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Öğe CORPORATE BANKRUPTCY PREDICTION USING MACHINE LEARNING METHODS: THE CASE OF THE USA(2022) Özparlak, Gerçek; Diliduzgun, Menevse OzdemirMany of the international hospitals and health institutions have faced serious financial difficulties with the Covid-19 epidemic that emerged at the end of 2019. In the coming years, these financial difficulties are expected to cause more bankruptcies. Being able to predict company bankruptcies is important to protect company partners, investors, company creditors and the continuity of the healthcare industry. Thanks to accurate forecasts in this area, company managers can prevent company bankruptcies by taking the necessary precautions and investors can limit their losses. This study aims to build a model that can predict bankruptcies in the health sector by using artificial neural networks (ANN). For the sample of this study, 23 companies in the health sector that declared bankruptcy between 01.01.2018 and 31.12.2020 in the USA, and 23 companies that were in the same period and the same sector but had no financial problems were selected as the control group. 30 financial ratios belonging to these companies were used as input data of the research. In the study, artificial neural networks (ANN) were chosen as the method. According to the results of the research, the correct classification rate of the artificial neural network models created using the training set data was 100%. The correct classification rate of artificial neural network models created using test set data was 90%. According to the results of the research, ANNs are promising for the prediction of company bankruptcies with their high classification success and ease of use. Therefore, it is recommended to be used by both researchers and investors.Öğe Corporate Governance of Banks, The Key for Trust: A Bibliometric Analysis(2024) Gurol, Burcu; Sultanoglu, Banu; Özparlak, GerçekCorporate governance aims to create a transparent, fair, accountable, and responsible management environment for all stakeholders. Due to the significant role of banks in the economy, corporate governance in banks is indispensable for establishing trust, which is crucial for them to survive. Albeit numerous bibliometric analyses have been found solely on banks or corporate governance, there needs to be more bibliometric analysis on the corporate governance of banks. Thus, this study aims to explore the research works of corporate governance, particularly of banks, by conducting a bibliometric analysis from 2003 to 2022. The results show that the interest in corporate governance in banks increased, especially after the 2008 financial crisis, and the studies focused on the board structure-bank performance and board structure-risk appetite relations. Additionally, corporate governance has emerged as an essential topic in Islamic banking since the 2010s.Öğe DOES BOARD GENDER DIVERSITY REDUCE INFORMATION ASYMMETRY? EVIDENCE FROM THE USA(2024) Özparlak, GerçekThe contributions of women managers to the financial, economic and sustainability areas of firms are obvious. However, women managers can also play a key role in reducing asymmetric information. The purpose of this study is to investigate the effect of gender diversity in corporate management on information asymmetry. The study refers to agency theory and critical mass theory. Gender equality, board diversity and control variables are used in the analyses. In the study, an ordinary least squares (OLS) model is used to analyse the relationship of variables. In addition, fixed effect, quantile regression and lag estimation models are used to analyse endogeneity problems. The annual data of 401 American companies listed in the S&P500 index between 2008 and 2023 were used in the sample. The results of the study contribute to the current debate on the benefits of gender diversity in corporate management with different tests and theories. According to the results of the study, increasing the number of women on the board contributes to the reduction of information asymmetry. According to another result of the study, under the critical mass theory, having three or more women in the company management contributes more to the reduction of information asymmetry.Öğe FİNANSAL TABLO MANİPÜLASYONLARININ TESPİTİNDE YAPAY SİNİR AĞLARININ KULLANILMASI(2021) Özparlak, GerçekHalka açık şirketlerin, gerçeğe aykırı bilgileri açıklayarak, finansal bilgi manipülasyonuna başvurmaları şirket ortaklarının ve ülke ekonomisinin zarara uğramasına neden olmaktadır. Bu kapsamda, bu çalışmanın iki amacı bulunmaktadır. Birinci amacı, Covid-19 salgının yarattığı ekonomik kriz ortamında, Borsa İstanbul’da yer alan şirketlerin finansal bilgi manipülasyonuna başvurup vurmadıkları ihtimalinin Beneish modeli ile analiz edilmesidir. İkinci amacı, teknolojinin gelişmesi ile beraber yaygın olarak kullanılmaya başlanılan yapay sinir ağlarının finansal bilgi manipülasyonunu ölçmedeki performansının değerlendirilmesidir. Araştırma sonuçlarına göre, çalışmadaki 264 şirketten %43’ünün (113 adet) çeşitli seviyelerde finansal bilgi manipülasyonu yapmış olabileceği tespit edilmiştir. Altman Z skoruna göre, finansal başarısızlık ihtimali bulunmayan, güvenli bölgedeki 135 şirketin %47’sinin (64 adet) finansal bilgi manipülasyonu yapmış olabileceğine dair olasılık ve bulgular vardır. Buna karşın, Altman Z skoruna göre, finansal başarısızlık ihtimali yüksek olan, tehlikeli bölgedeki 74 şirketten %45’inin (33 adet) çeşitli seviyelerde finansal bilgi manipülasyonuna başvurmuş olabileceği görülmüştür. Araştırmanın diğer sonuçlarına göre, Altman skoru sonuçları üzerine kurgulanan ve yapay sinir ağlarıyla gerçekleştirilen modelin doğru sınıflandırma oranı, eğitim seti verisi için %99,53 seviyesinde ve test seti verisi için %98,11 seviyesindedir. Beneish modelinin sonuçları üzerine kurgulanan ve yapay sinir ağlarıyla gerçekleştirilen modelin doğru sınıflandırma oranı, eğitim seti verisi için %96,21 seviyesinde ve test seti verisi için %86,80 seviyesindedir.Öğe The Impact of Financial Inclusion on Economic Growth and Income Inequality(2021) Özhan, Aslı Ceren; Özparlak, GerçekFinancial inclusion is defined as the access of households and firms tobeneficial and reasonably priced financial products and services which arein line with their necessities. These could be financial transactions, transfers,savings, and loans. After narrowing down the definition, it then measuresfinancial inclusion by using indexation technique. A major contribution ofthis study is the development of a measure of financial inclusion viaformation of three indices, namely financial access index, firm-level andhousehold-level financial usage indices. These three indices capture differentaspects of financial inclusion, which is comprised of access to financialservices by both households and firms in addition to effective use of theseservices. Based on Global Findex database and the Enterprise Surveydatabase collected by the World Bank, Financial Access database collectedby the International Monetary Fund the study introduces measures ofhousehold-level and firm-level inclusion, with placing Europe and CentralAsia in a historical and cross-country perspective. By using Panel andOrdinary Least Squares regression analysis, it analyzes the impact offinancial inclusion on two important macroeconomic variables, namelygrowth and inequality. Moreover, it focuses particularly on the ECA regionand analyzes the dynamics in the region. The study aims at documenting thestatus of financial inclusion in ECA, while shedding light on the impact offinancial inclusion on growth and inequality. It concludes that, in line withthe contemporary literature, financial inclusion enhances growth andreduces inequality with better access to resources to finance bothconsumption and investment. According to the article’s findings, thepositive impact of financial inclusion on growth is significant in the ECAregion.Öğe A New Bankruptcy Forecast Modelling For Energy Companies(Bandırma Onyedi Eylül Üniversitesi, 2022) Özparlak, GerçekDue to the Covid-19 epidemic, there was a significant increase in company bankruptcies in 2020. In this period, especially the energy sector has been one area where bankruptcies are the most seen. In this context, this study aims to build a model that can predict financially unsuccessful companies that have declared bankruptcy and successful companies operating in the energy sector in the U.S.A. For the study sample, 30 financial ratios of 23 energy companies that declared bankruptcy in the U.S.A. in 2020 and 30 financial ratios of 23 energy companies that were financially successful in the same period were selected. The multiple discriminant analysis (M.D.A.) was chosen to differentiate between the groups. According to the research results, the accuracy rate of the created function was found to be 87.0%. According to the sensitivity and specificity (R.O.C.) results, the performance of the model was found to be strong for distinguish differ between bankrupted and non-bankrupted companies.Öğe The Possible Impact Of Twitter Post Messages On Stock Market Activities(Ankara Üniversitesi, 2020) Özparlak, GerçekThe purpose of this research is to contribute to the academic field by demonstrating the relationship between stock related Twitter messages, their frequencies, sentiment analysis; stock return, volume, and volatility of Dow Jones Index and BIST30 & BIST100 Index. In this study, The Multinomial Naive Bayes Text Classifier is used as methodology since it is the most conventional method for text classification based on previous research. Using computational linguistics methods, 138.070 English and 34.632 Turkish tweets have been analyzed on a daily basis for a period of 8 months. The results demonstrated a strong relationship between tweets and their impact on the market. Moreover, according to results, there is a positive correlation between the number of retweets and BIST Volume lag-1 and lag+1. In addition, this article confirms that stock microblogs contain valuable information for investors and it can be an assistance in predicting the future market index.Öğe ÜLKELER?N KRED? TEMERRÜT TAKASI (CDS) PR?MLER?N?N D?NAM?K NEDENSELL?K ?L??K?S? ?LE ?NCELENMES?(2021) Özparlak, Gerçek; Yeşilyurt, SerkanBu çalı?mada, Türkiye?nin kredi temerrüt takası (CDS) primleri ile BRICS ülkelerinin (Brezilya, Rusya, Hindistan, Çin, Güney Afrika) ve Avrupa Birliği?nin lider ekonomilerinin (Almanya, Fransa, ?ngiltere, ?talya, ?spanya) kredi temerrüt takası primleri arasındaki dinamik nedensellik ili?kisi, iki a?amalı çapraz korelasyon fonksiyonu (CCF) yöntemi ile incelenmi?tir. ?lk a?amada, ülke CDS?leri EGARCH modelleri ile tahmin edilmi?tir. ?kinci a?amada, ülke CDS?lerinin EGARCH modellemesinden elde edilen standart hatalar ve kareler kullanılarak, varyanstaki ve ortalamadaki nedensellikleri, çapraz korelasyon fonksiyonu yöntemi test edilmi?tir. Elde edilen test sonuçlarına göre; BRICS ülkeleri tarafında; Türkiye ile Çin, Güney Afrika ve Hindistan arasında kar?ılıklı nedensellik ili?kisi varken, Rusya?nın tek yönlü olarak Türkiye?yi etkilediği tespit edilmi?tir. Avrupa Birliği tarafında ise Almanya, Fransa ve Türkiye arasında kar?ılıklı nedensellik ili?kisi görülürken, ?ngiltere ve ?talya?nın tek yönlü olarak Türkiye?yi etkilediği görülmü?tür. Ayrıca bu çalı?ma ile CFF Yakla?ımının ülkelerin CDS?leri arasındaki nedensellik ili?kisini ölçmede etkili bir method olduğu görülmü?türÖğe Validity Analysis of Financial Failure Prediction Models During the Covid-19 Pandemic(Yaşar Üniversitesi, 2022) Özparlak, GerçekUnexpected bankruptcies of companies cause significant damage to company partners, investors, employees, countries, commercial and financial creditors. In this context, the financial failure risks should be constantly measured and controlled. However, it is important to constantly check the validity of financial models that measure the risk of the financial failure of companies. Because the higher the validity rates of these models, the higher the probability of investors and researchers to make the right decision according to the results obtained from these models. In this context, validity tests are widely used in the literature, namely Altman (1968), Springate (1978), Ohlson (1980), Fulmer (1984), Zmijewski (1984), Canada (1987) and Grove (2001) models, were applied in this study. The sample of this study consists of 16 companies that operate in the energy sector in the US markets. The universe of the study includes all companies that operate in the energy sector. The research results have shown that the Zmijewski model has been the most successful model for predicting company bankruptcies in the energy sector in the USA. The model that best predicted bankrupt and non-bankrupt companies 1 year and 3 years before the bankruptcy is again the Zmijewski model. However, Fulmer is the best bankruptcy predictor 2 years before the bankruptcy. On the other hand, according to other results of the research, the accuracy rate of Altman, Springate, Canadian, Fulmer and Grover models is well below the average compared to other studies in the literature.
