An Application of Risk Management on Airline Industry via Financial Ratios and Artificial Intelligence

International Journal of Business and Applied Social Science, Vol. 5, Issue 6, 2019

11 Pages Posted: 2 Oct 2019

See all articles by Burcu Baydar

Burcu Baydar

Turkish Airlines (THY) - Infrastructure and Operations Department

Günay Deniz Dursun

affiliation not provided to SSRN

Date Written: June 30, 2019

Abstract

The growing demand for airline transportation in recent years has increased the importance of airline passenger and cargo operations and aviation sector globally. Aviation sector is a sector that has unique properties like high fixed costs, cyclical demand, intense competition, and vulnerability to external shocks like terrorist attacks, disasters, global financial crises especially after deregulation in 1978. Air transport industry is responsible for connecting the global economy, providing a lot of jobs and making modern quality of life possible. Under high competition, it is crucial for airline companies to evaluate and analyze which core business areas are essential for them to prevent bankruptcy and to reach sustainable success. Initially developed in 1968 and evaluated by Altman in time, Altman’s Z score model remains a commonly used tool for evaluating the financial health. Altman Z” score has been well accepted, widely used models of predicting survivals and failures. This model is one of the most frequently used risk early warning models. As one of the biggest player of aviation sector, Turkish airline industry is affected by many different social, political, economic and legal factors on both national and international level as well as other airlines. It is very important to forecast the companies that may gone bankrupt and determine underlying causes. Therefore, this paper evaluates the Altman's Z” score model for predicting the bankruptcy risk of Turkish Airlines inc. which is the Turkey’s flag carrier via financial performance ratios taken from financial statements for the years between 2002 to 2016. Within the scope of the research, both the theoretical information and the applied method details are held. Also for next three years (2017-2019) Z” score values are predicted using artificial intelligence neural network algorithms.

Keywords: Transportation, Bankruptcy Forecasting Models, Artificial Intelligence

JEL Classification: G32,G33,C45

Suggested Citation

Baydar, Burcu and Dursun, Günay Deniz, An Application of Risk Management on Airline Industry via Financial Ratios and Artificial Intelligence (June 30, 2019). International Journal of Business and Applied Social Science, Vol. 5, Issue 6, 2019, Available at SSRN: https://ssrn.com/abstract=3414157

Burcu Baydar (Contact Author)

Turkish Airlines (THY) - Infrastructure and Operations Department ( email )

Turkey

Günay Deniz Dursun

affiliation not provided to SSRN

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