R package 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 668 articles , 1 standard article )

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  1. Bahraoui, Tarik; Kolev, Nikolai: New measure of the bivariate asymmetry (2021)
  2. Chaoubi, Ihsan; Cossette, Hélène; Marceau, Etienne; Robert, Christian Y.: Hierarchical copulas with Archimedean blocks and asymmetric between-block pairs (2021)
  3. Chen, Yiqing; White, Toby; Yuen, Kam Chuen: Precise large deviations of aggregate claims with arbitrary dependence between claim sizes and waiting times (2021)
  4. Fissler, Tobias; Hlavinová, Jana; Rudloff, Birgit: Elicitability and identifiability of set-valued measures of systemic risk (2021)
  5. Górecki, Jan; Hofert, Marius; Okhrin, Ostap: Outer power transformations of hierarchical Archimedean copulas: construction, sampling and estimation (2021)
  6. Hashemi, Farzane; Naderi, Mehrdad; Jamalizadeh, Ahad; Bekker, Andriette: A flexible factor analysis based on the class of mean-mixture of normal distributions (2021)
  7. Hintz, Erik; Hofert, Marius; Lemieux, Christiane: Normal variance mixtures: distribution, density and parameter estimation (2021)
  8. Jiang, Jie; Li, Shengjie: On complexity of multistage stochastic programs under heavy tailed distributions (2021)
  9. Koike, Takaaki; Hofert, Marius: Modality for scenario analysis and maximum likelihood allocation (2021)
  10. Li, Zihao; Luo, Ji; Yao, Jing: Convex bound approximations for sums of random variables under multivariate log-generalized hyperbolic distribution and asymptotic equivalences (2021)
  11. Salazar Flores, Yuri; Díaz Hernández, Adán: Regular variation, conditions of domain of attraction and the existence of the tail dependence function in the general dependence case: a copula approach (2021)
  12. Yang, Xinxin; Zheng, Xinghua; Chen, Jiaqi: Testing high-dimensional covariance matrices under the elliptical distribution and beyond (2021)
  13. Bernard, Carole; Kazzi, Rodrigue; Vanduffel, Steven: Range value-at-risk bounds for unimodal distributions under partial information (2020)
  14. Bianchi, Michele Leonardo; Tassinari, Gian Luca: Forward-looking portfolio selection with multivariate non-Gaussian models (2020)
  15. Bielecki, Tomasz R.; Cialenco, Igor; Pitera, Marcin; Schmidt, Thorsten: Fair estimation of capital risk allocation (2020)
  16. Bonnefont, Michel; Juillet, Nicolas: Couplings in (L^p) distance of two Brownian motions and their Lévy area (2020)
  17. Boonen, Tim J.: ( \tau)-value for risk capital allocation problems (2020)
  18. Borowska, Agnieszka; Hoogerheide, Lennart; Koopman, Siem Jan; van Dijk, Herman K.: Partially censored posterior for robust and efficient risk evaluation (2020)
  19. Ceci, Claudia; Colaneri, Katia; Frey, Rüdiger; Köck, Verena: Value adjustments and dynamic hedging of reinsurance counterparty risk (2020)
  20. Chaoubi, Ihsan; Cossette, Hélène; Gadoury, Simon-Pierre; Marceau, Etienne: On sums of two counter-monotonic risks (2020)

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