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A Comparables Approach To Measuring Cashflow‐At‐Risk For Non‐Financial Firms

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  • Jeremy C. Stein
  • Stephen E. Usher
  • Daniel LaGattuta
  • Jeff Youngen

Abstract

Cashflow‐at‐Risk (C‐FaR) is an attempt to create an analogue to Value at Risk (VaR) that can be used by non‐financial firms to quantify various kinds of risk exposures, including interest rate, exchange rate, and commodity price risks. There are two basic ways to attack this problem. One is from the “bottom up,” which involves building a detailed model of all of a company's specific exposures. The C‐Far approach presented here is a “top‐down” method of comparables that looks directly at the ultimate item of interest—the companies' cashflows. The fundamental challenge facing the top‐down strategy is that, for any one company, there is not enough data on its own cashflows to make precise statements about the likelihood of rare events. To get around this problem, the authors match a target company with a large set of comparable companies that are expected to have similar cashflow volatility. The comparables are chosen to be close to the target company on four dimensions: (1) market cap; (2) profitability; (3) industry risk; and (4) stock price volatility. C‐FaR can be useful to managers addressing a variety of corporate finance decisions. For example, by providing estimates of the probability of financial distress, the C‐FaR method can be used in conjunction with capital structure data to help formulate debt‐equity tradeoffs in a more precise, quantifiable fashion. It can also be used to evaluate a firm's overall risk management strategy, including the expected benefits of using derivatives to hedge commodity‐price exposures or the purchase of insurance policies. Moreover, C‐FaR may even have a use in investor relations: by disclosing the results of a comparables‐based C‐FaR analysis ahead of time, a company may be able to cushion earnings shocks by furnishing investors or analysts with credible, objective estimates of what is likely to happen to their cash flows under different economic scenarios.

Suggested Citation

  • Jeremy C. Stein & Stephen E. Usher & Daniel LaGattuta & Jeff Youngen, 2001. "A Comparables Approach To Measuring Cashflow‐At‐Risk For Non‐Financial Firms," Journal of Applied Corporate Finance, Morgan Stanley, vol. 13(4), pages 100-109, January.
  • Handle: RePEc:bla:jacrfn:v:13:y:2001:i:4:p:100-109
    DOI: 10.1111/j.1745-6622.2001.tb00430.x
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    Cited by:

    1. Tat’yana Serebryakova Yur’evna & Татьяна Серебрякова Юрьевна, 2018. "Научно-методический аспект учета рисков организации // Scientific and Methodological Aspectsof Risk Accounting in an Organization," Учет. Анализ. Аудит // Accounting. Analysis. Auditing, ФГОБУВО "Финансовый университет при Правительстве Российской Федерации" // Financial University under The Government of Russian Federation, vol. 5(1), pages 44-55.
    2. Marcello Spanò, 2013. "Theoretical explanations of corporate hedging," International Journal of Business and Social Research, LAR Center Press, vol. 3(7), pages 84-102, July.
    3. Hsia Hua Sheng & Cristiane Karcher & Paulo Hubert Jr., 2009. "An Alternative Model of Risk in Non-financial Companies Applied to the Brazilian Pulp and Paper Industry," Brazilian Review of Finance, Brazilian Society of Finance, vol. 7(3), pages 347-360.
    4. Sumon Kumar Bhaumik & Saul Estrin & Tomasz Mickiewicz, 2017. "Ownership identity, strategy and performance: Business group affiliates versus independent firms in India," Asia Pacific Journal of Management, Springer, vol. 34(2), pages 281-311, June.
    5. Friberg, Richard & Huse, Cristian, 2012. "How to use demand systems to evaluate risky projects, with an application to automobile production," CEPR Discussion Papers 9266, C.E.P.R. Discussion Papers.
    6. Mark Carey & René M. Stulz, 2007. "The Risks of Financial Institutions," NBER Books, National Bureau of Economic Research, Inc, number care06-1, July.
    7. Sanda, Gaute Egeland & Olsen, Eirik Tandberg & Fleten, Stein-Erik, 2013. "Selective hedging in hydro-based electricity companies," Energy Economics, Elsevier, vol. 40(C), pages 326-338.
    8. Halkos, George E. & Tsirivis, Apostolos S., 2019. "Value-at-risk methodologies for effective energy portfolio risk management," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 197-212.
    9. N.N. Natocheeva & V.B. Frolova & T.V. Belyanchikova, 2018. "Model of Assessing the Impact of Factors on Cash Flow Multiplicators," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 338-347.
    10. Baule, Rainer, 2014. "Allocation of risk capital on an internal market," European Journal of Operational Research, Elsevier, vol. 234(1), pages 186-196.
    11. Yingying Kang & Rajan Batta & Changhyun Kwon, 2014. "Value-at-Risk model for hazardous material transportation," Annals of Operations Research, Springer, vol. 222(1), pages 361-387, November.
    12. Marcello Spanò, 2013. "Theoretical explanations of corporate hedging," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 3(7), pages 84-102, July.
    13. Halkos, George & Tsirivis, Apostolos, 2019. "Using Value-at-Risk for effective energy portfolio risk management," MPRA Paper 91674, University Library of Munich, Germany.
    14. Degl’Innocenti, Marta & Fiordelisi, Franco & Trinugroho, Irwan, 2020. "Competition and stability in the credit industry: Banking vs. factoring industries," The British Accounting Review, Elsevier, vol. 52(1).
    15. Mark Carey & Rene M. Stulz, 2007. "Introduction to "The Risks of Financial Institutions"," NBER Chapters, in: The Risks of Financial Institutions, pages 1-25, National Bureau of Economic Research, Inc.
    16. Alessandro Gennaro, 2021. "Insolvency Risk and Value Maximization: A Convergence between Financial Management and Risk Management," Risks, MDPI, vol. 9(6), pages 1-36, June.

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