Skip to main content
Log in

Risk: An R Package for Financial Risk Measures

  • Published:
Computational Economics Aims and scope Submit manuscript

Abstract

A new R contributed package written by the authors is introduced. The package is believed to be the most comprehensive one to date for financial risk measures. It computes twenty six financial risk measures for any continuous distribution. The use of the package is illustrated.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

References

  • Acerbi, C., Nordio, C., & Sirtori, C. (2001). Expected shortfall as a tool for financial risk management. arXiv preprint cond-mat/0102304.

  • Agarwal, V., & Naik, N. (1999). Does gain-loss analysis outperform mean-variance analysis? evidence from portfolios of hedge funds and passive strategies. In Working Paper, London Business School.

  • Ahmadi-Javid, A. (2012). Entropic value-at-risk: A new coherent risk measure. Journal of Optimization Theory and Applications, 155, 1105–1123.

    Article  Google Scholar 

  • Artzner, P., Delbaen, F., Eber, J., & Heath, D. (1999). Coherent measures of risk. Mathematical Finance, 9, 203–228.

    Article  Google Scholar 

  • Basak, S., & Shapiro, A. (1999). Value-at-risk based risk management: Optimal policies and asset prices. In Working Paper, New York University.

  • Bellini, F., Klar, B., Müller, A., & Gianin, E. (2014). Generalized quantiles as risk measures. Insurance: Mathematics and Economics, 54, 41–48.

    Google Scholar 

  • Belzunce, F., Pinar, J., Ruiz, J., & Sordo, M. (2012). Comparison of risks based on the expected proportional shortfall. Insurance: Mathematics and Economics, 51, 292–302.

    Google Scholar 

  • Bronshtein, E., & Kurelenkova, J. (2009). Complex risk measures in portfolio optimization.

  • Embrechts, P., Kaufmann, R., & Patie, P. (2005). Strategic long-term financial risks: Single risk factors. Computational Optimization and Applications, 32, 61–90.

    Article  Google Scholar 

  • Ghalanos, A. (2015). Rugarch: Univariate GARCH models. https://CRAN.R-project.org/package=rugarch. R package version 1.3.6.

  • Goulet, V., Auclair, S., Dutang, C., Milhaud, X., Ouellet, T., Pouliot, L., & Pigeon, M. (2017). Actuar: Actuarial Functions and Heavy Tailed Distributions. https://CRAN.R-project.org/package=actuar. R package version 2.1.1.

  • Jakob, K., Fischer, M., & Kolb, S. (2016). crp.CSFP: CreditRisk+ Portfolio Model. https://CRAN.R-project.org/package=crp.CSFP. R package version 2.0.2.

  • Kaplan, P., & Knowles, J. (2004). Kappa: A Generalized Downside Risk-Adjusted Performance Measure.

  • Kou, S., Peng, X., & Heyde, C. (2013). External risk measures and basel accords. Mathematics of Operations Research, 38, 393–417.

    Article  Google Scholar 

  • Longin, F. (2001). Beyond the VaR. Journal of Derivatives, 8, 36–48.

    Article  Google Scholar 

  • Luce, R. (1980). Several possible measures of risk. Theory and Decision, 12, 217–228.

    Article  Google Scholar 

  • Luethi, D., & Breymann, W. (2016). ghyp: A package on generalized hyperbolic distribution and its special cases. https://CRAN.R-project.org/package=ghyp. R package version 1.5.7.

  • McNeil, A., Frey, R., & Embrecht, P. (2015). Quantitative risk management: Concepts, techniques and tools. Princeton: Princeton University Press.

    Google Scholar 

  • Nadarajah, S., & Chan, S. (2016). Extreme events in finance: A handbook of extreme value theory and its applications, chapter estimation methods for value at risk. New York: Wiley.

  • Nadarajah, S., & Chan, S. (2017). Risk: Computes 26 financial risk measures for any continuous distribution, https://CRAN.R-project.org/package=Risk. R package version 1.0.

  • Nadarajah, S., Chan, S., & Afuecheta, E. (2013). VaRES: Computes Value at Risk and Expected Shortfall for Over 100 Parametric Distributions. https://CRAN.R-project.org/package=VaRES. R package version 1.0.

  • Nadarajah, S., Zhang, B., & Chan, S. (2014). Estimation methods for expected shortfall. Quantitative Finance, 14, 271–291.

    Article  Google Scholar 

  • Newey, W., & Powell, J. (1987). Asymmetric least squares estimation and testing. Econometrica, 55, 819–847.

    Article  Google Scholar 

  • Peterson, B., et al. (2014). PerformanceAnalytics: Econometric Tools for Performance and Risk Analysis. https://CRAN.R-project.org/package=PerformanceAnalytics. R package version 1.4.3541.

  • Pfaff, B. et al. (2016). QRM: Provides R-Language code to examine quantitative risk management concepts. https://CRAN.R-project.org/package=QRM. R package version 0.4.13.

  • Pfaff, B., McNeil, A., & Stephenson, A. (2012). evir: Extreme values in R. https://CRAN.R-project.org/package=evir. R package version 1.7.3.

  • R Development Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. http://www.R-project.org. ISBN 3-900051-07-0.

  • Renyi, A. (1961). In Proceedings of the fourth Berkeley Symposium on Mathematics, Statistics and Probability, chapter on measures of information and entropy. Berkeley: University of California.

  • Rmetrics Core Team, Wuertz, D., Setz, T., & Chalabi, Y. (2014a). fAssets: Rmetrics–analysing and modelling financial assets. https://CRAN.R-project.org/package=fAssets. R package version 3011.83.

  • Rmetrics Core Team, Wuertz, D., Setz, T., & Chalabi, Y. (2014b). fPortfolio: Rmetrics–portfolio selection and optimization. https://CRAN.R-project.org/package=fPortfolio. R package version 3011.81.

  • Rollinger, T., & Hoffman, S. (2013). Sortino ratio: A better measure of risk. Risk Management, 40–42.

  • Sarin, R. (1987). Some extensions of Luce’s measures of risk. Theory and Decision, 22, 125–141.

    Article  Google Scholar 

  • Shadwick, W., & Keating, C. (2002). A Universal performance measure. Journal of Performance Measurement.

  • Shannon, C. (1948). A mathematical theory of communication. Bell Systems Technical Journal, 27(379–423), 623–656.

    Article  Google Scholar 

  • Shannon, C. (1951). Prediction and entropy of printed english. Bell Systems Technical Journal, 30, 50–64.

    Article  Google Scholar 

  • Stone, B. (1973). A general class of three-parameter risk measures. The Journal of Finance, 28, 675–685.

    Article  Google Scholar 

  • Wang, S. (1998). An Actuarial index of the right-tail risk. North American Actuarial Journal, 2, 88–101.

    Article  Google Scholar 

  • Wittmann, A. (2009). CreditMetrics: Functions for calculating the creditmetrics risk model. https://CRAN.R-project.org/package=CreditMetrics. R package version 0.0.2.

  • Wuertz, D. (2013). fExtremes: Rmetrics–Extreme Financial market data. https://CRAN.R-project.org/package=fExtremes. R package version 3010.81.

  • Yamai, Y., & Yoshiba, T. (2002). Comparative analyses of expected shortfall and value-at-risk: Their estimation error, decomposition, and optimization. Monetary and Economic Studies, 20, 87–121.

    Google Scholar 

Download references

Acknowledgements

The authors would like to thank the two referees and the Editor for careful reading and comments which greatly improved the paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Saralees Nadarajah.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chan, S., Nadarajah, S. Risk: An R Package for Financial Risk Measures. Comput Econ 53, 1337–1351 (2019). https://doi.org/10.1007/s10614-018-9806-9

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10614-018-9806-9

Keywords

Navigation