PERFORMANCE ANALYSIS IN INSURANCE COMPANIES: AN APPLICATION FOR BIST INSURANCE INDEX

Yıldırım Ercan ÇALIŞ () and Mehmet Zafer TAŞÇI ()
Additional contact information
Yıldırım Ercan ÇALIŞ: Marmara Üniversitesi
Mehmet Zafer TAŞÇI: Sivas Cumhuriyet Üniversitesi

Eurasian Academy Of Sciences Social Sciences Journal, 2020, vol. 30, issue 30, 69-80

Abstract: The aim of this study is to evaluate the financial performance of the insurance companies traded on the Borsa Istanbul Insurance Index with SD (Standard Deviation) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) techniques.For this purpose, the data of six insurance companies in the insurance index for the period covering 2015-2018 are used.Performance criteria selected for SD-TOPSIS integrated model are earned gross premium, realized gross loss, total assets, total debt, equity, profit before tax, market value and market value added.In this study, in which the SD and TOPSIS methods are used for the first time to evaluate the financial performance of BIST insurance companies, the priority weights of the performance criteria selected with the SD technique are calculated, and the insurance companies are ranked in terms of performance with the TOPSIS method.According to the results of the study, the company showing the best financial performance in all years is Güneş Sigorta.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
https://eurasianacademy.org/index.php/socialsciences/article/view/296 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eas:journl:v:30:y:2020:i:30:p:69-80

DOI: 10.17740/eas.soc.2020.V30-05

Access Statistics for this article

More articles in Eurasian Academy Of Sciences Social Sciences Journal from Eurasian Academy Of Sciences
Bibliographic data for series maintained by Kutluk Kagan Sumer ().