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Time Series Analysis of Financial Statements for Default Modelling
P. 281–286.
Romanyuk K., Ichkitidze Y.
Credit rating agencies evaluate corporate risks and assign ratings to companies. Each rating grade corresponds to certain boundaries of default probability. KMV is a popular model to assess the default probability of a company. In this paper, a method to predict the default probability of a company is proposed. This method is based on the main concept of the KMV model; however, financial statements are applied instead of stock prices, i.e. time-series of EBIT (earnings before interest and taxes), net debt, sales, and the last year value of WACC (weighted average cost of capital). Default probabilities for 150 companies are evaluated. Results and limitations are discussed.
In book
Vol. 1228. , Springer, 2020.
Karpukhin I., Savchenko A., , in: Proceedings of the AAAI Conference on Artificial Intelligence. AAAI-26: AAAI Technical Track on Planning, Routing, and Scheduling; AAAI Technical Track on Reasoning under Uncertainty; AAAI Technical Track on Search and Optimization. Main Track, volume 40 no. 43.: American Association for Artificial Intelligence (AAAI) Press, 2026. P. 22536–22544.
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