Abstract
This chapter explores two problems: bankruptcy probability and company life expectancy. Bankruptcy probability and bankruptcy cost are the major bankruptcy risk measurement and major concern of the relevant parties of a company. However, neither bankruptcy probability nor bankruptcy cost can be calculated in mainstream finance. This chapter solves this quantitative problem based on the bankruptcy cost model derived in Chapter “Debt/Loan Risk, Bankruptcy Cost and Debt/Loan Pricing”. In addition, the bankruptcy probability and cost can be calculated for potential current bankruptcy and overall bankruptcy respectively. Such new bankruptcy risk analyses are illustrated based on the case of the three home appliances giants in China. Further, the findings in the bankruptcy risks setup the theoretical foundation for us to further predict the company life expectancy. We then explore the estimation of company life expectancy. Based on the queueing theory, the estimation of company life expectancy depends on the long run applicable annual bankruptcy probability. Further discussion reveals the logic from cumulative bankruptcy probability to annual bankruptcy probability and further to the long run applicable annual bankruptcy probability. Hence the problem of company life expectancy estimation is ideally solved.
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Notes
- 1.
The total asset can provide additional guarantee for the repayment of the current debt. This implies some of the repayment pressure or risk is partaken by the total asset, or the current asset is relative less risky than the total asset. But the specific measurement of the division of the risk is a little complicated. We just deal it simply by cutting the volatility of the total asset by 50% as the volatility of the current asset.
- 2.
One of the possible situations is: the growth rate is 8%, required payback period is 10 years, and the expected return on equity is 12%, then, based on Eq. (29) in Chapter “Stock and Equity Valuation: Where Discounting Does Not Work”, ZZ P/B = [(1 + g)n − 1](1 + g)re/g = 2.03.
- 3.
For healthy companies like those three companies, this is a reasonable assumption.
- 4.
Round up rather than round off.
References
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Further Readings
Beaver WH. Financial ratios as predictors of failure. J Account Res. 1966;4:71–111.
Beaver WH. Alternative accounting measures as predictors of failure. Account Rev. 1968;43:113–22.
Altman EI. Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. J Finance. 1968;189–209.
Agarwal V, Taffler RJ. Twenty-five years of the Taffler z-score model: does it really have predictive ability? Account Bus Res. 2007;37:285–300.
Ashraf S, Félix EGS, Serrasqueiro Z. Do traditional financial distress prediction models predict the early warning signs of financial distress? J Risk Financ Manage. 2019;12:55–66.
Koh HC, Tan SS. A neural network approach to the prediction of going concern status. Account Bus Res. 1999;29:211–16.
Sigrist F, Hirnschall C. Grabit: gradient tree-boosted Tobit models for default prediction. J Bank Finance. 2019;102:177–92.
Hull JC. Risk management and financial institutions. 3rd ed. Wiley; 2012. p. 249.
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Zhang, Z. (2023). Bankruptcy Probability and Firm Life Expectancy. In: Fundamental Problems and Solutions in Finance. Contributions to Finance and Accounting. Springer, Singapore. https://doi.org/10.1007/978-981-19-8269-9_12
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DOI: https://doi.org/10.1007/978-981-19-8269-9_12
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