IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v19y1999i6p1205-1214.html
   My bibliography  Save this article

On Modeling Correlated Random Variables in Risk Assessment

Author

Listed:
  • Charles N. Haas

Abstract

Monte Carlo methods in risk assessment are finding increasingly widespread application. With the recognition that inputs may be correlated, the incorporation of such correlations into the simulation has become important. Most implementations rely upon the method of Iman and Conover for generating correlated random variables. In this work, alternative methods using copulas are presented for deriving correlated random variables. It is further shown that the particular algorithm or assumption used may have a substantial effect on the output results, due to differences in higher order bivariate moments.

Suggested Citation

  • Charles N. Haas, 1999. "On Modeling Correlated Random Variables in Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 19(6), pages 1205-1214, December.
    • Handle: RePEc:wly:riskan:v:19:y:1999:i:6:p:1205-1214
    DOI: 10.1111/j.1539-6924.1999.tb01139.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1539-6924.1999.tb01139.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1539-6924.1999.tb01139.x?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
    ---><---

    References listed on IDEAS

    as
    1. Dale Hattis & David E. Burmaster, 1994. "Assessment of Variability and Uncertainty Distributions for Practical Risk Analyses," Risk Analysis, John Wiley & Sons, vol. 14(5), pages 713-730, October.
    2. Mohamed N. Jouini & Robert T. Clemen, 1996. "Copula Models for Aggregating Expert Opinions," Operations Research, INFORMS, vol. 44(3), pages 444-457, June.
    3. Andrew E. Smith & P. Barry Ryan & John S. Evans, 1992. "The Effect of Neglecting Correlations When Propagating Uncertainty and Estimating the Population Distribution of Risk," Risk Analysis, John Wiley & Sons, vol. 12(4), pages 467-474, December.
    4. Charles N. Haas, 1997. "Importance of Distributional Form in Characterizing Inputs to Monte Carlo Risk Assessments," Risk Analysis, John Wiley & Sons, vol. 17(1), pages 107-113, February.
    5. John Bukowski & Leo Korn & Daniel Wartenberg, 1995. "Correlated Inputs in Quantitative Risk Assessment: The Effects of Distributional Shape," Risk Analysis, John Wiley & Sons, vol. 15(2), pages 215-219, April.
    6. David E. Burmaster & Paul D. Anderson, 1994. "Principles of Good Practice for the Use of Monte Carlo Techniques in Human Health and Ecological Risk Assessments," Risk Analysis, John Wiley & Sons, vol. 14(4), pages 477-481, August.
    7. Jennifer Brainard & David E. Burmaster, 1992. "Bivariate Distributions for Height and Weight of Men and Women in the United States," Risk Analysis, John Wiley & Sons, vol. 12(2), pages 267-275, June.
    8. Joe, H., 1993. "Parametric Families of Multivariate Distributions with Given Margins," Journal of Multivariate Analysis, Elsevier, vol. 46(2), pages 262-282, August.
    9. Edward Frees & Emiliano Valdez, 1998. "Understanding Relationships Using Copulas," North American Actuarial Journal, Taylor & Francis Journals, vol. 2(1), pages 1-25.
    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. Y. Malevergne & D. Sornette, 2003. "Testing the Gaussian copula hypothesis for financial assets dependences," Quantitative Finance, Taylor & Francis Journals, vol. 3(4), pages 231-250.
    2. A. E. Ades & G. Lu, 2003. "Correlations Between Parameters in Risk Models: Estimation and Propagation of Uncertainty by Markov Chain Monte Carlo," Risk Analysis, John Wiley & Sons, vol. 23(6), pages 1165-1172, December.
    3. Edouard Kujawski, 2002. "Selection of technical risk responses for efficient contingencies," Systems Engineering, John Wiley & Sons, vol. 5(3), pages 194-212.
    4. Xu, Shiyun & Shao, Menglin & Qiao, Wenxuan & Shang, Pengjian, 2018. "Generalized AIC method based on higher-order moments and entropy of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 1127-1138.
    5. Jorge A. Sefair & Oscar Guaje & Andrés L. Medaglia, 2021. "A column-oriented optimization approach for the generation of correlated random vectors," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(3), pages 777-808, September.
    6. David Corredor-Montenegro & Nicolás Cabrera & Raha Akhavan-Tabatabaei & Andrés L. Medaglia, 2021. "On the shortest $$\alpha$$ α -reliable path problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 287-318, April.

    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. Robert T. Clemen & Terence Reilly, 1999. "Correlations and Copulas for Decision and Risk Analysis," Management Science, INFORMS, vol. 45(2), pages 208-224, February.
    2. Maged M. Hamed & Philip B. Bedient, 1997. "On the Effect of Probability Distributions of Input Variables in Public Health Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 17(1), pages 97-105, February.
    3. Per Sander & Bo Bergbäck & Tomas Öberg, 2006. "Uncertain Numbers and Uncertainty in the Selection of Input Distributions—Consequences for a Probabilistic Risk Assessment of Contaminated Land," Risk Analysis, John Wiley & Sons, vol. 26(5), pages 1363-1375, October.
    4. Robert T. Clemen & Gregory W. Fischer & Robert L. Winkler, 2000. "Assessing Dependence: Some Experimental Results," Management Science, INFORMS, vol. 46(8), pages 1100-1115, August.
    5. Y. Malevergne & D. Sornette, 2003. "Testing the Gaussian copula hypothesis for financial assets dependences," Quantitative Finance, Taylor & Francis Journals, vol. 3(4), pages 231-250.
    6. David E. Burmaster, 1998. "Lognormal Distributions for Skin Area as a Function of Body Weight," Risk Analysis, John Wiley & Sons, vol. 18(1), pages 27-32, February.
    7. J. Rosco & Harry Joe, 2013. "Measures of tail asymmetry for bivariate copulas," Statistical Papers, Springer, vol. 54(3), pages 709-726, August.
    8. Su, Jianxi & Furman, Edward, 2017. "Multiple risk factor dependence structures: Copulas and related properties," Insurance: Mathematics and Economics, Elsevier, vol. 74(C), pages 109-121.
    9. Nguyen, Tristan & Molinari, Robert Danilo, 2009. "Quantifizierung von Abhängigkeitsstrukturen zwischen Risiken in Versicherungsunternehmen," German Risk and Insurance Review (GRIR), University of Cologne, Department of Risk Management and Insurance, vol. 5(2), pages 28-52.
    10. David E. Burmaster & Donald M. Murray, 1998. "A Trivariate Distribution for the Height, Weight, and Fat of Adult Men," Risk Analysis, John Wiley & Sons, vol. 18(4), pages 385-389, August.
    11. Tianyang Wang & James S. Dyer, 2012. "A Copulas-Based Approach to Modeling Dependence in Decision Trees," Operations Research, INFORMS, vol. 60(1), pages 225-242, February.
    12. Roman Matkovskyy, 2019. "Extremal Economic (Inter)Dependence Studies: A Case of the Eastern European Countries," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(3), pages 667-698, September.
    13. Jianxi Su & Edward Furman, 2016. "Multiple risk factor dependence structures: Copulas and related properties," Papers 1610.02126, arXiv.org.
    14. David E. Burmaster, 1998. "Lognormal Distributions for Total Water Intake and Tap Water Intake by Pregnant and Lactating Women in the United States," Risk Analysis, John Wiley & Sons, vol. 18(2), pages 215-219, April.
    15. Genest, Christian & Rémillard, Bruno & Beaudoin, David, 2009. "Goodness-of-fit tests for copulas: A review and a power study," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 199-213, April.
    16. Ahmed Ghorbel & Wajdi Hamma & Anis Jarboui, 2017. "Dependence between oil and commodities markets using time-varying Archimedean copulas and effectiveness of hedging strategies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(9), pages 1509-1542, July.
    17. Naifar, Nader, 2012. "Modeling the dependence structure between default risk premium, equity return volatility and the jump risk: Evidence from a financial crisis," Economic Modelling, Elsevier, vol. 29(2), pages 119-131.
    18. Johan Braeken & Francis Tuerlinckx & Paul Boeck, 2007. "Copula Functions for Residual Dependency," Psychometrika, Springer;The Psychometric Society, vol. 72(3), pages 393-411, September.
    19. Smith, Michael Stanley, 2023. "Implicit Copulas: An Overview," Econometrics and Statistics, Elsevier, vol. 28(C), pages 81-104.
    20. Martí Nadal & Vikas Kumar & Marta Schuhmacher & José L. Domingo, 2008. "Applicability of a Neuroprobabilistic Integral Risk Index for the Environmental Management of Polluted Areas: A Case Study," Risk Analysis, John Wiley & Sons, vol. 28(2), pages 271-286, April.

    More about this item

    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:wly:riskan:v:19:y:1999:i:6:p:1205-1214. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    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.