IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v218y2022ics016517652200266x.html
   My bibliography  Save this article

Valuation of European firms during the Russia–Ukraine war

Author

Listed:
  • Bougias, Alexandros
  • Episcopos, Athanasios
  • Leledakis, George N.

Abstract

We infer the asset value dynamics of European firms during the Russia–Ukraine war via the structural model of Merton (1974). Using high-frequency stock price data, we find that the war led to lower corporate security prices and higher asset volatility, eventually shifting asset values closer to the default region. On average, the balance sheet of European firms is expected to shrink by 2.05% and their 1-year default probability to increase from 0.32% to 2.12%. Regression analysis on asset and equity returns as well as default probability changes suggests that these effects are stronger for firms with large revenue exposure to Russia.

Suggested Citation

  • Bougias, Alexandros & Episcopos, Athanasios & Leledakis, George N., 2022. "Valuation of European firms during the Russia–Ukraine war," Economics Letters, Elsevier, vol. 218(C).
    • Handle: RePEc:eee:ecolet:v:218:y:2022:i:c:s016517652200266x
    DOI: 10.1016/j.econlet.2022.110750
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S016517652200266X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2022.110750?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007. "Multi-period corporate default prediction with stochastic covariates," Journal of Financial Economics, Elsevier, vol. 83(3), pages 635-665, March.
    2. Boungou, Whelsy & Yatié, Alhonita, 2022. "The impact of the Ukraine–Russia war on world stock market returns," Economics Letters, Elsevier, vol. 215(C).
    3. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    4. Tosun, Onur Kemal & Eshraghi, Arman, 2022. "Corporate decisions in times of war: Evidence from the Russia-Ukraine conflict," Finance Research Letters, Elsevier, vol. 48(C).
    5. Amelie Brune & Thorsten Hens & Marc Rieger & Mei Wang, 2015. "The war puzzle: contradictory effects of international conflicts on stock markets," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 62(1), pages 1-21, March.
    6. Suresh Sundaresan, 2013. "A Review of Merton’s Model of the Firm’s Capital Structure with Its Wide Applications," Annual Review of Financial Economics, Annual Reviews, vol. 5(1), pages 21-41, November.
    7. Ming Deng & Markus Leippold & Alexander F. Wagner & Qian Wang, 2022. "War and Policy: Investor Expectations on the Net-Zero Transition," Swiss Finance Institute Research Paper Series 22-29, Swiss Finance Institute, revised May 2023.
    8. Benjamin Yibin Zhang & Hao Zhou & Haibin Zhu, 2009. "Explaining Credit Default Swap Spreads with the Equity Volatility and Jump Risks of Individual Firms," Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5099-5131, December.
    9. Bruno Frey & Marcel Kucher, 2001. "Wars and Markets: How Bond Values Reflect the Second World War," Economica, London School of Economics and Political Science, vol. 68(271), pages 317-333, August.
    10. Maria Vassalou & Yuhang Xing, 2004. "Default Risk in Equity Returns," Journal of Finance, American Finance Association, vol. 59(2), pages 831-868, April.
    11. Choudhry, Taufiq, 2010. "World War II events and the Dow Jones industrial index," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 1022-1031, May.
    12. Jessen, Cathrine & Lando, David, 2015. "Robustness of distance-to-default," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 493-505.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Umar, Zaghum & Bossman, Ahmed & Choi, Sun-Yong & Vo, Xuan Vinh, 2023. "Are short stocks susceptible to geopolitical shocks? Time-Frequency evidence from the Russian-Ukrainian conflict," Finance Research Letters, Elsevier, vol. 52(C).
    2. Oana Panazan & Catalin Gheorghe, 2024. "Impact of Geopolitical Risk on G7 Financial Markets: A Comparative Wavelet Analysis between 2014 and 2022," Mathematics, MDPI, vol. 12(3), pages 1-22, January.
    3. Liu, Wei & Chen, Xiao & Zhang, Jihong, 2023. "The Russia-Ukraine conflict and the automotive energy transition: Empirical evidence from China," Energy, Elsevier, vol. 284(C).
    4. Alcindo Neckel & M. Santosh & Brian William Bodah & Laércio Stolfo Maculan & Diana Pinto & Cleiton Korcelski & Paloma Carollo Toscan & Laura Pasa Cambrussi & Isadora Cezar Caino & Leila Dal Moro & Dir, 2022. "Using the Sentinel-3B Satellite in Geospatial Analysis of Suspended Aerosols in the Kiev, Ukraine Region," Sustainability, MDPI, vol. 14(24), pages 1-14, December.
    5. Marjan Petreski, 2023. "The impact of the crisis induced by the conflict in Ukraine on firms in North Macedonia: Evidence from a micro-survey," Finance Think Policy Studies 2023-06/46, Finance Think - Economic Research and Policy Institute.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiaoqing Fu & Matthew C. Li & Philip Molyneux, 2021. "Credit default swap spreads: market conditions, firm performance, and the impact of the 2007–2009 financial crisis," Empirical Economics, Springer, vol. 60(5), pages 2203-2225, May.
    2. Afik, Zvika & Arad, Ohad & Galil, Koresh, 2016. "Using Merton model for default prediction: An empirical assessment of selected alternatives," Journal of Empirical Finance, Elsevier, vol. 35(C), pages 43-67.
    3. Umar, Muhammad & Riaz, Yasir & Yousaf, Imran, 2022. "Impact of Russian-Ukraine war on clean energy, conventional energy, and metal markets: Evidence from event study approach," Resources Policy, Elsevier, vol. 79(C).
    4. Turalay Kenc & Emrah Ismail Cevik, 2021. "Estimating volatility clustering and variance risk premium effects on bank default indicators," Review of Quantitative Finance and Accounting, Springer, vol. 57(4), pages 1373-1392, November.
    5. Piotr Fiszeder & Marta Ma³ecka, 2022. "Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(4), pages 939-967, December.
    6. Turalay Kenc & Emrah Ismail Cevik & Sel Dibooglu, 2021. "Bank default indicators with volatility clustering," Annals of Finance, Springer, vol. 17(1), pages 127-151, March.
    7. Daniel Dimitrov & Sweder van Wijnbergen, 2022. "Quantifying Systemic Risk in the Presence of Unlisted Banks: Application to the Dutch Financial Sector," Tinbergen Institute Discussion Papers 22-034/VI, Tinbergen Institute.
    8. Batten, Jonathan A. & Khaw, Karren Lee-Hwei & Young, Martin R., 2021. "Convertible debt and asset substitution of multinational corporations," Journal of Corporate Finance, Elsevier, vol. 67(C).
    9. Jessen, Cathrine & Lando, David, 2015. "Robustness of distance-to-default," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 493-505.
    10. Huang, Hsing-Hua & Lee, Han-Hsing, 2013. "Product market competition and credit risk," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 324-340.
    11. Giesecke, Kay & Longstaff, Francis A. & Schaefer, Stephen & Strebulaev, Ilya, 2011. "Corporate bond default risk: A 150-year perspective," Journal of Financial Economics, Elsevier, vol. 102(2), pages 233-250.
    12. Bijoy Chandra Das & Fakhrul Hasan & Soma Rani Sutradhar & Sujana Shafique, 2023. "Ukraine–Russia Conflict and Stock Markets Reactions in Europe," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(3), pages 395-407, September.
    13. Tsai, Feng-Tse & Lu, Hsin-Min & Hung, Mao-Wei, 2016. "The impact of news articles and corporate disclosure on credit risk valuation," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 100-116.
    14. Pu, Xiaoling & Zhao, Xinlei, 2012. "Correlation in credit risk changes," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1093-1106.
    15. Duc Hong Vo & Binh Ninh Vo Pham & Chi Minh Ho & Michael McAleer, 2019. "Corporate Financial Distress of Industry Level Listings in Vietnam," JRFM, MDPI, vol. 12(4), pages 1-17, September.
    16. Stefan Nagel & Amiyatosh Purnanandam & Itay Goldstein, 2020. "Banks’ Risk Dynamics and Distance to Default [Robust comparative statics in large dynamic economies]," Review of Financial Studies, Society for Financial Studies, vol. 33(6), pages 2421-2467.
    17. Gatfaoui, Hayette, 2017. "Equity market information and credit risk signaling: A quantile cointegrating regression approach," Economic Modelling, Elsevier, vol. 64(C), pages 48-59.
    18. Koresh Galil & Neta Gilat, 2019. "Predicting Default More Accurately: To Proxy or Not to Proxy for Default?," International Review of Finance, International Review of Finance Ltd., vol. 19(4), pages 731-758, December.
    19. Wan†Chien Chiu & Juan Ignacio Peña & Chih†Wei Wang, 2015. "Measuring Systemic Risk: Common Factor Exposures and Tail Dependence Effects," European Financial Management, European Financial Management Association, vol. 21(5), pages 833-866, November.
    20. Harada, Kimie & Ito, Takatoshi & Takahashi, Shuhei, 2013. "Is the Distance to Default a good measure in predicting bank failures? A case study of Japanese major banks," Japan and the World Economy, Elsevier, vol. 27(C), pages 70-82.

    More about this item

    Keywords

    European firms; Merton model; Russia–Ukraine war; Asset returns; Default risk;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecolet:v:218:y:2022:i:c:s016517652200266x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.