number of layers. Mean quarterly MPIN (PIN) estimate is 31.9% (23.7%) for 361 stocks listed in Borsa Istanbul (BIST) between Q1 2007 and Q1 2014. Third chapter measures the extent of HFT in BIST by examination of 243 million messages in 85 million orders. Initially, the methodology suggested by Hasbrouck and Saar (2013) is applied. Next, an extended methodology is proposed and implemented. This is based on the linkage of same-sized orders of a stock if they have messages (submission, modification or cancellation) arriving within a low latency of a second. While this measure attributes around 6% of all orders to HFT, this rate is twofold for large orders and portfolio/fund firm orders.
Modelling credit rating transition probability matrices
Increased risk of credit related exposures and contagion effect of the recent Global financial crisis have led to stringent regulations and the need for accurate credit risk models. This thesis investigates and addresses various issues related to rating migration and default probabilities in the context of credit risk. The present study contributes to the literature on transition probability matrices in three different aspects. In the first part, conditional models are presented for transition probability matrices using macroeconomic variables. The model is applied for sovereign entities considering short term horizon and incorporates asymmetric distribution assumption. This is found to provide superior results compared to the traditional symmetric models. The second part proposes a simulation based methodology for the stressed transition probability matrices. The model targets accuracy of credit loss estimations and uses conditional correlation dynamics. This is analyzed under different portfolio structures and the model outputs capture economic contraction periods. The third and the final part introduces a smoothing methodology on the transition probability matrices using a risk sensitive loss function. The model results are consistent with empirical observations and the desired theoretical properties. Portfolio credit risk simulations are performed to estimate the impact of smoothing.
Three essays on dynamics of firm-specific performance: Intangible asset, financial openness and uncertainity
Which characters of firms provide sustainable competitive economic performance gains importance nowadays. According to the Resource Based View (RBV) the key factor in this field is intangible assets. 3 dynamics on the economic performance of the firms are defined as company-specific internal dynamics, integration with financial markets and sectoral concentration and global and local risk factors. General derivations are i-) Size effect, trade openness and intangible assets enable the firms to gain competitive advantages in their sectors. ii-) Although the rise in the amount of intangible investment affects positively short-term economic performance of firms, it does not have a positive effect in achieving a sustainable competitive advantage. It has been observed that intangible investments and market power-trade openness simultaneously have a positive influence on sustainable competitive performance. iii-) While it is observed that financial openness alone decreases the economic performance of companies in the mean, the covariate effect of financial openness with trade openness and herfindahl index is more effective in economic performance. iv-) Sectoral concentration harms overall economic performance of the firms. v-) The uptrend in all indices of uncertainty has lowered the economic performance of the firms in the mean. vi-) In an environment of increased uncertainty, blue-chip companies and high exports firms are regarded as safe havens. The data obtained from financial statements between the years 1995-2014 of above 200 firms traded at Borsa Istanbul are used. Generalized Method of Moments is used to solve the equations through the thesis.
Three essays on economic growth:Economic freedom, intra-industry trade, foreign direct investment
Economic Freedom affects countries' economic development and their progress. However, economic growth is not only influenced by economic freedom, but also by other institutional factors and structural parameters such as savings rate, human capital and research and development expenditure, commercial and financial openness (Trade, Foreign Direct Investment and Financial Integration), infrastructure, competitiveness, financial development. This study aims to analyze the determinants of economic growth. The main findings of Chapter 2 are similar with the resource curse literature and general accepted theories i.e. economies rich in natural resources have tendency to grow slower than resource-poors and quality of institutions determines the curse or blessing in Natural Resource Rich countries. Economic freedom and its determinats show positive effect on Total Factor Productivity growth. In Chapter 3, the effects of Economic Freedom, Foreign Direct Investment, Human Capital, Intra-Industry Trade and their interaction effect together on Total Factor Productivity Growth are analysed and relation between Total Factor Productivity and other variables in both Natural Resource Rich countries, Organisation for Economic Co-operation and Development countries (OECD), except Foreign Direct Investment in Natural Resource Rich Countries has been observed. Whether Economic Freedom stimulates macroeconomic growth within non-linear endogenous growth model with the other growth determinants namely Saving Rate and Labor Force is analyzed in Chapter 4. Findings show relation between economic freedom and per capita growth.
A cross-market comparison of the month of the year anomaly for bitcoin
According to the Efficient Markets Theory, asset prices reflect all information regarding the assets, and there should be no consistent patterns in returns based on calendar time or any other market differences. We examine if there are calendar time market anomalies in the crypto currency markets, and whether these anomalies, if any exists, vary across different markets based on the location. Specifically, we focus on Bitcoin, the largest crypto currency market, and search for the evidence regarding the month of the year effect anomaly in the Bitcoin markets during the period of 2015-2018. To see if market characteristics change based on the location, we compare the presence and the characteristics of the month of the year anomaly among three different Bitcoin exchanges: Bitfinex, Bitstamp and Okcoin. We find a strong month of the year effect anomaly in the Bitcoin markets during the period of our study. Although the general results are similar, we find some differences with respect to the month of the year effect anomaly among the three Bitcoin exchanges considered.
The relationship between development of finance and economic growth
At last dates have been made important many academic and observational studies on importance of financial indicators in encouraging economic growth. The interrelation between finance market progress and economic growing negatively affected economic performance after global crisis. Like these situations show us the degree of importance of studying the interrelation between finance market progress and economic growing. This study, reveal a new special revisable of scientific studies, as well as new observational and statistical proof on the interrelation between finance market progress and economic growing for a wide cross-section sampling of forty-one states for the time period of the first quarter of 1999 to third quarter of 2011. We use a range of econometric approaches, focusing on developed and developing countries. Finance market progress is measured by five variables to keep the different dimensions of the financial systems. These variables are total current account balance (percent of GDP), exchange rate (national currency to USD), net direct investment ratio to GDP, total loan to private sector (percentage of GDP) and interest rate. The result of study shows us the presence of causality and the trend way of causation between finance market progress and economic growing. It is determined by the factors that are chosen to represent progress of finance. We use Panel Var and GMM method to detect every aspects of this relationship. In addition, the interrelation between finance market progress and economic growing indicate differences among states in spite of these economies have almost identical structural features.
Essays in financial economics, timing ability of mutual fund managers
This dissertation explores three different issues regarding mutual funds, consisting of three empirical studies. The first study investigates the evidence for market timing in the Turkish Real Estate Investment Trusts from 2004 to 2014. To this end, twenty-five Real Estate Investment Trusts in Borsa Istanbul are analyzed in three sub-sample periods around the Global Financial Crisis in 2007: Pre Crisis (2004-2006); Crisis (2007-2010) and Post-Crisis (2011-2014). As our findings indicate, there is no evidence that the Turkish Real Estate Investment Trusts have employed effective market timing. The second study examines the market timing abilities of Turkish variable-fund managers during 2011-2016 in a panel data framework, using interaction variables to assess the impact of global emerging-markets portfolio returns, country openness, technology advancement, economic growth, and derivative market size on these. For emerging markets, factors that impact the growth and development of the mutual fund industry may also be relevant. Our results show strong evidence for market timing ability, which increases with economic growth, country openness, global emerging-market portfolio returns, to a smaller extent for derivative market size, and decreases with technology advancement. The third study examines the liquidity timing ability of Turkish variable fund managers during 2011-2018, and how this ability is affected by the environmental factors such as the technological advancement level, the presence of derivatives market, the growth in the overall economy, the level of market openness, and the performance of portfolios for foreign exchange, gold, bond, real estate, and emerging markets. We use interaction variables within a panel data framework. We find strong evidence of liquidity timing ability of mutual fund managers even after controlling for environmental factors. The nature of the interactions for most of the control factors with liquidity timing ability is strongly significant and differs based on the factor.
Advanced nonlinear and nonstationary methods for the analysis of financial time series
A broad range of advanced subjects and methods for nonstationary and nonlinear time series analysis comprises this thesis. These researches and their contents are summarized as follows. The wavelet coherence is investigated and applied on FTSE 100 and S&P 500 with several major Asian markets and major real estate markets. It is revealed that the developed economy stock markets have strong influences over Asian stock markets. These relationships are used to develop a VARMA based forecast model that shows less forecast errors than the models constructed with individual time series. Moreover, the multiple wavelet coherence is added for the analysis of dynamic correlations between three time series together. The chaos related properties of FIGARCH(p, d, q) processes are examined by computing the correlation dimension and the largest Lyapunov exponent from the stochastic difference equations directly and the simulated time series through mutual information, false nearest neighbour method, Wolf's algorithm, Kantz's algorithm and Jacobian algorithm. A new stochastic modelling and forecasting method for the chaotic noisy Duffing map series and for the financial time series with identical characteristics is introduced. The combination of telegraph process and the fractional Gaussian noise is fitted to the noisy Duffing map series that possesses regime switching and long-range dependent characteristics and then the real-world financial time series with identical features. Multiscale correlation dimension (MSCD) is proposed as a new method for chaotic properties of time series. Based on MSCD method, fractal dimension and Hurst exponent relationship is investigated in multiple scales on several time series.
IFRS 16: Comparasion of sectoral impacts of IFRS 16 on financial ratios
The purpose of this thesis is to analyze the impacts of the replacement of IAS17 by IFRS 16 regarding leasing transactions. This replacement impacted mainly operating leasing. In IAS17, operating leasing are considered as off-balance sheet items whereas IFRS16 treats them like financial leasing and are assumed one-balance sheet items, except few exceptions. This change impacts mainly financial ratios and the firm value. These elements are very important for fund providers, clients, stockholders, and share price…. In this thesis we analyze the impact of the adoption of IFRS16 on Turkish firm. Financial ratios of retained firms as well as their values are determined and analyzed.
Dynamic analyses of the relationship between non-performing loans and macroeconomic indicators in the Turkish financial sector
This study applies vector autoregressive (VAR) methodology to analyze the dynamic relationship between Turkish banking sector's non-performing loans (NPL) and the macroeconomic indicators during the period of 2004-2010. The vector autoregressive model is one of the most flexible and easy to use model for the analysis of multivariate time series. The VAR models have been used especially for describing the dynamic behavior of financial time series and also for forecasting. Besides data description and forecasting, the VAR models can also be used for structural inference and policy analysis. On the other hand, restrictions (exogeneity of some of the variables and etc.) may be imposed on VAR models regarding statistical procedures. Variables used in the VAR model are Non-performing loans to total banking sector loans ratio, real effective exchange rate, gross domestic product, nominal interest rates, consumer price index and foreign trade import volume index. All of the historical series consist of quarterly data covering the period of 1997-2003 and 2004-2010. Our impulse response analyses show that it takes at least 8 quarters to see the impact of unexpected changes in the gross domestic product growth rate, the real exchange rate, and the import volume on the non-performing loans while unexpected changes in the nominal interest rate (the policy rate) impact the non-performing loans within six quarters. The results from our variance decomposition analyses suggest that stress tests solely based on macroeconomic indicators, may not give sufficiently early warning signals about the potential upcoming credit crisis and that most powerful predictor of the banking sector non-performing loan ratio is the previous values of the ratio itself. Thus, policies only dealing with macroeconomic factors may not be sufficient to fend off any likely financial crisis in Turkey.
Kredi riski ve derecelendirme
In the thesis, firstly, the meaning of credit is defined and categorized, in chapter two with the aim to analyze credit risk issue in the next chapters. As a result of financial liberalization achieved in global markets in last decades, investment possibilities around the world have been boosted and this development has led to lots of opportunities and risks. In Chapter three, risk management is explained with the aim to explore the benefits of risk management in the financial institutions. In Chapter four, types of credit risk are analyzed. The aim of this thesis is to create a rating system which enables to analyze the creditworthiness of the firms with objective criterias. In chapter five, rating system methodologies are discussed. In Chapter six and seven the impacts of credit risk on the profitability are discussed and credit risk models are explained. Also importance of credit analysis are discussed. The stages to create a rating system are analyzed in the chapter eight. After explanation of credit rating in chapter eight, three well known rating agencies are considered. The financial ratios used by this rating sytem are explained in detail in chapter ten. The principles of the rating sytem is based on liquidity ratios, solvency-ability to meet key term obligations ratios, profitability ratios, Altman Z scores, Z prime scores and the industry averages published by TCMB. Rating score cards are calculated for 11 firms which are traded in ISE. The results obtained of this rating system are determined in the conclusion.
Stock market volatility and macroeconomic performance in the Nigerian economy
This thesis seeks to investigate the impact of stock market volatility on macroeconomic variables, specifically on real GDP and inflation, in Nigeria using quarterly time series data from 1985Q1-2012Q4. To achieve this, the study establishes two equations: real GDP and inflation equations, and splits the analysis into two parts. In the first part, the study employs four volatility models: ARCH, GARCH, EGARCH and TGARCH models, and compares them based on both model selection criterion and forecast performance in order to choose among them the fittest model to All Share Index (ASI) series (which is used as a proxy of the Nigerian stock market index). The TGARCH model was then selected as the best model, and therefore, the Nigerian stock market volatility series were extracted from it. In the second part, the thesis applies Bounds test co-integration approach and ARDL model. The results from the Bounds test analysis suggest the existence of co-integration relationship between the Nigerian stock market volatility and macroeconomic variables. While, the results from the ARDL model indicate that the stock market volatility has no any significant effect on the real GDP in both long-run and short-run and on the inflation in the long-run in Nigeria. However, the results also show that in the short-run, the Nigerian stock market volatility has significant positive impact on inflation. Keywords: Stock Market Volatility, Real GDP equation, Inflation equation, ARCH Family Models, Bounds tests, ARDL Model
Efficiency and productivity in Turkish banking sector
We study the efficiency and productivity growth in Turkish banking by using the non-parametric method, data envelopment analysis (DEA) and the Malmquist index in the period of 2003-2012. One aim of the study is to examine whether the banking reforms undertaken after the crisis in 2001 have had any effect on productivity. This is also a period of rapid development in the banking sector as it is evident from the substantial increases in numbers of branches, employees, and ATMs, which should affect productivity. We find that productivity growth in Turkish commercial banking sector is 0.1 percent per year over the period, which is rather low. We also present some evidence that privately-owned banks have done slightly better than foreign banks. We also look into the effect of the Global financial Crisis in 2008, and conclude that contrary to the popular impression banking sector might have suffered from it.
Kredi derecelendirme üzerine bir model belirleme
Turkey has an institution-based finance system. In this system all types of businesses acquire the necessary funds mostly from the banks. That is why banks are the most important financial institutions in Turkey. In this regard the most important risk that the banks face is credit risk, which can be defined as the probability of default by the customer and subsequent loss incurred by the bank as a result of the default. For this reason it is of utmost importance by the banks to manage their credit risks efficiently. One of the ways to accomplish this objective is to evaluate the credibility of the businesses that apply for a loan or a line of credit. This evaluation process is called credit rating. In this thesis a multivariate statistical model is developed to accomplish the credit ratings of the businesses that are the potential loan customers of a bank. A unique data set is formed from the loan applications of a bank. Businesses whose loan applications are accepted and businesses whose loan applications are rejected are included in this data set. These businesses form the cases of the model. Independent variables are financial data (financial ratios and percentage changes). The best model for credit rating is found to be the logistics regression model (logit model). The most important variables that distinguish accepted and rejected businesses are found to be the net profit margin and debt ratio. As net profit margin increases, probability of acceptance increases. As the debt ratio increases probability of rejection increases. Key words: Credit rating, banking, loans, multivariate statistical methods
The efficiency of housing market in Turkey
This study investigates the efficiency of housing market and the validity of the ripple effect in Turkey. In order to do this, we examined the housing price dynamics of Turkey with various unit root tests in all 81 cities of Turkey by dividing them into geographical groups apart from İstanbul, Ankara, and İzmir according to the original grouping of Central Bank of Turkey where we acquired our data from. Along with a conventional unit root test which assumes structural stability and linear adjustment, a nonlinear unit root test and also a nonlinear unit root test with structural breaks were applied. Our tests proved evidently that the majority of housing markets in Turkey is inefficient even though the test results were mixed, and also the ripple effect does exists indeed. In the light of this information, the housing market in Turkey calls for urgent investigation towards the inefficient markets and ripple effect originating points. Keywords: Housing market efficiency, Ripple effect, Linear unit root test, Nonlinear unit root tests, Nonlinear unit root test with structural breaks.
External public debt management: Use of derivative instruments
Public debt is a financing tool that is frequently applied for increasing public spending in the face of increasing public costs or for financing large countrywide public investments.There have been many different schools of though and theory put forth on public debt from ancient times to the present day. The impossibility of achieving an equilibrium between market conditions and the understanding the state?s role of the social state in the economy is a reality accepted by virtually every country today. Taken in this context, for those countries that lack the internal dynamics for public debt financing to go the route of external borrowing to cover public debt is an unusual phenomenon.Budget deficits in developing countries have reached serious levels due to many global crisis?s that have developed in International markets, and cyclical changes that occur as a result of inflationary pressures. These countries which do not have a robust economy and financial structure had to resort to foreign borrowing to finance public deficits.This process of borrowing that gained substantial acceleration especially during 1980s, effecting the debt rates and services of developing countries? economies and thus jeopardizing the status of countries that has been the lender. This situation revealed that developing countries needed to focus on public domestic and external debt management. From this period forward, the debt management issues such as debt stock limit, risk ratio, internal and external debt sustainability gained importance for developing countries. During the same period, the derivative products emerged as a result of the studies performed in order to reduce the risks brought by borrowing in international markets. These products began to be used effectively by many developed countries to avoid risks such as exchange rate, interest rate, inflation. These products that were used in these markets grew as time went on and with the promotion of certain economic and financial institutions began to attract the attention of developing countries.The situation in Turkey was not different than in other developing countries. Especially after 1980, the external public debt levels increased sharply by means of economic and financial reforms that had been performed during this period. The derivative instruments which ensure the risk management and which emerged in the '80s as an alternative in the public internal and external debt management only began to attract attention at the end of the 90s in Turkey and the trading volume could be increased with the opening of the Derivatives Market in 2002. But this interest remained confined only to the private sector.It is not possible to ignore the benefits that may be obtained by use of derivative instruments when the past experiences of Turkey are observed.In this study it is explained the importance of a sound external public debt management and the advantages of use of derivative instruments within this frame. It is signified that evaluation and development of the derivative market will be advantageous, both in order for the economic development plans to be executed in a more clear way and in terms of assistance to the monetary policies to become successful.
Audit committee and committee subdivisions' characteristics versus operational risk oversight in Turkish banking sector
The main reason for financial scandals and crises experienced during the 2000s has always been addressed as lack of corporate governance; and accordingly, countless theories and suggestions have been asserted in order to develop appropriate corporate governance mechanisms. Nevertheless, because of missing data and abstractness of concepts, it has not been possible to measure completely whether these mechanisms were really effective, or whether they served their designated purpose. The present thesis analyzes, by means of the dynamic-panel data method based on unique data, the effect of important characteristics of internal audit, internal control, risk management, and audit committee mechanisms on operational risk, whose significance has substantially increased after the re-structuring developed in the Turkish Banking industry parallel to the international regulations that arose after the 2001 financial crisis. Also analyzed in terms of their comprehension capability regarding local economic environments are staff size, competence, reporting level, and explanation level of financial resource, as well as gender, auditing background of audit committee, and nationality. According to the study results, it was revealed that while there is almost no effect of the characteristics of the risk management department on operational loss, some characteristics of internal audits and internal control can mitigate operational risk. On the other hand, it was concluded that having female members and experienced members on an audit committee, and leaving off foreign-originated members, have significant positive impact on minimizing operational risk.
An attempt on the applicability of Basel III liquidity coverage ratio (LCR) and capital adequacy ratio (CAR) requirements to selected food retail sector firms and a comparison with traditional financial ratio analysis
Banks, in financial markets, work as intermediaries between who need funds and those who have fund surplus. Funds gathered from a person, agency or institute are placed to a person, agency or institute who need funds. At this point, banks have to pay their money to those who have fund surplus on demand, while call back from organizations who need funds at a particular time set when the money placed. Even though it's possible to recall a credit, this process is avoided for the reason that reputationally it has big reservations. Accordingly, in this point two main problems appear: First one is maturity mismatch and the second is credit safety. Maturity mismatch is the problem of being shorter the fund maturity of investors than demandants. The second problem is the situation that withholding payment of a placed credit when it is due or late payment. These two problems actually arise from a single point: liquidity. First point features the liquidity, in other words capability of obligation to pay, of the banks while the second of a person, agency or institute who demand funds. Spreading of financial crisis emerges with becoming unable of a financial institution after one or more debtor fail to discharge of obligation, because of inadequacy of liquidity, and accordingly with reaching a point of failing to discharge of obligation of this financial institution itself, failing the other creditor financial institutions successively. Financial crisis can reach a point that put even governments in a tight spot, it's essential that financial institutions and whom they lend to be liquid. This significance is evaluated within countries and in a platform between countries. Bank of International Settlements (BIS) set up a committee, named Basel Committee, in order to prevent emerging and spreading the financial crisis. This committee targeted to ensure the financial security of financial institutions taking some decisions. Financial criteria, with some changes, take their present form. The point to be emphasized is that these criteria only bind the financial institutions. There is no obligation for the debtors unless being a financial institution. Financial institutions use several evaluation standards while choosing the person, agency or institute to whom are credit a fund. Financial analysis is one of the methods to present the financial status of an institutions and the most significant of all evaluation tools in using evaluations of big firms. According to the criterion in consequence of this evaluation, a decision is made whether to give a credit or not. In this thesis, it is aimed to show the contingency situation in case of adaptation the liquidity and capital adequacy criteria to firms. While implementation process, we confronted an inconsistency problem of financial statements of between financial institutions and real sector firms. In order to overcome this problem we implemented transformation processes. Because of the scale difference, we also used some parameters and ratio smoothing, which committees and national board of audits use to audit institutions. We implemented this study to the firms which operates in stock market of retail industry, which we suppose that it is the most approximate sector to financial institutions from among the real sector firms. Three firms are analised and, then compared the ratio analysis, one of the financial analysis techniques and our adopted method.
Stochastic mortality using non - life methods
Although longevity and mortality risks have been studied for a long time, there has been a remarkable increase in the number and scope of these studies due to recent theoretical and practical developments. Such developments paved the way for a more detailed analysis of the asset-liability balance of life insurance and pension companies. The impact of these risks is huge albeit long-term. In addition to life insurance and pension companies, governments are also considerably affected through health expenditures and pension payments. Further, environmental impact on food and water supplies and pollution should also be considered as well as financial ramifications. Hence, the accurate modelling and forecasting of longevity and mortality risks has become more important than ever as the accelerating population increase is taking its toll on mankind both financially and environmentally. This thesis focuses on the most widely used stochastic mortality models. The results pertaining to historical death probability, force of mortality, life expectancy, and rectangularization behavior are analysed in detail. These models are applied to the data from 20 different countries. In terms of the variety of stochastic mortality models and the number of different countries, this study is singled out as the most extensive study to date. The main contribution of this thesis is the introduction of a new approach to model mortality. This approach is based on IBNR calculations in non-life insurance. The comparison of this approach with two extensively used models in practice, namely Lee and Carter and Renshaw and Haberman models, shows that the new approach outperforms the aforementioned models with UK data.
Foreign exchange risk and financial performance: The case of Turkey
The purpose of this study is to investigate the amount of foreign exchange open positions of manufacturing and service sector companies, to determine the effect of open positions on companies' financial performance and to find out the factors that contribute to the firms' tendency of keeping short foreign exchange position. The analysis conducted on 30 firms for the period spanning from the third quarter of 2012 to the second quarter of 2015 showed that operating profitability of the firms with short foreign exchange position was lower than operating profitability of firms with long foreign exchange position. The performed ANOVA test indicated that companies with short foreign exchange position were able to increase their overall profitability to the same level as companies with long foreign exchange position in periods when local currency was overvalued, but exposed to serious losses in periods of local currency devaluation. Applied regression analysis revealed that companies carried short foreign exchange position in the present period had higher liquidity and asset efficiency and lower overall profitability than companies with long foreign exchange position in the previous period Keywords: Short FX Position, Hedging, Financial Performance, Relative Purchasing Power Parity
The effect of crude oil prices on the foreign trade deficit - case of Turkey (2000-2015)
In this study, the relationship between Turkey's foreign trade deficit and oil prices, was analyzed with non-linear cointegration analysis for the period 2010-2015. The variables were analyzed using the Johansen Cointegration analysis after first differences were taken and stabilized. The results of the analysis revealed, a long-term positive relationship between foreign trade deficit and oil prices. The fact that the change in oil prices affected the foreign trade deficit with a delay of three periods is also among the findings of the study. It has been found with the Error Correction Model that the relationship is positive and the long-run correlations between oil prices and foreign trade deficit have stabilized by 38% compared to the previous turn. The findings of the econometric analysis, showed that the long-term relationship between oil prices and foreign trade deficits is positive consistent with the previous studies.
Kurumsal iktisat perspektifinden Türkiye'de vergi gayreti ve kurumsal kalite ilişkisi: Teori ve uygulama
Ülkeler arasındaki mali ve ekonomik farklılıkların açıklanmasında ana akım (mainstream) iktisada eleştirel bir açıdan yaklaşan Heterodoks iktisadi görüşlerin özellikle geride bıraktığımız yüzyılın son çeyreği ile birlikte tutarlı ve rasyonel katkıları yadsınamaz niteliktedir. Toplumların, gelişme – büyüme ve kalkınma ölçütlerinin salt ekonomik performansa bağlı değerlendirilmemesi gerektiğini, toplumların bir arada kalabilme ve hareket edebilme kabiliyetlerine yön veren hukuk, kültür, siyaset, tarih, eğitim, teknoloji, dil, din ve örf ve adetler gibi unsurların iktisadi analizlerin içine dahi edilmesini öneren Kurumsal İktisat son yıllarda gerek dünyada gerekse de ülkemizde popülerliğini artırma eğilimindedir. Vergi, geçmişten günümüze devletler nezdinde sadece kamu harcamalarının finansmanında kullanılmak üzere toplumun geneli üzerinden sağlanan bir fon olarak değil, aynı zamanda sosyal ve politik bir olgu olarak da önemli bir politika olma özelliğini sürdürmektedir. Verginin bu özelliği onun maliye otoriteleri açısından bir teknik mesele olarak ele alınmasından ziyade siyasi, kültürel, sosyolojik ve felsefi bir konu olarak tüm yönleriyle bütüncül (holistic) açıdan ele alınmasını gerektirmektedir. Doğurduğu sonuçlar açısından birey –devlet, birey – toplum ve toplum – devlet ilişkileri içerisinde karşılıklı etkiler yaratan vergi konusu Kurumsal iktisadın klasik sınıflandırmasından hareketle formal ve informal kurumlar çerçevesinde ele alınmış ve vergi uyumu, vergi ahlakı ve vergi kültürü gibi kavramlar irdelenmiştir. Bir kurum olarak vergi kavramı Türkiye açısından tarihsel perspektifte ortaya konularak, cumhuriyetin kuruluş yıllarından günümüze uygulanan vergi politikaları kurumsal iktisat perspektifinde eleştirilmiştir. Bu noktadan hareketle çalışmada 1984 – 2017 yılları arasında kurumsal kaliteyi oluşturan unsurlar ve Türkiye için gerçekleştirilen vergi yükü tahmini ve vergi gayreti hesaplamaları ekonometrik analize tabi tutularak elde edilen sonuçlar kurumsalcı bir yaklaşımla yorumlanmıştır.
Asimetrik panel nedensellik testi: Gelişmekte olan ülkelerin borsaları üzerine bir uygulama
Değişkenler veya olaylar arasındaki ilişki anlamına gelen nedensellik kavramı geçmişten bugüne kadar birçok bilim dalı tarafından inceleme konusu olmuştur. Nedensellik ilk olarak felsefe bilimi tarafından kullanıldıktan kısa süre sonra istatistik ve ekonometri gibi sayısal bilimlerin de ilgi alanına girmeyi başarmıştır. İktisadi değişkenlerin arasındaki ilişkilerin varlığının saptanması iktisat literatüründe var olan birçok teorinin temelini oluşturmaktadır. Bu sebeple iktisat literatüründe nedenselliğin önemi göz ardı edilemez. Ekonometri ise iktisadi teorilerin geçerliliğinin sınanmasına olanak sağlamaktadır. Bu teorilerin birçoğu nedensellik testleri yardımıyla açıklanmaktadır. Bu açıdan bakıldığında nedensellik ilişkisi ve bu ilişkinin test edilmesi son derece önemlidir. Asimetri ise birçok farklı tanıma sahiptir. Değişkenlerde asimetri, bir iktisadi zaman serisi değişkeninin meydana gelen pozitif ve negatif şoklara verdiği farklı tepkileri ifade etmektedir. İktisadi değişkenlerin şoklar karşısındaki tepkileri farklılık gösterebilmektedir. Bu farklılıklar göz ardı edildiği zaman değişkenlerin aralarında var olan ilişkiler ortaya çıkarılamayacaktır. Bu durum yapılan analizlerin güvenilirliğini azaltmaktadır. Bu noktada değişkenlerde asimetri dikkate alınarak aralarındaki saklı ilişkilerin bulunması mümkündür. Özellikle oynaklığın fazla olduğu değişkenlerde simetrik yerine asimetrik ilişiklerin incelenmesi daha güvenilir sonuçlar elde edilmesine neden olmaktadır. Bu çalışmada literatürde bir eksiklik olarak görülen panel veriler için asimetrik nedensellik testi geliştirilmesi amaçlanmıştır. Bu doğrultuda değişkenlerin asimetrik bileşenleri kullanılarak aralarındaki ilişki panelde yer alan her bir birim için ayrı ayrı incelenebilmektedir. Uygulama olarak geliştirilen asimetrik panel nedensellik testi, gelişmekte olan 11 ülkenin borsa endeksleri ile döviz kurları arasındaki asimetrik ilişkinin araştırılmasında kullanılmıştır. Bunun yanında sonuçlar simetrik panel nedensellik testi ile karşılaştırılmıştır. Çalışmanın sonuçlarına göre simetrik panel nedensellik testlerinin ortaya çıkaramadığı saklı ilişkiler yeni geliştirilen asimetrik panel nedensellik testi ile ortaya çıkarılmıştır.
Three essays on technology, trade, and business cycle: A dynamic econometric approach
The purpose of this thesis is to shed light on the implementation of forward-looking and counter-cyclical macroeconomic policies through an examination of technology and international trade processes using macroeconomic models. The thesis contains three independent chapters on PMG-ARDL and GMM econometric modeling of technology and international trade and estimating and evaluating a small open economy and middle open economy DSGE modeling as well as an introduction. In the second part of this study, we examined in detail the transfer of technology in terms of both developed and developing countries. In the third part of the study, we extensively investigated the dynamic and stochastic general equilibrium models, which have recently been used by many central banks in terms of analysis and planning of monetary and interest rate policies. In the final section, we extended the model for the same period to a middle open economy. Our research indicates that all countries benefit from technology transfer and that there is a long-term relationship between technology transfer and economic growth per capita. On the other hand, the simulation results for both small and medium open economy dynamic stochastic general equilibrium models are quite consistent with the Turkey macroeconomic variable data set. However, due to the high volatility of the macroeconomic variables used in the study, the model's simulated variables have large standard deviations. Both small and medium open economy general equilibrium models, while there are some parts to be improved, are excellent tools for analyzing optimal monetary policy for the Turkish economy.
Endüstri içi ticaret üzerine üç makale
This study consists of two different parts of international trade which are intra- industry trade (IIT) and foreign direct investment (FDI). The thesis has meaningful contribution to the literature both it collects the intra- industry trade values by various products and industries, strengthens determinants of IIT and FDI that are exits in the literature by new indexes and making a unique comparison between marginal intra- industry trade (MIIT) indexes to explain the relationship between MIIT and labor adjustment cost. In the first chapter, influence of currency crisis on foreign direct investment is observed with the situation of economic freedom level in the country. At the same time the chapter also presents determinants of FDI with the comparison of two methods of panel data in 37 countries in the period 1995 to 2017. The model provides special contribution to the issue of international trade by its indexes. In the second chapter, we took various eight products that are widely imported and exported in international trade to observed determinants of IIT in 40 different countries in the periods 2002 to 2018 in tobit model. The model improved by new indexes and new point of view to the related indexes that are also used in the literature. In the third chapter, we used three various indexes which were taken places in the literature to calculate marginal intra-industry trade (MIIT) on the issue of observation of labor adjustment cost. We investigated the relationship between marginal intra-industry trade and labor adjustment cost by compering different MIIT measurements.
Stochastic modeling of stock exchange markets: Three essays
In this study, stochastic modelling is applied to analyze time series of daily closing prices of BIST100 and major stock exchange indices to gain new insight and help develop new applicable tools for investors and market participants alike for their portfolios and investments. The study is comprised of three parts. In the first essay we present the applicability of heavy-tailed distributions with the generalized autoregressive conditional heteroskedasticity (GARCH) model and continuous-time, COGARCH, model with Meixner distribution for BIST100. In the second part, we examine the long memory prop erty of five major stock exchanges by considering different models and show that the autoregressive fractionally integrated moving av erage (ARFIMA) model is a better candidate than the fractionally integrated generalized autoregressive conditional heteroscedastic (FI GARCH) in modelling volatility of the stock indices studied. The fi nal essay focuses on wavelet transformation, which has gained some popularity recently, between DAX and NIKKEI stock indices, and show that there are some level of correlation and coherency between the two. The Hurst exponent also estimated and there exist signs of multifractal process in the time series.
News impact curve analysis and spillovers during COVID-19 pandemic case studies: Pharmaceutical industry, tech companies (Faang) & airline industry
The Covid-19 pandemic, which has gained momentum since the day it started, has taken the whole world under its influence. In this thesis, how the Covid-19 pandemic affected three sectors, namely the pharmaceutical industry, technology companies, and the airline industry, was investigated in three separate chapters. Sectors have been affected by the discovery of the vaccine as well as by the pandemic. In this context, in the first chapter, an analysis was made using the EGARCH Model and news impact curves to examine the effects on the returns of pharmaceutical and biotechnology companies. As a result of the measures and restrictions taken to prevent the pandemic from progressing, people started to work from home. People have had to start meeting many of their needs online because restaurants only offer takeaway, shopping malls are closed, etc. Therefore, the need for technology has increased even more in this period. Individuals, being locked at home, have turned to online broadcasts such as Netflix. In this context, in the second chapter, how the stock returns of Facebook, Apple, Amazon, Netflix, and Alphabet (FAANG) are affected by using the DCC GARCH model was examined. In some periods, travel has been imposed restrictions due to the increasing number of cases. With the discovery of the vaccine, restrictions have also changed. In the last chapter, an analysis has made using the Granger Causality Tests and Diagonal BEKK Model to examine long-term spillover effects among the two crude oil prices (Brent, WTI) and three US Airlines Stock prices (American Airlines Group, Southwest Airlines Company, and Delta Air Lines). By expanding the data set used in the study, more comprehensive results can be obtained and may guide future research.
Seküler durgunluk hipotezi üzerine üç deneme
In this thesis, The Secular Stagnation hypothesis is investigated from emerging and developed markets perspectives. The first chapter investigates the contagiousness of safe asset shortages as an implication of the secular stagnation hypothesis. Our motivation is to quantify the degree of financial contagion of safe asset demand among developed and emerging markets. In the second chapter, inspired by the universal law of gravitation, a new metric to measure the financial distance of countries has been created. In this metric, financial distance is directly related to Credit Default Swap (CDS) Spreads and is inversely associated with the Foreign Exchange (FX) Rate. The new metric has been used to optimize the hedging global fixed income portfolios. The third chapter aims to provide a new financial gravity framework to understand the nature of dependency on US monetary policy and its results. This thesis provides significant theoretical and empirical take aways by analyzing different aspects of secular stagnation hypothesis.
Large-scale forecasting of large fluctuations using wavelet coherence and multifractal behavior and developing wavelet coherence for multiple time series
Shocks, jumps, booms, and busts are typical large fluctuation markers that appear in crisis. Identifying financial crises and estimating leading indicators with strong relations during crisis periods have an essential role in the literature. This thesis examines the dynamic co-movements of leading indicators' multifractal features to identify financial crises due to large fluctuations. The detected dynamic relationships predict leading indicators with scale-by-scale analysis and make large-scale predictions better than challenger models. As a natural result of these studies, the n-dimensional wavelet coherence method is examined, and the vectorwavelet package is transferred to the R program. This thesis consists of three independent parts, and the contents of the studies are summarized below. In the first part, stock returns' co-movements with other leading indicators in crisis periods are analyzed with multiple and quadruple wavelet coherence using interest rate, exchange rate, and trade balance differences. The scale-by-scale wavelet transformation was used to predict large-scale relationships, and stock return estimation was performed. In the second part, the multifractal characteristics of sectoral default probabilities of the real sector in Turkey and Turkey sovereign CDS rates were examined by detrended fluctuation analysis. Significant dynamic connections between the Hölder exponents of the default rates and CDS during financial crisis periods have been examined. During the periods of financial crises, among the Hölder exponents, severely correlated large scales show multifractal features. Scale-by-scale wavelet transform has been used to predict large-scale relationships, and hence vector fractionally autoregressive integrated moving average forecasting provides better results than scalar models. The final part of the thesis introduces a new wavelet methodology to handle multivariate time series dynamic co-movements by extending multiple quadruple wavelet coherence methodologies. The primary motivation of our works is to measure wavelet coherence analytically for the specific dimension.
Three essays on co-movement in financial market: Fractal behavior, information flow, causality and forecasting
The behavior of financial time series, their interactions with each other, and analyzes of forecasts especially in crisis and shock periods, have gained an important place in the literature. In the coming years, such analyzes will find a place in many studies. The relationships between financial time series are a very important indicator in analyzing the economic shocks encountered. There are many methodologies and analyses on this subject in the literature. From this point of view, the aim of the thesis is to analyze the co-movement of financial time series, fractal behavior, the measure and direction of information flow, and future price forecasting, and to develop new analysis methods. The fact that all these methods have not been studied together is another starting point of the thesis. In the first part of the thesis, the co-movement of financial time series was analyzed by Wavelet coherence (WTC) method, crisis and shock periods were determined by Multiple wavelet coherence (MWC) method, then fractal behaviors were examined with Multifractal de-trended fluctuation analysis (MFDFA) method and for the post-crisis periods, daily price range estimations for the future were made by using the Vector autoregressive fractionally integrated moving average (VARFIMA) method, in comparison with real data. In the second part, a new method called Wavelet transform guided transfer entropy method (WTGTEM) has been proposed. In this new method, the co-movement of exchange rate time series has been examined with the Wavelet coherence (WTC) method, and the measurement and direction of the information flow between the financial series under the guidance of WTC have been analyzed by the Transfer entropy (TE) method. In the last part of the thesis, the new methodology presented in the second part has been applied to major stock indices. Especially during the COVID period, the behavior of the series has been analyzed, and it would be helpful for investors in portfolio diversification, especially in times of crisis. We believe that this thesis will guide future studies of this kind and that the methods used will be preferred by researchers.
Estimation of international trade
The study analyzed foreign trade volume among Turkey and 37 OECD countries, especially the sway of the LPI on Turkey's foreign trade volume. The effects of the LPI in determining Turkey's foreign trade volume were analyzed by using the data of Turkey and OECD countries in the 2007-2020 period. In the study, three different models were established in which the total foreign trade volume, Turkey's exports and imports with OECD countries are dependent variables. The variables used in the models are the GDP of Turkey and OECD countries, R&D investments, population, LPI, and distance between countries. Since the models have problems with autocorrelation, heteroskedasticity, and cross-section dependence, the Huber-Eicker-White estimator that robust to these problems, was used. When the results obtained were examined, it was concluded that the sign of the relationship between GDP and foreign trade volume of the countries in the model that the foreign trade volume was the dependent variable was positive. The gravity model has main variables used in the studies. Among these, the variable that expresses the geographical distance between countries is among the most used. In the study, the direction of relationship with trade flows is negative. Turkey's LPI positive affects foreign trade volume in the first two models. It's been observed that there is a positive relationship between the populations of OECD countries and Turkey's foreign trade volume, in line with expectations. When the study's primary purpose is evaluated, Turkey's LPI has a positive and significant effect on foreign trade volume.
A review on currency shocks and inflation volatility: Evidence from a DCC-GARCH model
In the present research, the relationship among the exchange rate and inflation in Turkey was investigated by considering the monthly dataset among 1990:1-2022:4 years. The consumer price index, producer price index, industrial production index, nominal exchange rate, and money supply are used as variables to represent inflation. Impulse-Response analyzes were used to find the short-term effects of the variables, decomposition of variance analysis for the causes of the changes in the variances of the variables, and the medium and long-term relationships of the variables in pairs were determined by DCC-GARCH models. While the models were being created, they were seasonally adjusted, and the inputs of the DCC-GARCH models were determined, consequently, the VAR analysis. In the results of the impulse-response analysis, it is seen that the reaction of inflation to the exchange rate shock is positive and lasts for five periods, after which the response fades. In the results of the impact-response analysis of the exchange rate, it has been determined that the reaction of the exchange rate to inflation has been stable for twelve periods. In the results of the variance decomposition analysis for inflation, at the end of twelve periods, 4.83% of the change in inflation was caused by the exchange rate; In the exchange rate variance decomposition analysis, it was concluded that 8% of the difference in the exchange rate was caused by inflation. While GARCH models show a negative interaction between inflation and exchange rate, DCC-GARCH results show that the permanence degree of short-term shocks between inflation and exchange rate is 0.43%. In addition, while a semi-strong GARCH process was found between inflation and money supply, a strong GARCH process was found between inflation and producer price index.
International gold prices, gold reserves of central banks and debt stocks relationship: Analysis among G8 countries
Gold is a commodity that has been used to protect the wealth of not only people but also organizations and states from past to present. For this reason, countries prefer to keep some of their reserves as gold through their central banks. At the financial macroeconomic level, the primary goal of countries is to sustain a healthy economic growth. However, when the economies of developed countries are examined, especially when the economic growth rate of the G8 countries, which are called the strongest countries class, is examined, it is seen that the public debt ratio is very high, which increases the risk levels of the countries. Therefore, it is expected that the gold reserve demands of these countries will be in a causal relationship with international gold prices. In this study, the causality relationship between the public debt stock of countries, international gold prices and gold reserve of countries is investigated based on this question. The country sample is based on the quarter between 2008 and 2020 of the G8 country group. The analysis method has been utilized by econometric methods and the relationship between variables has been examined with panel granger causality analysis. As a result, a unidirectional causality relationship has been found between the debt stock of countries and international gold prices, and between gold reservoirs and debt stock. Key Words: International Gold Prices; Gold Reserves of Central Banks; Panel Granger Causality Relationship; Public Debt Stock
The effects of climate change on financial markets
There is a critical relationship between climate change and financial markets. In this study, temperature change values are used to examine the impact of climate change on agriculture, banking, investment, and insurance sectors. The study determines the relationship between temperature changes and agriculture, banking, investment, and insurance indices in BIST by regression analysis. The results show that climate change has different impacts on different sectors. While the agricultural sector is more sensitive to temperature changes, its impact on the banking and investment sectors may be more limited. These results suggest that temperature changes directly and significantly impact the financial performance of the agricultural sector and provide a broad understanding of the potential impacts of climate change on financial markets and the agricultural sector. In addition, the insurance sector can be affected by climate change, and temperature increases can trigger changes in insurance indices. These results emphasize that climate change is an essential factor in financial sector performance and risk management. In this context, policies and strategies to combat climate change should focus on promoting stability and sustainability in financial markets.