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Risk and value at risk

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  • Stambaugh, Fred

Abstract

Increasingly complicated tools known as financial derivatives have been introduced in recent times to manage the market risk arising from floating exchange rates. The rapid development of the derivatives markets has in turn introduced new risks into the business of finance - witness the highly-publicised trading losses at Metallgesellschaft and Procter and Gamble. A principal method for measuring and reporting market risk in the portfolios of banks and their clients is 'value at risk' (VaR). Fred Stambaugh explains the concept of 'value at risk' and describes three principal approaches to calculating it - correlation matrix, historical simulation and Monte Carlo simulation; they are alternatives, not competitors. As well as setting out their uses, he considers those situations that go beyond 'value at risk', i.e. dire events that lie beyond the confidence level of VaR. Techniques for portfolio stress testing are discussed.

Suggested Citation

  • Stambaugh, Fred, 1996. "Risk and value at risk," European Management Journal, Elsevier, vol. 14(6), pages 612-621, December.
    • Handle: RePEc:eee:eurman:v:14:y:1996:i:6:p:612-621
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    1. Patra, Pradipta & Kumar, U. Dinesh & Nowicki, David R. & Randall, Wesley S., 2019. "Effective management of performance-based contracts for sustainment dominant systems," International Journal of Production Economics, Elsevier, vol. 208(C), pages 369-382.
    2. Hasna Fadhila & Nora Amelda Rizal, 2013. "Analysis of Risk using Value at Risk (VaR) After Crisis in 2008 Study in Stocks of Bank Mandiri, Bank BRI and Bank BNI in 2009-2011," Information Management and Business Review, AMH International, vol. 5(8), pages 394-400.
    3. González-Díaz, Julio & González-Rodríguez, Brais & Leal, Marina & Puerto, Justo, 2021. "Global optimization for bilevel portfolio design: Economic insights from the Dow Jones index," Omega, Elsevier, vol. 102(C).
    4. Stavros Stavroyiannis & Leonidas Zarangas, 2013. "Out of Sample Value-at-Risk and Backtesting with the Standardized Pearson Type-IV Skewed Distribution," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 60(2), pages 231-247, April.
    5. Calvo, Clara & Ivorra, Carlos & Liern, Vicente, 2015. "Finding socially responsible portfolios close to conventional ones," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 52-63.
    6. Friedrich, Stefan & Paul, Carola & Brandl, Susanne & Biber, Peter & Messerer, Katharina & Knoke, Thomas, 2019. "Economic impact of growth effects in mixed stands of Norway spruce and European beech – A simulation based study," Forest Policy and Economics, Elsevier, vol. 104(C), pages 65-80.
    7. Vlad-Cosmin Bulai & Alexandra Horobet & Oana Cristina Popovici & Lucian Belascu & Sofia Adriana Dumitrescu, 2021. "A VaR-Based Methodology for Assessing Carbon Price Risk across European Union Economic Sectors," Energies, MDPI, vol. 14(24), pages 1-21, December.
    8. Fabian H. Härtl & Sebastian Höllerl & Thomas Knoke, 2017. "A new way of carbon accounting emphasises the crucial role of sustainable timber use for successful carbon mitigation strategies," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 22(8), pages 1163-1192, December.
    9. Stavroyiannis, S. & Makris, I. & Nikolaidis, V. & Zarangas, L., 2012. "Econometric modeling and value-at-risk using the Pearson type-IV distribution," International Review of Financial Analysis, Elsevier, vol. 22(C), pages 10-17.
    10. Sang Hoon Kang & Seong-Min Yoon, 2009. "Value-at-Risk Analysis for Asian Emerging Markets: Asymmetry and Fat Tails in Returns Innovation," Korean Economic Review, Korean Economic Association, vol. 25, pages 387-411.
    11. Cabedo Semper, J. David & Moya Clemente, Ismael, 2003. "Value at risk calculation through ARCH factor methodology: Proposal and comparative analysis," European Journal of Operational Research, Elsevier, vol. 150(3), pages 516-528, November.
    12. Larsen, Ryan A. & Leatham, David J. & Mjelde, James W. & Wolfley, Jared L., 2008. "Geographical Diversification: An Application of Copula Based CVaR," 2008 Agricultural and Rural Finance Markets in Transition, September 25-26, 2008, Kansas City, Missouri 119533, Regional Research Committee NC-1014: Agricultural and Rural Finance Markets in Transition.
    13. Härtl, Fabian & Knoke, Thomas, 2014. "The influence of the oil price on timber supply," Forest Policy and Economics, Elsevier, vol. 39(C), pages 32-42.
    14. Baroni, Michel & Barthélémy, Fabrice & Mokrane, Mahdi, 2006. "Monte Carlo Simulations versus DCF in Real Estate Portfolio Valuation," ESSEC Working Papers DR 06002, ESSEC Research Center, ESSEC Business School.

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