Financial performance analysis of BIST100 tourism companies
Is this your thesis?
This record came from a bulk archive import. If it’s yours, link it to your profile.
Abstract (EN)
For a business to achieve sustainable success, it must show a good financial performance. Investors pay attention to whether companies' performance is sustainable and how their financial performance is according to the sector. Determination of financial performance is crucial not only for investors but also for the company to evaluate itself based the sector and to take actions. Since tourism companies are in a sector where large investments are required, the measurement of financial performance is very critical for this sector. In addition, the sector which is deeply affected by the economic and political conjuncture of the country, needs an assessment of its financial performance in order to take measures against these risks over the years. In this study eight tourism companies in BIST were evaluated based on financial performance using financial ratios. As a result of the analysis made with liquidity, leverage, profitability, activity ratios and cash conversion time, implications and suggestions regarding the sector are presented.
Author
Nagihan Çardak
Institution
How to Cite
Nagihan Çardak (Master Thesis). Financial performance analysis of BIST100 tourism companies, 2021, Yeditepe University.
Keywords
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from Yeditepe University
- Studies on cyclodextrin complexation of a poorly water soluble anti-hyperlipidemic drug, tablet formulation and characterization(2021)
- Washington ambassadors in Turkish-US relations (1927-1960)(2023)
- The relationship between mindfulness and sleep quality: The mediating role of smartphone addiction and bedtime procrastination(2023)
- The role of NATO's enlargement policy in the Russia-Ukraine crisis(2023)
- Metamorphosis of female voices: A study of the violation of women in Greek and Roman mythology and feminist rewritings reclaiming the narrative(2022)
- Knowledge distillation with foundation models for image segmentation(2023)