Browsing by Author "Oz, Ibrahim Onur"

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Citation - WoS: 11
Citation - Scopus: 10
Bankruptcy Prediction Models' Generalizability: Evidence From Emerging Market Economies
(Elsevier Science Bv, 2018) Oz, Ibrahim Onur; Simga-Mugan, Can
[Abstract Not Available]
Citation - WoS: 43
Citation - Scopus: 50
Examination of Real and Accrual Earnings Management: a Cross-Country Analysis of Legal Origin Under Ifrs
(Elsevier Science Inc, 2018) Oz, Ibrahim Onur; Yelkenci, Tezer
This study examines the impact of legal origin differences on accrual and real earnings management behaviors for 14 international financial reporting standards (IFRS) countries. Specifically, a cross-country analysis determines the effects of enforcement intensity and IFRS adoption on earnings management (EM) types, depending on code or common law origins. The results indicate that legal origin directly affects EM behaviors, whereas enforcement intensity and IFRS result in different accrual earnings management (AEM) and real earnings management (REM) behaviors depending on the different legal origins. In particular, the findings also suggest that an increase in enforcement strength may not produce similar EM results for each legal tradition, specifically for the expected shift from AEM to REM as recent studies have proposed. This study also offers evidence that IFRS represent a constraint on AEM in code law origin countries, and it highlights a constraint on REM only for common law countries when the enforcement intensity increases.
Citation - WoS: 49
Citation - Scopus: 61
Investigating the Natural Gas Supply Security: a New Perspective
(Pergamon-Elsevier Science Ltd, 2015) Biresselioglu, Mehmet Efe; Yelkenci, Tezer; Oz, Ibrahim Onur
This paper assesses the natural gas supply security of 23 importing countries from divergent regions of the world for the period between 2001 and 2013. The indicators used for the study are the volume of imported natural gas, the number of natural gas suppliers, the level of dependency on one country, import dependency, the fragility of supplier countries, and the share of natural gas in primary energy consumption. The method used to establish the supply security index is the PCA (principal component analysis) over the indicators in the model for each country on a yearly basis for the period 2001 to 2013. The dispersed country sample enables the established index to measure the sensitivity of specific natural gas importer countries using a uniform framework. According to the results, the most effective indicators for the measurement of supply security are the number of supplier countries, supplier fragility, and the overall volume of imported gas. (C) 2014 Elsevier Ltd. All rights reserved.
The Role of Earnings Components and Machine Learning on the Revelation of Deteriorating Firm Performance
(Elsevier Science Inc, 2021) Oz, Ibrahim Onur; Yelkenci, Tezer; Meral, Gorkem
This study explores the proficiency of earnings components for detecting earnings and cash flows distress. The authors examine the deterioration of these two performance indicators for two aggregate and two disaggregate earnings models, each of which is subject to examination through different machine learning, non-parametric, and parametric methods. The results, obtained from firms in 22 countries, reveal that the current information content of earnings not only has explanatory power for future earnings and cash flows but also can support advance classifications of the two performance indicators as negative or positive. Each aggregate and disaggregate model offers distress classification ability, the disaggregation of earnings generates better, robust detection accuracies for cash flow distress, while aggregate earnings model provides improved classification for prospective earnings distress. The findings also suggest that machine learning estimation methods provide superior distress detection compared to a parametric method, despite its still decent performance.
Citation - WoS: 11
Citation - Scopus: 18
A Theoretical Approach To Financial Distress Prediction Modeling
(Emerald Group Publishing Ltd, 2017) Oz, Ibrahim Onur; Yelkenci, Tezer
Purpose - The purpose of this paper is to examine a theoretical base for the financial distress prediction modeling over eight countries for a sample of 2,500 publicly listed non-financial firms for the period from 2000 to 2014. Design/methodology/approach - The prediction model derived through the theory has the potential to produce prediction results that are generalizable over distinct industry and country samples. For this reason, the prediction model is on the earnings components, and it uses two different estimation methods and four sub-samples to examine the validity of the results. Findings - The findings suggest that the theoretical model provides high-level prediction accuracy through its earnings components. The use of a large sample from different industries in distinct countries increases the validity of the prediction results, and contributes to the generalizability of the predictionmodel in distinct sectors. Originality/value - The results of the study fulfill the gap and extend the literature through a distress model, which has the theoretical origin enabling the generalization of the prediction results over different samples and estimation methods.