Davutyan, Nurhan

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Davutyan, Nurhan
N.,Davutyan
N. Davutyan
Nurhan, Davutyan
Davutyan, Nurhan
N.,Davutyan
N. Davutyan
Nurhan, Davutyan
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Nurhan.davutyan@khas.edu.tr
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International Trade and Finance
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Former Staff
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Scholarly Output

11

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4

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0

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5

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2013 - 20194
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Type: Master Thesis

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Now showing 1 - 4 of 4
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    Master Thesis
    Estimate the Yield Curve for Sovereign Bonds in Turkey and Forecasting Turkish Economy From the Shape of Yield Curve (2005 - 2018)
    (Kadir Has Üniversitesi, 2019) Temuçin, Teoman Samet; Davutyan, Nurhan; Davutyan, Nurhan
    Yield curve that reflects the interest expectations of market participants is one of the cornerstones of the financial analysis. In the first chapter of our study, Turkey yield curve for sovereign bond market is estimated in 2005-2018 by using Extended NelsonSiegel (ENS) and Dynamic Nelson-Siegel (DNS) models. Since Turkish sovereign market becomes more liquid and 10-year fixed rate coupon bonds were started to be traded after 2010, this allows us to make estimation for 10-year term to maturity. As a result of estimation via two methodologies, it is concluded that Dynamic Nelson-Siegel model estimates Turkey yield curve slightly better than the Extended Nelson-Siegel model. Besides, OLS (Ordinary Least Square) is better methodology than optimization tools in DNS. This is why, the estimated Turkey yield curve via Dynamic Nelson-Siegel model with OLS methodology is used to forecast Turkish macroeconomic and financial indicators in the second chapter of the study. The yield curve can be simply perceived as a representation of interest rates of treasury bonds or other security instruments in different maturities. However, that simple graph is beyond the representation of interest rate. If it is read carefully, the market efficiency theory can be beaten and regular profits from the market can be made. Many scholars and empirical studies of them have proved the significant forecasting ability of the yield curve about recessions, turning points in the stock market and inflation rates. Therefore, it seems as a reliable mechanism for forecasting to some important indicators in the macroeconomic set. I also simply test the forecasting capabilities of the estimated Turkey yield curve on Turkish recessions, bear market, industrial production index, bist100 index and consumer price index. As a result of analysis, it is concluded that parameters, which represent the Turkey’s yield curve, contain important information and predictions regarding recessions, bear market formation, bist100 index and consumer price index.
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    Master Thesis
    Kredi ve Likidite Açısından Kobi-banka İlişki Yönetimi: İstanbul Örneği
    (Kadir Has Üniversitesi, 2013) Apan, Mehmet; Davutyan, Nurhan; Davutyan, Nurhan
    Bu tez calismasi ile KOB'lerin kredi ve likidite acisindan bankalarla iliskilerini nasil yonettiklerinin tespit edilmesi amaclanmistir. Bu kapsamda KOBİ-Banka ?liski Yonetimi icin “Dagitim Kanallari” “Musteri Memnuniyeti” “Kurumsallasma ve Raporlama” “Bilgi ve Uzmanlik” “?letisim Ulasilabilirlik ve İlem Hizi” “Likidite Yonetimi” “Kredinin Yapisi ve Prosedurler” ve “Bankacilik Sektorunun Yapisi ve Regulasyonlar” ana karakteristikleri tez arastirmasi ile analiz edilmistir.
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    Master Thesis
    Estimating Size of Shadow Economy Through Cda: the Case of Turkey
    (Kadir Has Üniversitesi, 2017) Toker, Serkan; Davutyan, Nurhan; Davutyan, Nurhan
    This paper estimates the size of the shadow economy for the 26 NUTS-2 regions of Turkey. it is the first research that attempts at the NUTS-2 level for Turkey in the literature. The estimation used yearly data covering 2011-2014 and applies the modified currency demand approach by Ardizzi et al. (2014) with several updates. The size of the shadow economy is found as between 6.23% and 7.09% of official GDP of Turkey for the years 2011 to 2014. Results are just an indication of its base value. Because we do not have available data of cash in circulation for each NUTS-2 area we assume cash flow in circulation is approximately equal to demand deposit flow. However when the movements of the monetary aggregates variable at the country level are examined they demonstrate the similar trend. Thus this paper also present reliable distribution of the shadow economy among 26 Turkish areas. Results indicate that shadow economy has an upward trend over these specified years and the size of it in metropolitan areas like istanbul Ankara and izmir is bigger than in other areas. Also the magnitude of it is decreasing when moving from the western areas to the eastern areas of Turkey.
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    Master Thesis
    An Empirical Study on Credit Early Warning Systems
    (Kadir Has Üniversitesi, 2016) Ongoren, Haluk; Davutyan, Nurhan; Davutyan, Nurhan
    Due to its impact on profitability and its potential regulatory consequences financial distress prediction is vitally important for banks. The first generation of prediction models were based on the dichotomous classification of survival versus failure states and utilized balance sheet figures and income statements of bank customers to make predictions. However those models were not designed to accommodate the change in the financial situation of bank customers over time. We define default broadly as the bank declaring a loan as non-performing or initiating the legal process to collect the claimed amounts from the borrower. in this study we use Cox's PH – Proportional Hazard approach to predict the potential defaulters using an unbalanced panel data set from 2005 and 2012. We have 202615 observations on 15593 customers obtained from one of the most reputable participation banks. To our knowledge it is the first application of the Cox PH model to predict financial distress of bank borrowers. it is also important to note that it is also the first such study where only core banking information namely accounting and lending records is used. We did not adopt the traditional approach and thus did not use customer financial statements in our study. We create three different financial distress models and use selectivity ratio and success rate for defaulters terminology to analyze which model's predictive performance is better. We conclude that 72.41% of actual defaulters in the first quarter of 2013 and 58.37% of actual defaulters in 2013 have already been predicted by our Model at the end of 2012.