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Türkiye'nin 2023 vizyonu ve dış ticaret hedefleri
Ülkelerin geleceği planlamaları yeni bir kavram değildir bu anlamda ülkeler gelecekte olması gereken politikalarını planlayarak veya hedefleyerek ekonomik siyasi anlamda çağdaşlaşma hedeflerini gerçekleştirmeye çalışmaktadırlar. Vizyon 2023 Projesinin ana teması; Cumhuriyetimizin 100. yılında, Atatürk'ün işaret ettiği muasır medeniyet seviyesine ulaşma hedefi doğrultusunda ülkemizde siyasi ve ekonomik alanda gelişmektir. Ülkemizde başlatılan 2023 hedefleri ile ekonomide sektörlerin gelişimi ile birlikte gelişme kaydedilecektir. Bu gelişme ülkemizin dünyada söz sahibi olan ekonomisi büyük ve dış ticareti son derce gelişmiş bir ülke haline getirecektir.Çok uzaklarda görünüyorsa da stratejik Türkiye Vizyonu için hedef olarak Cumhuriyetimizin yüzüncü kuruluş yıldönümüne denk düşen 2023 seçilmesi kitlelere yön göstermek, motivasyon sağlamak bakımından önemlidir. Böylesi bir vizyon çalışması tarımdan eğitime, yabancı yatırımlardan bilgi ekonomisine, dış ticaret ve dış politikadan su sorununa, sürdürülebilir kalkınmaya, güvenlik mimarisinden kent planlamasına, AB üyeliğinden alternatif enerji kaynaklarına, kültürel yenilenmeye kadar uzanan geniş bir menzilde değişen dünyanın ve değişemeyen Türkiye'nin fotoğrafını çekmeye, geleceğe dönük görüş ve önerileri, kestirimleri paylaşmaya çalışmalıdır.Şüphesiz bu amaçları gerçekleştirmek hiç de kolay olmayacaktır. Bu açıdan öncelikle harekete geçmesi gereken bazı unsurlar vardır. Bunlar teknoloji, enerji politikaları, KOBİ politikaları ve yatırım politikaları v.b ülkemizin dünya ülkeleri arasında büyüme potansiyeli açısından iyi bir konumda olması her şeyden önce dış ticarete yansımalı ve ekonomik büyüme ile beraber dış ticaret hacmimiz de artmalıdır.
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.
Three essays on volatility forecasting, option pricing, and value at risk forecasting using neural network models
This thesis consists of three chapters, each addressing important topics in financial forecasting using a combination of traditional and modern approaches. The first chapter explores the application of a hybrid GARCH-LSTM model to forecast market volatility. By integrating traditional econometric models with long short-term memory (LSTM) networks, the study demonstrates the potential of combining machine learning with established methods to improve volatility forecasting accuracy. The second chapter introduces the Stochastic-Local-Jump Volatility Option Pricing Model (SLJV-OPM), which combines stochastic volatility (Heston model), jump diffusion (Merton model), and local volatility (Dupire model). This model formalizes their integration using the Expectation-Maximization (EM) algorithm, providing a systematic method for calibrating the contributions of each component. To the best of our knowledge, this is the first formal use of the EM algorithm to combine stochastic, jump, and local volatility models in option pricing. After presenting this novel method, machine learning models, specifically LSTM networks, are applied according to the proposed framework for enhancing option pricing models. Finally, the third chapter investigates the use of LSTM models for forecasting Value at Risk (VaR). This chapter highlights the effectiveness of the proposed methodology in estimating financial VaR. Together, these chapters contribute to the growing literature on financial forecasting and risk modeling, demonstrating the versatility of both traditional and machine learning-based methods.
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.
Market sentiment and its impact on the earnings yield- dividend payout relationship: Evidence from emerging markets
In this study, we examine the effect of market sentiment on the relationship between dividend payout ratio and earnings yield using software companies operating in developing countries. Emerging markets have high volatility and different risk dynamics compared to developed markets. The study aims to understand how market sentiment impacts the dynamics between dividend payouts and earnings yields as well as other financial metrics controlling for firm return and risk metrics. We employ a panel data set consisting of 49 cross-sections between 2013 and 2022 and covering companies from BRICS countries, Brazil, China, India and South Africa, that have common stocks traded on major stock exchanges. Our data includes dividend-paying public companies in the software sector. Our results document that there is a negative relation between dividend payout ratio and future earnings yield and market sentiment decreases the strength of this negative relationship. According to our analyses the impact of market sentiment on the relationship between dividend yield and future asset growth is only marginal for the software companies in BRICS countries during our sample period. Our analyses also indicate that the presence of Covid- 19 crisis have no significant effect our results.
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.
Does market perception influence the relationship between dividends&earnings yield? Evidence from developed economies
In this study, we examine whether market sentiment alters the relationship between dividend payout and earnings yield in software and computer services firms across G7 economies during the 2013–2022 period. Our approach combines classical dividend theories with recent insights from behavioral finance, and applies a panel regression framework using the OECD Composite Leading Indicator (CLI) as a measure of market perception. We test whether sentiment strengthens or weakens the link between dividends and forward earnings yield, and whether this potential interaction changes when firms' growth characteristics are taken into account. Our findings show that the dividend payout ratio does not provide significant explanatory power for forward earnings yield, while sentiment maintains a consistently positive association with valuation indicators. Although the sentiment–dividend interaction remains insignificant for earnings yield, it becomes statistically relevant when growth-oriented valuation measures are used as dependent variables. This result suggests that dividends matter more through their contribution to perceived growth prospects than through direct earnings-based valuation channels in sentiment-driven market conditions. By focusing on a single technology-intensive industry in developed markets, we contribute to the literature by explaining why the importance of dividends may vary across sectors, time periods, and sentiment measures. The study also provides evidence on how investor perception influences payout interpretation and highlights the role of market sentiment in shaping valuation dynamics in technologically dynamic firms. Keywords: Dividend policy, earnings yield, investor sentiment, behavioral finance, OECD CLI, market perception, G7 software companies.
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
Automotive industry: Economic effects of foreign direct investment in Turkey
ABSTRACT Foreign Direct Investment (FDI) and automobile industry have inseparable relationship. The academic studies reveal that FDI generally has positive effect on employment, human recourses, management training, GDP, productivity, exports and spillover effects on local industry. In this research, the economic effects of Foreign Direct Investments (FDI) on the Turkish Automotive Industry in terms of export, productivity and employment, the topic of concentration in the Turkish automobile industry between 1997 and 2010 and in the world highest 15 automobile producers between 1998 and 2012 have been analyzed. The results show significant FDI contribution to the Turkish automotive industry in all three areas considered. The results found out that foreign direct investment has significant positive effects on Turkish economy. Policy makers should encourage such investments to stimulate the domestic markets. Keywords: Foreign direct investment, automotive industry, motor vehicle, exports, productivity, employment, labor costs, panel data, fixed effects models, random effects models, concentration.
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.
Essays on the price behaviours of energy commodities (Chaos, fractality, wavelet and non-linearity)
This dissertation investigates the pricing behaviors of major energy commodities; crude oil (wti), gasoline, heating oil and natural gas in different aspects. In this context, the initial focus is on testing nonlinear, long memory, chaotic and fractal behaviors of those energy commodities, and examining whether wavelet studies contribute to modeling and forecasting in a positive way. On the other hand, since it is found that there exist no chaotic and fractal behavior, FIAPARCH and Levy process are evaluated under stochastic modelling additionally.
Two essays on market liquidity
This dissertation consists of two parts and focuses on the equity based market liquidity in Borsa Istanbul, as an order driven electronic market. In the first part, we empirically analyze the agent based relationship between liquidity flow and downside price formation based on the trading network topologies. We apply PageRank Algorithm to extract daily centrality degree in liquidity demand of domestic financial institutions classified as informed traders and use intraday maximum drawdown to capture intraday liquidity shocks. We find evidence that 1) Maximum cumulative loss for a given day, deepens with the increasing liquidity demand of informed traders. 2) The uncertainty in the centrality degree of informed trading on the sell side of the transaction book is overtime positively related with the uncertainty regarding the highest level of intraday loss. 3) Time Patterns are significant: Drawdown depth is highest on Thursdays and lowest on Mondays. Highest (lowest) drawdowns on May (March) indicate the existence of Sell-in-May effect (earnings announcement effect). In the second part, we focus on the market liquidity risk, which is often ignored in conventional Value at Risk (VaR) Metrics. We propose two alternative parametric methods to the existing literature on Liquidity Adjusted Value at Risk. The first model is based on the uncertainty in depth whereas the second model includes the tightness dimension to the latter. Our validation results indicate that both parametric approaches are strong alternatives to existing tightness based models and strictly superior to conventional VaR, with respect to performance related to regulatory compliance, statistical coverage, predictive quantile loss and overall relative cost of liquidity vs. loss.
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 economic growth : Financial innovation, human capital and foreign direct investment
The most recent global financial crisis has fueled arguments against financial innovation on the premise that it was especially the financially engineered complex products that triggered or paved the way to the crisis, which had detrimental effects on macroeconomic growth. Thus, there is considerable motivation to study and empirically test financial innovation and GDP growth relationship. In chapter 1, focus is to examine financial innovation and GDP growth relationships within an endogenous growth model. I explicitly aim to derive balanced growth path equilibrium and stability conditions for the endogenous growth model. Genuine proxy variable for financial innovation is defined. Also an iterative estimation technique panel non-linear least squares method with Gauss Newton algorithm is used to determine relation between per capita growth and financial innovation via simulation. In chapter 2 and 3, we aim to test whether the non-linear endogenous growth model explains relationship between per worker growth and other important growth determinants namely Human Capital and Foreign Direct Investment and also compare and contrast Financial Innovation empirical results with them.
Three essays on investment and cash flow; Financial constraint, financial development and uncertainty
In this thesis, the relationship between investment and cash flow is examined under three headings. In the first part of the thesis, it was tried to understand how the sensi-tivity of companies' investment expenditures to cash flows is affected by the financial limitations and export rates. In the second part, it is tried to be understood how the development of capital and money markets affected the sensitivity of investments to cash flows. In the third chapter, it was tried to determine how the uncertainties in global and local sense affect both the investment expenditures and the dependence of investments on cash flows. Data of the investigation is composed of the data of com-panies that are traded on the BIST (Istanbul Stock Exchange) between the years 1996 and 2014. As the data are in the panel data type, analyses were performed by applying dynamic GMM (Generalised Method of Moments) analysis. As a result, it has been found that as the degree of financial constraints of companies and the level of global and local uncertainty increase, dependence of investment expenditures on cash flows strengthen and the level of investments decline. In the second part we were expecting a decline in the dependence of investments on cash flows as capital and money mar-kets evolve, however according to the analysis results we could not surely confirm our expectation. That is to say it is understood that more data is needed to validate or fal-sify the hypothesis of the second part.
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.
Mekansal ekonomi üzerine ampirik makaleler
Intra-industry trade (IIT) approach is widely believed to entail low transitional adjustment costs in relative production factors. First chapter of thesis examines labor adjustment costs of EU industries with trade relation of NAFTA on industry-level via the perspective of IIT over 36 months period. Results have shown that high economic performance and dominant free trade approach impact trade blocks positively but a financial turmoil cripples IIT by lowering bilateral trade amounts. Second chapter aims to capture marginal IIT levels of trade of industry sectors in 25 developing countries with 34 developed countries and compare its adjustment costs pattern. Evaluating MIIT patterns in diversifying adjustment costs is main approach for examining the correlation between trade liberalization and adjustment costs. Dual index application with newly introduced graphical resolution, Trade Concentration Space (TCS) are crucial for robust results of developing countries by identifying industries as contracting, neutral and expanding via trade liberalization process. Third chapter focuses on the geographical region determinants as a weight matrix. The main motive is here to move beyond singular two-fold relations and aim to confine the effect of IIT on job turnover while monitoring the rest of relevant variables by using newly introduced weight matrix. A spatial two-stage least squares model (S2SLS) is applied for measuring MIIT relation between regional trade pattern and labor market adjustment costs. In first stage, Euclidean distance spatial model is applied to calculate regional weights in EU-28 and in second stage the distinctive impact of variables have shown in empirical results.
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.
Development of new forecasting strategies using wavelet transform (wt), multiple wavelet coherence (mwc) and multi-fractal de-trended fluctuation analysis (mfdfa)
Modeling and forecasting has increasingly become very important in analysis of trends in financial markets, particularly in high frequency trades. It is difficult to predict the price return, i.e. profit or loss, due to many unknown variables including social and political unrest, catastrophic events, etc. Hence these time series have different characteristics of movement, so called fluctuations. Wavelet analysis, multiple wavelet coherence analysis and especially scale by scale wavelet transform are powerful tools to investigate the series possessing different frequency levels. Multi fractal de-trended fluctuation analysis also reveals the different frequency levels of characteristics. It is realized that there is no generalized forecasting strategy available using these methods together. Therefore, a new strategy will be proposed through application on real life data sets to detect highly correlated time series and forecast using vector autoregressive moving average and vector autoregressive fractionally integrated moving average methods in order to compare with real data and quantify the efficiency of forecasting. The thesis is composed of four independent sections. The first section covers a forecasting method using three dimensional multiple wavelet coherence and scale by scale wavelet transformation of precious metals. The second section covers the similar method with western and eastern markets but employs a four dimensional multiple wavelet coherence. The third section covers three dimensional multiple wavelet coherence and its multifractal de-trended fluctuation analysis at the specific scale. The third section utilizes two dimensional wavelet coherence and multifractal de-trended fluctuation analysis of the raw data for a specific determined scale.
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.
Health spending and economic growth
In this study, the effects of health spending on economic growth in OECD countries were investigated between 1998 and 2017. In the scope of the study, a panel data was created by using output-side real GDP as dependent variable, gross capital formation, government consumption, health spending and human capital index as independent variables. In order to achieve economic growth, the spending of health takes an important place and the amount can differ from one country to another base on the development level of the country. When there is a good progress in economy of a country, the progress can be also seen in the fields of health and education as well. People, who are at a certain level economically and in terms of health, within a society, are one of the vital inputs for economic development. Therefore, this study which focuses on understanding the place of health spending in economic development is quite important. All actions, which affect people within a community in physical, psychological and social terms, are included in health care. In order to keep economic progress positively, the length of life-time should get longer and mortality should decrease. Manpower is an important factor that brings economic achievement to today's societies and therefore requires economic investment. So, the spending on health are kind of investment to succeed productivity in manpower and it cannot be considered as a burden to economy because of the fact that spending will turn into investments. Key words: Health Spending, Economic Growth
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.
Essays on the return, volatility and correlation features of emerging market bonds and related models
In this thesis, Emerging Market Local Bonds are examined from the portfolio risk perspective and certain methodologies on which the literature is limited are dealt with. MFDFA (Multifractal Detrended Fluctuation Analysis) and MFDXA (Multifractal Detrended Cross-Correlation Analysis) methods are applied to all portfolio components; the return, volatility and cross-correlation data of short-term and long-term bonds of Brazil, Indonesia, India, South Africa, Mexico, Turkey. The findings of this study have significant implications for the asset management industry as it paves the way for the improvement of forecast and risk measurement techniques by considering fractal-based models. In the second part, we focus on Turkish local fixed income as-sets by stylizing tools for the risk analysis. To investigate and model, volatility clustering, asymmetry-leverage impacts, and especially the volatility persistence several fractional models: FIGARCH, HYGARCH, FIEGARCH, and FIAPARCH are ap-plied. It is revealed that, under two different market conditions, in-sample analysis and the forecasting performances of fractional models deliver superior outcomes. In the third part of the thesis, Emerging Market Bond portfolios are evaluated with the fractional models. For different versions of Emerging Market Bond portfolios, Dynamic Conditional Correlation (DCC) GARCH and FIGARCH models are applied. Performances are demonstrated with Value at Risk (VaR) analysis. Portfolio analysis covers dynamic portfolios that consider portfolio optimizations. This thesis as a whole, provide specific takeaways by suggesting the applications of multifractal analysis and fractional models to Emerging Market Bond portfolios.
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.
A novel approach for optimal portfolio allocation: Feasible market factor estimation
This study gives the answer to the factor selection problem existing within the factor based covariance estimation framework. First, we illustrate the fact that the sample covariance estimation of the large scaled covariance matrices deteriorates the performance of the optimal asset allocation compared to naive diversification. Employing factors instead of assets into covariance estimation plays heroic role to lower estimation error and keep optimal asset allocation strategies alive for both asset management industry and the academic universe. However, choosing the optimal number of factors to reduce the estimation error to the rock bottom while not losing required information to estimate covariance profile of the asset universe, is still either sample size or time period dependent. To eliminate factor selection problem, we proposes a novel factor-based covariance estimation method, "Feasible Market Factor (FMF)" estimation, which generates a single artificial factor representing the sum of the individual variances of the observed factor universe. Under various constraint setting we compare the performance of the proposed approach to PCA, single and multi-factor and sample covariance estimation methods in terms of portfolio's performance ratios. Empirical results illustrate that FMF outperforms other factor based and sample covariance estimation methods in terms of Sharpe and Sortino ratios especially for the portfolios minimizing either variance or semi-variance. To also improve performance of the optimal portfolios maximizing return with given volatility, we implement the Autoregressive Markov Regime Switching model within FMF framework and enhance the performance of Maximum Sharpe Ratio (MSR) portfolio compared to CAPM.
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.
A reinvestigation of the hysteresis hypothesis in the OECD countries
This study re-investigates the hysteresis hypothesis in unemployment for 24 OECD countries. The results obtained in the literature are quite mixed for the OECD countries, with the findings highly sensitive to the econometric methodology applied and data used. Therefore, to shed some light on this debate in addition to the conventional unit root tests, a variety of other tests that allow for asymmetric adjustment, structural breaks or both simultaneously are also considered. Our results show that the hysteresis effect in unemployment was confirmed for most of the countries studied according to all tests applied. Thus, the labor markets of the OECD countries calls for urgent reform, especially if they want their jobless rates to return to their pre 2008-2009 global financial crisis levels. Keywords: Hysteresis in unemployment, Nonlinear unit root test, Unit root test with structural break, Unit root test with both structural break and asymmetric nonlinearity.
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.