Vol. 10 No. 3 (2022): Business & Management Studies: An International Journal
Articles

Impact of the anticipated credit losses of businesses traded in BIST in wholesale and retail trade and restaurant and hotel industries on their financial statements

PDF (Türkçe)
  • Semra ÇAĞLAR,
  • Günay Deniz DURSUN
Semra ÇAĞLAR
PhD. Student, İstanbul Aydın University, İstanbul, Turkiye
Günay Deniz DURSUN
Assoc. Prof. Dr., Beykent University, İstanbul, Turkiye
DOI: https://doi.org/10.15295/bmij.v10i3.2090

Published 2022-09-25

Keywords

  • Beklenen Kredi Zararı, Panel Veri Analizi, TFRS 9, Finansal Araçlar
  • Anticipated Credit Loss, Panel Data Analysis, TFRS 9, Financial Instruments

How to Cite

ÇAĞLAR, S., & DURSUN, G. D. (2022). Impact of the anticipated credit losses of businesses traded in BIST in wholesale and retail trade and restaurant and hotel industries on their financial statements. Business & Management Studies: An International Journal, 10(3), 931–955. https://doi.org/10.15295/bmij.v10i3.2090

Copyright (c) 2022 Semra ÇAĞLAR- Günay Deniz DURSUN

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Abstract

This research aims to determine the impact levels of the anticipated credit losses of businesses traded in Borsa İstanbul A.Ş. (BIST) and operating in Wholesale and Retail Trade and Restaurant and Hotel Industries on their statements of financial position in line with Turkish Financial Reporting Standard 9 Financial Instruments (TFRS 9). In the research scope, we have reviewed the anticipated credit loss / current assets ratio retrieved from the statements of financial position and their footnotes for the 2018 to 2021 periods regarding the businesses traded in BIST and operating in Wholesale and Retail Trade and Restaurant and Hotel Industry for their impact on the liquidity ratios, financial structure ratios, profitability ratios, and growth rates using the panel data analysis methods. Considering the results of our study, we have concluded that the anticipated credit loss / current assets ratio harms the liquidity ratios, financial structure ratios, profitability ratios, and growth rates. The anticipated credit loss / current assets ratio gives rise to a decline in the businesses' liquid assets, short-term receivables, current assets, total assets, profitability, and equity.

PDF (Türkçe)

Downloads

Download data is not yet available.

References

  1. Akbayır, F,, & Yereli, A, B, (2020), Türkiye’de birincil dengeyi etkileyen faktörler, Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 15(2), 565-582,
  2. Akçin, O,, & Şen, İ, K, (2019), Özkaynak yatırımlarının UFRS 9 finansal araçlar standardı uyarınca muhasebeleştirilmesi, Muhasebe ve Finansman Dergisi, 83, 131-146,
  3. Akdoğan, N,, & Tenker, N, (2010), Finansal Tablolar ve Mali Analiz Teknikleri, Ankara: Gazi Kitabevi,
  4. Alves, A, T,, Bordin, M, P,, Gonzales, A,, & Santos, F, A, (2020), The impact from adapting of the IFRS 9 (CPC 48) on expected credit losses (ECL) in brazilian energy companies, Revista Ambiente Contábil, 12(1), 21-43,
  5. Arslan, A,, & Zaif, F, (2021), Beklenen kredi zararlarının ölçümünde kullanılan yöntemler: BIST 30’da bir araştırma, Muhasebe Bilim Dünyası Dergisi, 23(1), 144-171,
  6. Barnoussi, A, E,, Howieson, B,, & Beest, F, V, (2020), Prudential application of IFRS 9: (Un) fair reporting in COVID-19 crisis for banks worldwide?!, Australian Accounting Review, 94(30), 178-192,
  7. Beerbaum, D, (2020), COVİD-19: ABD değerleme modeli (CECL) ve UFRS 9 model değeri (ECL) çerçevesinde kredi departmanındaki transferler dengesi, Journal Of Applied Research İn Memory and Cognition, 1-12,
  8. Breitung, J, (2005), A parametric approach to the estimation of cointegration vectors in panel data, Econometric Reviews, 24(2), 151-173,
  9. Breuer, J, B,, Mcnown, R, F,, & Wallace, M, S, (2002), Series- specific unit root test with panel data, Oxford Bulletin of Economics and Statistics, 64, 527–573,
  10. Brkovic, M, (2017), IFRS 9 ımplementation in banks and macroeconomic scenarios some methodological aspects, Bankarstvo, 46(3), 36-51,
  11. Doğru, B, (2014), Türkiye’de para talebinin uzun ve kısa dönem dengesinin ARDL ve VEC yaklaşımları ile analiz edilmesi, Ekonomik ve Sosyal Araştırmalar Dergisi, 10(2), 19-31,
  12. Fidan, M, M, (2019), Ticari alacaklarda değer düşüklüğü–TFRS 9 finansal araçlar standardının basit yaklaşımı ve vergi usul kanunu karşılaştırılması, Muhasebe ve Finansman Dergisi, 81, 37-58,
  13. Gökgöz, A, (2019), TFRS 9 finansal araçlar standardı çerçevesinde ticari alacaklara ilişkin beklenen kredi zararlarının tespiti ve muhasebeleştirilmesi,, Journal of Accounting, Finance and Auditing Studies, 5(2), 163-178,
  14. Groff, M, Z,, &Mörec, B, (2020), IFRS 9 transition effect on equity in a post bank recovery environment: The case of slovenia, Economic Research, 1-17,
  15. Grzybowska, U,, & Karwanski, M, (2020), Application of machine learning method under IFRS 9 approach to LGD modeling, Proceedings of the 10th Polish Symposium on Physics in Economy and Social Sciences, 138(1), 116-122,
  16. Güzel, A, E,, & Arslan, Ü, (2019), Piyasa ekonomisi kurumları, ekonomik küreselleşme ve insani gelişme: OECD ülkeleri için ampirik bir araştırma, Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 53, 39-58,
  17. Hadri, K, (2000), Testing for stationarity in heterogeneous panel data, The Econometrics Journal, 3, 148-161,
  18. Hadri, K,, & Kurozumi, E, (2012), A simple panel stationarity test in the presence of serial correlation and a common factor, Economics Letters, 115(1), 31-34,
  19. Halilbegoviç, S,, Šaković, E,, Arapoviç, A, O,, & Čelebić, N, (2019), Implementation effects of “IFRS 9 impairment modelling for financial instruments” on regulatory capital banks in federation of bosnia and herzegovina, European Journal of Economic Studies, 8(2), 120-130,
  20. Ilgaz, B, Oran analizleri, Erişim Tarihi 27 Haziran 2022, www,bilgaz,net/dosyalar/orananalizi,pdf
  21. Im, K,S,, Pesaran, M,H,, & Shin, Y, (2003), Testing for unit roots in heterogeneous panels, Journal of Econometrics, 115, 53-74,
  22. Karaarslan, S,, & Gülhan, O, (2020), TFRS 9’a geçişin Türkiye’de halka açık bankaların finansal durum tablolarına etkileri, Muhasebe ve Finansman Dergisi, 86, 111-124,
  23. Landini, S,, Uberti, M,, & Casellina, S, (2018), Credit risk migration rates modeling as open systems: A micro-simulation approach, Commun Nonlinear Sci Numer Simulat, 58, 147–166,
  24. Levin, A,, Lin, C,F,, & Chu, C,S,J, (2002), Unit root tests in panel data: Asymptotic and finite-sample properties, Journal Of Econometrics, 108(1), 1-24,
  25. Mechelli, A,, & Cimini, R, (2020), The efect Of corporate governance and investor protection environments on the value relevance of new accounting standards: The case of IFRS 9 and IAS 39, Journal of Management and Governance, 25(4), 1-26,
  26. Pesaran, M, H, (2004), General diagnostic tests for cross section dependence in panels, Cesifo Working Paper No, 1229, 1-39,
  27. Pesaran, M, H, (2007), A simple panel unit root test in the presence of cross-section dependence, Journal of Applied Econometrics, 22, 265-312,
  28. Sağdıç, E,N,, & Yıldız, F, (2021), Küreselleşme sürecinde finansal gelişmişliğin vergi gelirleri üzerindeki etkisi: Türkiye örneği (1986-2018), The Journal of International Scientific Researches, 6(2), 108-122,
  29. Schutte, W,D,, Verster, T,, Doody, D,, Raubenheimer, H,, & Coetzee, P, J, (2020), A proposed benchmark model using a modularised approach to calculate IFRS 9 expected credit loss, Cogent Economics & Finance, 8(1), 1-27,
  30. Taylor, M, P,, & Sarno, L, (1998), The behavior of real exchange rates during the post-bretton woods period, Journal of International Economics, 46, 281-312,
  31. TCMB, Oran formülleri, Erişim Tarihi 27 Haziran 2022, http://www3,tcmb,gov,tr/sektor/dosyalar/menu/ratios_tr,pdf