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Modeling of wind speed using differential evolution: Istanbul case
(Yildiz Technical University, 2024) Koçak, Emre; Özsoy, Volkan Soner; Örkcü, H. Hasan
Over the years, increasing energy demands with the growth of the population and the development of technology have caused more fossil fuel consumption. Besides, environmental pollution and climate change, which are vital importance for humanity, are encountered. In order to avoid these dangerous situations, people have started to turn to clean and renewable energy sources such as wind energy. Due to the rapid development of such situations, it is very important to obtain information on the determination of the regions where wind energy facility will be installed and the characteristics of the wind speed. Wind power estimation can be made through various statistical distributions used to explain the characteristics of wind speed data. Rayleigh, Weibull, Nakagami, Gamma, Logistic, Loglogistic, Lognormal and Burr Type XII distributions, which are frequently used in the wind energy literature, are discussed in this study and the performances of the specified distributions are compared through the data sets obtained from the stations in Istanbul from Marmara region. One of the most preferred methods in estimation problems is the maximum likelihood method, and a differential evolution algorithm is proposed for ML estimation of the parameters of the distributions examined in the study.
Vulnerability of Stock Markets to Earthquakes / The 7.7 and 7.6 Scale Earthquakes in Turkey in 2023: Sectors of Non-Metallic Mineral Products, Basic Metals and Construction & Infrastructure
(Ahmet Arif EREN, 2023) Hamurcu, Çağrı
This study aims to reveal whether stock markets are vulnerable to the effects of earthquakes and how they are affected by earthquakes. The 7.7 and 7.6 magnitude earthquakes in Turkey in February 2023 were explored. The impact of the earthquake on Borsa Istanbul was analyzed with the event study method, specific to non-metallic mineral products, basic metals, and construction & infrastructure sectors. Firstly, the paired-samples T-Test and the Wilcoxon Signed Ranks Test were used to evaluate whether there was a difference that was statistically significant in the cumulative abnormal returns (CARs) of the sector-specific indexes in the 5, 10, 15, 20, 25, 30, 35, 40, 45 and 50 hour time periods prior to and following the earthquake first occurred. The first results indicate that for all evaluated time intervals, the first occurred earthquake had positive effects on the CARs of the non-metallic mineral products and base metals sector indices and negative effects on the construction & infrastructure sector indices. Secondly, the effects of both the first and second earthquakes were analyzed with the Seemingly Unrelated Regressions (SUR) Model. According to the SUR Model analysis, the direction of the effects of the first earthquake is consistent with the first findings. In this model, the direction of the effects of the second earthquake is also compatible with the direction of the effects of the first earthquake, but the size and trend of the consequences of these earthquakes change over time. The findings are expected to contribute to the literature by shedding light on how sectors can respond to catastrophes like earthquakes occurrences at the micro level.
Relationship between the green finance index, CO2 emission, and GDP
(Walter de Gruyter (Verlag), 2023) Hamurcu, Çağrı
Green technology innovation and effective use of green financing tools are very important in order to ensure sustainable economic and environmental development without environmental degradation, and to decarbonize all sectors. Evaluating the green investment process together with the inputs, outputs and the factors involved in the process will make important contributions in terms of determining the current situation, developing new and effective policies and raising awareness on green finance. For all these reasons, it is aimed to reveal the interaction mechanisms between GFI, CO2 emissions and GDP in this study. GFI, CO2 emissions, and GDP variables covering 26 countries between 2018-2021 were analyzed using panel data analysis with a fixed effects model. Firstly, it is found that CO2 emission had a negative effect on GFI, but GDP had a positive effect on GFI, and the effect of CO2 was greater than GDP. Secondly, GFI was found to have negative effects on CO2 emissions whereas GDP had positive effects, with GFI benefiting slightly more than GDP from these effects. Thirdly, GDP was shown to be positively affected by both GFI and CO2, and the analyses revealed that the effect of CO2 was much greater than that of GFI. The findings are considered important in terms of making predictions in terms of understanding and developing green finance and its effects.
Bank failure risk: A study on Silicon Valley Bank, Signature Bank, and Silvergate Capital Corporations
(Walter de Gruyter (Verlag), 2023) Hamurcu, Çağrı
This study investigates whether the ratio of long-term investment to total assets, the ratio of cash on hand to total assets, and the ratio of price-to-earnings are risk indicators for bank failures. Silicon Valley Bank (SVB), Signature Bank, and Silvergate Capital Corp., which experienced bank failure, and banks that are among the 20 largest banks in the USA are analyzed with the panel data method. Analyses were made using quarterly data between 2003Q4 and 2022Q4. It is revealed that the long-term investment to total assets ratio increases the bank failure risk. The risk of bank failure varies negatively with the cash on hand to total assets ratio. Bank failure risk rises as the price-to-earnings ratio rises. In terms of revealing the factors influencing the risk of bank failure and possible consequences, it is expected that the findings obtained could contribute to the literature.
Financial risk-taking in adult attention deficit hyperactivity disorder
(Emerald Publishing, 2024) Hamurcu, Çağrı; Yalvaç Hamurcu, Hayriye Dilek; Karakuş, Merve
This study aimed to examine the financial risk-taking behaviors of adult individuals diagnosed with attention deficit hyperactivity disorder (ADHD). Design/methodology/approach: The study was conducted with adults (n = 80) diagnosed with ADHD and healthy controls (n = 80). In order to measure risk-taking in the financial domain, the items in the investment and gambling sub-dimensions of the Domain-Specific Risk-Taking Scale (DOSPERT) were applied. Findings: Adults with ADHD had higher investment and gambling risk-taking and expected benefits scores than the control group, and there was no difference between the two groups in terms of risk perceptions. In the regression analysis, there was a positive linear relationship between the investment and gambling risk-taking scores and the expected benefits scores in both groups. There was a negative linear relationship between investment risk-taking and risk perceptions scores only in the control group. Originality/value: In terms of investment and gambling, both risk-taking and expected benefits are greater in individuals with ADHD. It has been observed that while healthy individuals take investment risks, they evaluate according to the expected benefits and risk perceptions, while individuals with ADHD make evaluations only according to the expected benefits, risk perceptions do not predict financial risk-taking in individuals with ADHD. When it comes to risk-taking related to gambling, both groups take risks only according to their expectations of benefits, not their perceptions of risk. The study provides outputs that can contribute to the literature in terms of the effects of ADHD diagnosis on financial decision-making processes in the context of risk-taking.
Model selection in multivariate adaptive regressions splines (MARS) using alternative information criteria
(Elsevier Ltd, 2023) Bekar Adıgüzel, Meryem; Cengiz, Mehmet Ali
Multivariate Adaptive Regression Splines (MARS) is a useful non-parametric regression analysis method that can be used for model selection in high-dimensional data. Since MARS can identify and model complex, non-linear relationships between the dependent variable and independent variables without requiring any assumptions, it has advantage over simple linear regression techniques. Also, for simplifying the model building process and preventing overfitting, MARS can select automatically the variables to be included in the model, which is useful for datasets with many variables. While MARS is a flexible non-parametric regression method, generalized cross validation (GCV) technique is used within the MARS framework to avoid overfitting and to select the best model. GCV criterion is widely used and can be effective in many situations, however it has some criticism. These criticism are the arbitrary value of the smoothing parameter used in the algorithm of the GCV criterion and the models obtained using this criterion are high-dimensional. In this paper, it is aimed to obtain the barest model that best explains the relationship between the dependent variable and independent variables by using alternative information criteria (Akaike information criterion (AIC), Schwarz Bayesian criterion (SBC) and information complexity criterion (ICOMP(IFIM)PEU)) instead of the use of smoothing parameters in order to put an end to the criticism. To achieve this goal, a simulation study was first conducted with a data set composed of variables that do and do not contribute to the dependent variable to test the success of the information criteria. As a consequence of this simulation work, when variables (which do not contribute to the dependent variable) are not included in the regression model, it demonstrates the success of the criteria in model selection. As a real data set, the reasons for loan defaults were investigated between the years 2005–2019 by utilizing data from 18 banks operating in Türkiye. The results obtained reveal the success of ICOMP(IFIM)PEU criterion in model selection.
Can Elon Mask's Twitter Posts About Cryptocurrencies Influence Cryptocurrency Markets by Creating a Herding Behavior Bias
(Ahmet Arif Eren, 2022) Hamurcu, Çağrı
The main purpose of this study is to examine the effects of Elon Mask's Twitter posts about cryptocurrencies on cryptocurrency markets within the scope of herding behavior bias. For this purpose, the daily price values and transaction volumes of Bitcoin and Dogecoin are analyzed by applying the EGARCH models. The results show that Elon Musk's positive Twitter posts increase dogecoin's volatility more than bitcoin in terms of price and trading volume. In addition, the effect of positive tweets has been found to increase Bitcoin and Dogecoin prices and their market transactions. According to the results, while negative tweet sharing negatively affects bitcoin returns, it manifests itself with an increase in volatility after a certain period of time. Another result is that the Dogecoin return and negative tweet interaction vary according to time intervals, but the presence of the effect on volatility cannot be determined. It is also concluded that after the negative tweet, both bitcoin and dogecoin transaction volumes increased in the first days, but their volatility was not affected. The results are important in terms of showing the effects of an influential person's social media posts on the financial markets by creating a herd behavior effect. Revealing the "influential person effect" as a behavioral finance bias is seen as the originality of the study. It is thought that the findings can be evaluated in terms of pointing out a factor that may pose a potential risk to financial stability in the global sense.
On a three dimensional higher order system of difference equations
(Watam Press, 2022) Akrour, Youssouf; Kara, Merve; Touafek, Nouressadat; Yazlık, Yasin
In this work, we derive the solutions form of the following three-dimensional system of nonlinear difference equations of higher-order (Formula presented). where the parameters ?, ?, a, b, A, B and the initial values x?i, y?i, z?i, i ? {0, 1, …, k} are non-zero real numbers. provided in details. The behavior of the solutions of our system with p = 1 is.
Depremlerin sigortacılık sektörü hisse senetleri üzerinde etkisi olabilir mi? 2020 yılındaki İzmir depremi üzerine bir araştırma
(Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Fakültesi, 2022) Hamurcu, Çağrı
Bu çalışmada, depremlerin sigortacılık sektöründe faaliyet gösteren firmaların hisse senetleri üzerindeki etkisinin incelenmesi amaçlanmıştır. Bu amaçla, İzmir şehrinde şiddetli yıkıcı etkiler yaratan 30 Ekim 2020 tarihinde meydana gelen deprem, bu çalışmada ele alınmıştır. BIST TUM endeksi içerisinde bulunan sigortacılık sektörü hisse senetlerinin bu deprem felaketine verdiği tepkiler olay çalışması yöntemi ile analiz edilmiştir. Analizde, hisse senetlerinin deprem tarihi öncesindeki ve sonrasındaki 15, 30, 45, 60 ve 75 günlük zaman dilimlerindeki kümülatif anormal getirilerinde (cumulative abnormal return-CAR) farklılaşma olup olmadığı bağımlı örneklem t testi (paired samples t test) ile analiz edilmiştir. Sonuçlara göre depremin, sigortacılık sektörü hisse senetlerine ait kümülatif getirilerde 15, 30, 45 ve 60 günlük dönemler için negatif yönde etkiler yarattığı tespit edilmiştir. Riskten kaçınma, kayıptan kaçınma ve belirsizlikten kaçınma davranışsal finans eğilimlerinin, yatırımcılar üzerinde yaratmış olabileceği birtakım etkilerin, hisse senetlerinin getirilerinde meydana gelen düşüşlerin nedenleri arasında olabileceği akıllara gelmektedir. Çalışma sonuçlarının, özellikle felaket dönemlerinde sigortacılık sektörü hisse senetlerinin bu olaylara nasıl tepkiler verebileceğinin ortaya konulabilmesi açısından literature katkı sağlayabileceği düşünülmektedir.
Impact of COVID-19 first official vaccine approval on precious metals: a behavioral finance approach
(Alanya Alaaddin Keykubat Üniversitesi İktisadi, İdari ve Sosyal Bilimler Fakültesi, 2022) Hamurcu, Çağrı
This research aims to reveal the effect of first official COVID-19 vaccine approval on precious metal prices in terms of return and volatility. Within the context of precious metal, gold, silver, platinum, and palladium are selected as dependent and US dollar index as independent variables. In order to measure the difference in the returns and volatilities before and after the first official approval of the COVID-19 vaccine, a dummy variable is defined. Analysis studies have been carried out with EGARCH models. According to the results, it is determined that the first official COVID-19 vaccine approval had negatively affected the level of volatility for gold and silver prices. The approval does not affect the volatility of platinum and palladium. Besides, a negative relationship is found between both all precious metals and the US dollar index in terms of returns. It is assumed that the results could be interpreted as investors acted by the risk aversion bias before the first official approval of the COVID-19 vaccine, and the approval created an effect of reducing uncertainty in the financial markets.
Aile şirketlerinin finansal karar verme süreçleri: planlı davranış teorisi çerçevesinde bir araştırma
(2022) Duman, Haluk; Yücenurşen, Mehmet
Bu çalışmanın amacı, Planlı Davranış Teorisi çerçevesinde aile şirketlerinin finansal karar verme süreçlerini etkileyen faktörleri incelemektir. Araştırmada, Aksaray OSB’de faaliyet gösteren aile şirketleri anakütle olarak tespit edilmiş ve 160 adet aile şirketi sahibi/yöneticisine bir anket uygulanmıştır. Toplanan verilere; tanımlayıcı istatistikler ile açımlayıcı faktör analizi, keşfedici faktör analizi ve yol analizleri uygulanmıştır. Elde edilen bulgular, aile normları ve tutumun davranışsal niyet üzerinde etkili olduğunu göstermiştir.
A window dea based efficiency evaluation of the public airports in Turkey: 2014-2019 case
(Academy Economic Studies, 2022) Özsoy, Volkan Soner; Pehlivanlı, Edib Ali
Aviation is strategically important because of its enormous contribution to the economy, as well as being the field of application and production of new technologies. The efficiency of airports comes to the fore in efficiency researches in aviation. However, efficiency analyzes with Data Envelopment Analysis (DEA) using single-year data may not be sufficient to determine the trend. Therefore, output-oriented Window-DEA (W-DEA) using multi periods was performed in this study. Moreover, W-DEA provides information about the increases and decreases in the efficiency trends of airports. The research was carried out with the data of 42 Turkish airports for the period 2014-2019. The findings show that two airports in Istanbul as well as Adana, Van and Antalya airports have high efficiency. With this study, measuring the performance of Turkish airports with W-DEA has been brought to the literature. This study will shed light on the feasibility studies of new investments as well as the sustainability and competitiveness studies.
Hierarchical groups DEA cross-efficiency and TOPSIS technique: An application on mobile money agents locations
(Inderscience Publishers, 2022) Muvingi, Jacob; Peer, Arshad Ahmud Iqbal; Lotfi, Farhad Hosseinzadeh; Özsoy, Volkan Soner
Ranking of efficient decision-making units (DMUs) allows a further analysis of the data envelopment analysis (DEA) efficient DMUs, where otherwise a high number of efficient DMUs can be identified. The current research seeks to segregate the efficient DMUs through the use of seven cross-efficiency (CE) ranking approaches. The choice of using those CE approaches was meant to reduce bias associated with the use of a single criterion. The seven approaches were extended to suit a situation were DMUs are structured in a two-level hierarchical grouping. The CE of level 1 DMUs was adjusted with the performance of the level 2 DMUs. Variations in the seven adjusted CE ratings were observed. In a bid to ensure complete ranking, the technique for order preference by similarity to ideal solution (TOPSIS) ranking method was combined with the adjusted CE ratings.
Muhasebe meslek mensuplarının büyük veri analitiği teknolojisi direncine yönelik bir araştırma
(IJMEB, 2021) Yücenurşen, Mehmet
Bu çalışmanın amacı, Statüko Yanlılığı (Status Quo Bias) Teorisi çerçevesinde muhasebe meslek mensuplarının yeni veri analitiği teknolojisi direncine neden olan faktörleri incelemektir. Araştırmada, Aksaray ilinde aktif olarak çalışan Serbest Muhasebeci Mali Müşavirler (SMMM) anakütle olarak tespit edilmiş ve 100 adet SMMM’ye bir anket uygulanmıştır. Toplanan verilere; tanımlayıcı istatistikler ile açımlayıcı faktör analizi, keşfedici faktör analizi ve yol analizleri uygulanmıştır. Elde edilen bulgular; algılanan değer, değişim maliyeti ve meslektaş görüşlerinin değişime direnç üzerinde etkili olduğunu göstermektedir.
Performance management of OECD countries on Covid-19 pandemic: a criticism using data envelopment analysis models
(Emerald Group Holdings Ltd., 2021) Doğan, Mustafa İsa; Özsoy, Volkan Soner; Örkçü, H. Hasan
The Covid-19 pandemic spread rapidly around the world and required strict restriction plans and policies. In most countries around the world, the outbreak of the disease has been serious and has greatly affected the health system and the economy. The factors such as the number of patients with chronic diseases, the number of people over 65 years old, hospital facilities, the number of confirmed Covid-19 cases, the recovering Covid-19 cases and the number of deaths affect the rate of spread of Covid-19. This study aims to evaluate the performances of 21 Organisation for Economic Co-operation and Development (OECD) countries against the Covid-19 outbreak using three data envelopment analysis (DEA) models. Design/methodology/approach: In this study, the performance of 21 OECD countries to manage the Covid-19 process has been analysed weekly via DEA which is widely used in various practical problems and provides a general framework for efficiency evaluation problems using the inputs and outputs of decision-making units. Findings: The analysis showed that 11 countries out of 21 countries were efficient for selected weeks. According to the DEA results from the 20-week review (09 April 2020–20 August 2020), information about the course of the epidemic prevention and the normalization process for any country can be obtained. Originality/value: In this study, due to the problem of the discrimination power of DEA, the cross-efficiency model and the super-efficiency model also used. In addition, the output-oriented model was preferred in this study for Covid-19 management efficiency
How consumer confidence index affects foreign investors' portfolio and equity security investments: a research on Turkey
(Celal Bayar Üniversitesi, 2021) Hamurcu, Çağrı
In this study, it has been investigated whether the consumer confidence index, which is an indicator of investor sensitivity, has an effect on the portfolio and equity security investments of foreign investors. Analyses are made using the consumer confidence index and the quarterly data of foreigners' portfolio and equity security investments in Turkey between 2012 and 2020. Dual VAR models are created and Granger causality analyses are performed. The results show there is Granger causality from the consumer confidence index to the portfolio investments made by foreign residents. This causality is also determined in the direction to equity security investments. Regression analyses indicate that the causality relationships have a positive sign. It is concluded that an increase in the consumer confidence index may lead to an increase in the domestic portfolio and equity security investments of foreign residents or, on the contrary, it will decrease. These results could be interpreted as the consumer confidence index might be used as a measure of investor sentiment in estimating the amount of portfolio and equity security investments of foreign investors.
A novel approach for determining common weights in two division network DEA: a case study of Science and technology parks in Turkey
(Routledge, 2022) Özsoy, Volkan Soner; Belgin, Önder; Balkan, Dursun
Data Envelopment Analysis is a popular tool for assessing the relative efficiency of units, treated as a whole unit, without considering the internal structure of decision-making units. In contrast to the conventional models, Network DEA models consider the internal operations of units. In both models, the most favourable weights of the input-output factors for each unit are used. One of the main pitfalls of these models is that they require a set of n different vectors of these weights for the units, thus the factors may not have the same importance for each unit. To overcome this drawback and avoid ignoring some factors, several methods have been proposed to determine a common set of weights (CSWs) of the factors. However, none of the proposed approaches can determine the CSWs in network DEA models. This paper contributes to the existing literature by proposing a novel approach for determining the CSWs based on Entropy Method. Finally, the proposed approach is applied to demonstrate their applicability in both numerical and illustration examples. Moreover, a case of assessment of Science and Technology Parks in Turkey was used for the purpose of illustration.
Gray’in muhasebe değerleri üzerine ampirik bir değerlendirme
(2021) Yücenurşen, Mehmet; Karakuş, Mustafa
Bu çalışmada, Gray’in teorik olarak ileri sürdüğü muhasebe değerleri olan profesyonellik, tekdüzelik, tutuculuk ve gizliliğe yönelik ampirik bir değerlendirme gerçekleştirmek amaçlanmıştır. Araştırmanın, Türkçe literatürde Hofstede-Gray modeline yönelik ampirik bir değerlendirme olmaması nedeniyle ilgili yazına katkı sağlayacağı düşünülmektedir. Yöntem – Çalışmada Aksaray ilinde faaliyet gösteren Serbest Muhasebeci Mali Müşavirler (SMMM) anakütle olarak belirlenmiş ve 108 muhasebe meslek mensubuna bir anket uygulaması gerçekleştirilmiştir. Elde edilen verilerin analizinde, tanımlayıcı istatistikler ile açımlayıcı faktör analizi ve keşfedici faktör analizi gerçekleştirilmiştir. Bulgular – Elde edilen bulgular, Gray’in muhasebe değerleri modelinin kısmen desteklendiğini göstermektedir ancak tutuculuk değeri ‘açıklama açısından tutuculuk’ ve ‘değerleme/ölçüm açısından tutuculuk’ olarak iki ayrı faktöre yüklenmiştir. Tartışma – Araştırmada kullanılan ölçeğin açıklanan toplam varyans değeri %64,582 olduğundan dolayı henüz tanımlanmamış başka muhasebe değerlerinden söz edilebilir. Bu bağlamda, teorik temel yerine deneysel olarak hazırlanan veri toplama tekniği ile tanımlanmamış diğer muhasebe değerlerini tanımlamak mümkün olabilecektir.
The determination of the most suitable inertia weight strategy for particle swarm optimization via the minimax mixed-integer linear programming model
(Emerald Publishing, 2021) Özsoy, Volkan Soner
Purpose This paper aims to consider each strategy of the particle swarm optimization (PSO) as a unit in data envelopment analysis (DEA) and uses the minimax mixed-integer linear programming DEA approach to find the most suitable inertia weight strategy. A total of 15 inertia weight strategies were empirically examined in a suite of 42 benchmark problems in the view of DEA. Design/methodology/approach PSO is very sensitive to inertia weight strategies, and therefore, an important amount of research attempts has been concentrated on these strategies. There is no research into the determination of the most suitable inertia weight strategy; however, there are a large number of comparisons related to the inertia weight strategies. DEA is one of the performance evaluation methods, and its models classify the set of strategies into two distinct sets as efficient and inefficient. However, only one of the strategies should be used in the PSO algorithm. Some effective models were proposed to find the most efficient strategy. Findings The experimental studies demonstrate that an approach is a useful tool in the determination of the most suitable strategy. Besides, if the author encounters a new complex problem whose properties are known, it will help the author to choose the best strategy. Practical implications A heavy oil thermal cracking three lumps model for the simplification of the reaction system was used because it is an important complicated chemical process. In addition, the soil water retention curve (SWRC) plays an important role in diverse facets of agricultural engineering. As the SWRC can be regarded as a nonlinear function between the water content and the soil water potential, Van Genuchten model is proposed to describe this function. To determinate these model parameters, an optimization problem is formulated, which minimizes the difference between the measured and modeled data. Originality/value In this paper, the PSO algorithm is integrated with minimax mixed-integer linear programming to find the most suitable inertia weight strategy. In this way, the best strategy could be chosen for a new more complex problem.
On the system of difference equations
(Islamic Azad University, 2020) Kara, M.; Yazlık, Y.
In this paper, we show that the system of difference equations x(n) = x(n-2)y(n-3)/y(n-1)(a(n)+b(n)x(n-2)y(n-3)), y(n) = y(n-2)x(n-3)/x(n-1)(alpha(n)+beta(n)y(n-2)x(n-3)), n is an element of N-0, where the sequences for all n is an element of N-0, (a(n)), (b(n)), (alpha(n)), (beta(n)) and the initial values x(-j), y(-j), j is an element of {1, 2, 3} are non-zero real numbers, can be solved in the closed form. For the case when all the sequences (a(n)), (b(n)), (alpha(n)), (beta(n)) are constant we describe the asymptotic behavior and periodicity of solutions of above system is also investigated.

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