QRM: Provides R-language Code to Examine Quantitative Risk Management Concepts. This package is designed to accompany the book Quantitative Risk Management: Concepts, Techniques and Tools by Alexander J. McNeil, Rudiger Frey, and Paul Embrechts: This book is primarily a textbook for courses in quantitative risk management (QRM) aimed at advanced undergraduate or graduate students and professionals from the financial industry. The book has a secondary function as a reference text for risk professionals interested in a clear and concise treatment of concepts and techniques used on practice. Different courses can be devised based on different chapters of the book: market risk, credit risk, operational risk, risk-measurement and aggregation concepts, risk-management techniques for financial econometricians. Material from various chapters could be used as interesting examples for statistics courses on subjects like multivariate analysis, time series analysis and generalized linear modelling.

References in zbMATH (referenced in 250 articles , 1 standard article )

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  1. Allen, D.E.; Powell, R.J.; Singh, A.K.: Take it to the limit: innovative CVaR applications to extreme credit risk measurement (2016)
  2. Artikis, Panagiotis T.: Deriving advantage over a crisis by incorporating a new class of stochastic models for risk control operations (2016)
  3. Asimit, Alexandru V.; Gerrard, Russell; Hou, Yanxi; Peng, Liang: Tail dependence measure for examining financial extreme co-movements (2016)
  4. Bae, Taehan; Iscoe, Ian: On the limit of conditional Spearman’s rho under the common factor model (2016)
  5. Bignozzi, Valeria; Mao, Tiantian; Wang, Bin; Wang, Ruodu: Diversification limit of quantiles under dependence uncertainty (2016)
  6. Das, Bikramjit; Ghosh, Souvik: Detecting tail behavior: mean excess plots with confidence bounds (2016)
  7. Durante, Fabrizio; Girard, Stéphane; Mazo, Gildas: Marshall-Olkin type copulas generated by a global shock (2016)
  8. Embrechts, Paul; Jakobsons, Edgars: Dependence uncertainty for aggregate risk: examples and simple bounds (2016)
  9. Ignatieva, Katja; Trück, Stefan: Modeling spot price dependence in Australian electricity markets with applications to risk management (2016)
  10. Landsman, Zinoviy; Makov, Udi; Shushi, Tomer: Multivariate tail conditional expectation for elliptical distributions (2016)
  11. Lehmann, Christoph; Tillich, Daniel: Consensus information and consensus rating. A note on methodological problems of rating aggregation (2016)
  12. Liao, Xin; Peng, Liang; Peng, ZuoXiang; Zheng, YanTing: Dynamic bivariate normal copula (2016)
  13. Li, Yunxian; Tang, Niansheng; Jiang, Xuejun: Bayesian approaches for analyzing earthquake catastrophic risk (2016)
  14. Mazo, Gildas; Girard, Stéphane; Forbes, Florence: A flexible and tractable class of one-factor copulas (2016)
  15. Mikosch, Thomas: Book review of: A. J. McNeil et al., Quantitative risk management. Concepts, techniques and tools. Rev. ed. (2016)
  16. Nešlehová, Johanna G.: Book review of: A. J. McNeil et al., Quantitative risk management. Concepts, techniques and tools. (2016)
  17. Ratovomirija, Gildas: On mixed Erlang reinsurance risk: aggregation, capital allocation and default risk (2016)
  18. Samanthi, Ranadeera Gamage Madhuka; Wei, Wei; Brazauskas, Vytaras: Ordering gini indexes of multivariate elliptical risks (2016)
  19. Tankov, Peter: Tails of weakly dependent random vectors (2016)
  20. Tian, Yuzhu; Zhu, Qianqian; Tian, Maozai: Estimation of linear composite quantile regression using EM algorithm (2016)

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