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Scenario Simulation: Theory and methodology (*)


Author Info

  • Farshid Jamshidian

    (New Products and Strategic Trading, Sakura Global Capital, 42 New Broad Street, London EC2M 1JX, United Kingdom)

  • Yu Zhu

    (Risk Assessment and Control, Sakura Global Capital, 65 East 55 Street, New York, NY 10022, USA)


This paper presents a new simulation methodology for quantitative risk analysis of large multi-currency portfolios. The model discretizes the multivariate distribution of market variables into a limited number of scenarios. This results in a high degree of computational efficiency when there are many sources of risk and numerical accuracy dictates a large Monte Carlo sample. Both market and credit risk are incorporated. The model has broad applications in financial risk management, including value at risk. Numerical examples are provided to illustrate some of its practical applications.

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Bibliographic Info

Article provided by Springer in its journal Finance and Stochastics.

Volume (Year): 1 (1996)
Issue (Month): 1 ()
Pages: 43-67

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Handle: RePEc:spr:finsto:v:1:y:1996:i:1:p:43-67

Note: received: February 1996; final revision received: June 1996
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Keywords: Risk analysis · Monte Carlo studies · approximations to distributions;

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Cited by:
  1. Arthur Charpentier & Christophe Villa, 2010. "Generating Yield Curve Stress-Scenarios," Working Papers hal-00550582, HAL.
  2. Agata Gemzik-Salwach, 2012. "The Use Of A Value At Risk Measure For The Analysis Of Bank Interest Margins," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 8(4), pages 15-29, February.
  3. Christophe PÉRIGNON & Christophe VILLA, 2002. "Permanent and Transitory Factors Affecting the Dynamics of the Term Structure of Interest Rates," FAME Research Paper Series rp53, International Center for Financial Asset Management and Engineering.
  4. Kostas Andriosopoulos & Nikos Nomikos, 2012. "Risk management in the energy markets and Value-at-Risk modelling: a Hybrid approach," RSCAS Working Papers 2012/47, European University Institute.
  5. Laruent Barras, 2005. "International Conditional Asset Allocation under Real Time Uncertrainty," FAME Research Paper Series rp153, International Center for Financial Asset Management and Engineering.
  6. Christensen, Jens H.E. & Lopez, Jose A. & Rudebusch, Glenn D., 2013. "A probability-based stress test of Federal Reserve assets and income," Working Paper Series 2013-38, Federal Reserve Bank of San Francisco.
  7. Roberta Fiori & Simonetta Iannotti, 2006. "Scenario Based Principal Component Value-at-Risk: an Application to Italian Banks' Interest Rate Risk Exposure," Temi di discussione (Economic working papers) 602, Bank of Italy, Economic Research and International Relations Area.
  8. Fabio Trojani, 2007. "Accurate Short-Term Yield Curve Forecasting using Functional Gradient Descent," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 5(4), pages 591-623, Fall.
  9. Andrea Beltratti & Andrea Consiglio & Stavros A. Zenios, 1998. "Scenario Modeling for the Management of International Bond Portfolios," Center for Financial Institutions Working Papers 98-20, Wharton School Center for Financial Institutions, University of Pennsylvania.
  10. Michael S. Gibson & Matthew Pritsker, 2000. "Improving grid-based methods for estimating value at risk of fixed-income portfolios," Finance and Economics Discussion Series 2000-25, Board of Governors of the Federal Reserve System (U.S.).
  11. Matthias Fengler & Wolfgang Härdle & Christophe Villa, 2003. "The Dynamics of Implied Volatilities: A Common Principal Components Approach," Review of Derivatives Research, Springer, vol. 6(3), pages 179-202, October.
  12. Fabio Trojani & Francesco Audrino, 2005. "Accurate Yield Curve Scenarios Generation using Functional Gradient Descent," Computing in Economics and Finance 2005 14, Society for Computational Economics.
  13. Karoline Terán Matamoros & Oscar Molina Tejerina, 2005. "Simulación eficiente del valor de riesgo de un portafolio de acciones del IPSA: Un análisis de componentes principales," Investigación & Desarrollo 0205, Universidad Privada Boliviana, revised Mar 2005.


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