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Yayın Performance analysis in Turkish banking sector. Camels application(Işık Üniversitesi, 2020-01-15) Koç, Caner; Teker, Dilek; Işık Üniversitesi, Sosyal Bilimler Enstitüsü, Yöneticiler İçin İşletme Yönetimi Yüksek Lisans ProgramıAfter funds suppliers and funds demanders Banks are 3rd actors in the financial system. The banking sector accounts for most financial intermediaries. Fund transfer, Money supply, economic and financial policies support is some of the main activities. In addition to all its duties within the financial system, it also makes a huge contribution to the employment of the country as a sector. Thus, it has importance and responsibility for all kinds of structures in households, from small to medium-sized enterprises, commercial and corporate companies, to public institutions. All structures will be affected in case of possible crisis that banks will experience. These effects lead to many crises in the country, especially the economic crisis, and may result in serious chaos environments. In order not to experience these situations, the banking sector must be under audit and observation. One of the most important actions to be taken for this audit and observation is the regular measurement of financial performance analysis of banks. CAMELS analysis is a globally accepted system for this performance analysis. Camels analysis measures banks with components of capital adequacy, asset quality, management quality, profitability, liquidity and sensitivity to market risks. In this study, a total of 16 banks, 2 separate bank groups operating in the Turkish banking sector, 13 of which are private capital banks, 3 of which are Public Banks, were subjected to CAMELS analysis for 16 separate periods taking into account the balance sheets at the end of 2003 and 2018. According to the results of the study, among the banks, Türkiye Cumhuriyeti Ziraat Bankası A.Ş., Akbank T.A.Ş. ve Türkiye Garanti Bankası A.Ş. among the groups, it was observed that the group of Public Banks had stronger performance than other banks and groups.Yayın Optimal investment levels to eliminate inventory inaccuracy in a two-level supply chain(Istanbul Technical Univ, 2007) Uçkun, Canan; Karaesmen, Ahmet Fikri; Savaş, SelçukInventory inaccuracy is a major problem in supply chains. RFID technology is anticipated to alleviate this problem at the expense of the required hardware and software investment. For a supply chain consisting of single supplier and multiple warehouses, we investigate the optimal levels of investment in order to decrease inventory inaccuracy. The analysis yields in-sights on the relative benefits of RFID implementation depending on factors such as demand and inaccuracy variability, financial parameters and supply chain structure.Yayın What would normalisation of economic relations between Mashrek countries, Turkey and Israel imply?(Blackwell, 2007-04) Tovias, Alfred; Kalaycıoğlu, Sema; Dafni, Inon; Ruben, Ester; Herman, LiorThis article examines the potential for economic cooperation among Mashrek countries, Turkey and Israel in the fields of trade in goods and services both separately and across-field. It first describes the macroeconomic features of the region and then estimates the overall potential for inter-industry trade in goods by estimating gravity equations for each country separately and the potential for intra-industry trade using Grubel-Lloyd indices. The article also examines the potential for trade in specific services, namely information and computer technology, transport, financial and health services.Yayın ISIKUN at the FinCausal 2020: Linguistically informed machine-learning approach for causality identification in financial documents(Association for Computational Linguistics (ACL), 2020) Özenir, Hüseyin Gökberk; Karadeniz, İlknurThis paper presents our participation to the FinCausal-2020 Shared Task whose ultimate aim is to extract cause-effect relations from a given financial text. Our participation includes two systems for the two sub-tasks of the FinCausal-2020 Shared Task. The first sub-task (Task-1) consists of the binary classification of the given sentences as causal meaningful (1) or causal meaningless (0). Our approach for the Task-1 includes applying linear support vector machines after transforming the input sentences into vector representations using term frequency-inverse document frequency scheme with 3-grams. The second sub-task (Task-2) consists of the identification of the cause-effect relations in the sentences, which are detected as causal meaningful. Our approach for the Task-2 is a CRF-based model which uses linguistically informed features. For the Task-1, the obtained results show that there is a small difference between the proposed approach based on linear support vector machines (F-score 94%), which requires less time compared to the BERT-based baseline (F-score 95%). For the Task-2, although a minor modifications such as the learning algorithm type and the feature representations are made in the conditional random fields based baseline (F-score 52%), we have obtained better results (F-score 60%). The source codes for the both tasks are available online (https://github.com/ozenirgokberk/FinCausal2020.git/).Yayın Comparison of evolutionary techniques for Value-at-Risk calculation(Springer-Verlag Berlin, 2007) Uludağ, Gönül; Etaner Uyar, Ayşe Şima; Senel, Kerem; Dağ, HasanThe Value-at-Risk (VaR) approach has been used for measuring and controlling the market risks in financial institutions. Studies show that the t-distribution is more suited to representing the financial asset returns in VaR calculations than the commonly used normal distribution. The frequency of extremely positive or extremely negative financial asset returns is higher than that is suggested by normal distribution. Such a leptokurtic distribution can better be approximated by a t-distribution. The aim of this study is to asses the performance of a real coded Genetic Algorithm (CA) with Evolutionary Strategies (ES) approach for Maximum Likelihood (ML) parameter estimation. Using Monte Carlo (MC) simulations, we compare the test results of VaR simulations using the t-distribution, whose optimal parameters are generated by the Evolutionary Algorithms (EAs), to that of the normal distribution. It turns out that the VaR figures calculated with the assumption of normal distribution significantly understate the VaR figures computed from the actual historical distribution at high confidence levels. On the other hand, for the same confidence levels, the VaR figures calculated with the assumption of t-distribution are very close to the results found using the actual historical distribution. Finally, in order to speed up the MC simulation technique, which is not commonly preferred in financial applications due to its time consuming algorithm, we implement a parallel version of it.Yayın In bourgeoisie we trust, but which one? Islamism, development, and the “Finance Curse”(UiTM Press, 2015-01) Demiralp, SedaThe rise of Islamic financial institutions in the past decades stimulated studies that investigated their link to Islamic parties. Some perspectives viewed them as the financial wing of Islamic extremism. Others argued that the rise of an Islamic bourgeoisie, especially if integrated into the global economy, promotes moderation and liberalization among Islamic groups. This study investigates the relationship between the type of Islamic capital and Islamic moderation. In addition, it analyzes how state institutions can shape the trajectories of Islamic movements through economic policies. In this regard we compare and contrast production based capitalism which empowers industrial actors versus finance based capitalism which may not support the industry but strengthen financial elites. We find that production based development is more likely to promote mutual wins among Islamic and other actors and facilitate moderation than finance based economies which may promote zero-sum games and polarization.
