QRM

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 691 articles , 1 standard article )

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  1. Arellano-Valle, Reinaldo B.; Azzalini, Adelchi: A formulation for continuous mixtures of multivariate normal distributions (2021)
  2. Avanzi, Benjamin; Taylor, Greg; Wong, Bernard; Yang, Xinda: On the modelling of multivariate counts with Cox processes and dependent shot noise intensities (2021)
  3. Bahraoui, Tarik; Kolev, Nikolai: New measure of the bivariate asymmetry (2021)
  4. Birge, John R.; Chavez-Bedoya, L.: Portfolio optimization under the generalized hyperbolic distribution: optimal allocation, performance and tail behavior (2021)
  5. Bouzebda, Salim; Elhattab, Issam; Nemouchi, Boutheina: On the uniform-in-bandwidth consistency of the general conditional (U)-statistics based on the copula representation (2021)
  6. Cai, Jun; Wang, Ying: Optimal capital allocation principles considering capital shortfall and surplus risks in a hierarchical corporate structure (2021)
  7. Chaoubi, Ihsan; Cossette, Hélène; Marceau, Etienne; Robert, Christian Y.: Hierarchical copulas with Archimedean blocks and asymmetric between-block pairs (2021)
  8. Chen, Yiqing; White, Toby; Yuen, Kam Chuen: Precise large deviations of aggregate claims with arbitrary dependence between claim sizes and waiting times (2021)
  9. Eini, Esmat Jamshidi; Khaloozadeh, Hamid: The tail mean-variance optimal portfolio selection under generalized skew-elliptical distribution (2021)
  10. Fissler, Tobias; Hlavinová, Jana; Rudloff, Birgit: Elicitability and identifiability of set-valued measures of systemic risk (2021)
  11. Genest, Christian; Jaworski, Piotr: On the class of bivariate Archimax copulas under constraints (2021)
  12. Górecki, Jan; Hofert, Marius; Okhrin, Ostap: Outer power transformations of hierarchical Archimedean copulas: construction, sampling and estimation (2021)
  13. Hashemi, Farzane; Naderi, Mehrdad; Jamalizadeh, Ahad; Bekker, Andriette: A flexible factor analysis based on the class of mean-mixture of normal distributions (2021)
  14. Hintz, Erik; Hofert, Marius; Lemieux, Christiane: Normal variance mixtures: distribution, density and parameter estimation (2021)
  15. Jiang, Jie; Li, Shengjie: On complexity of multistage stochastic programs under heavy tailed distributions (2021)
  16. Ji, Liuyan; Tan, Ken Seng; Yang, Fan: Tail dependence and heavy tailedness in extreme risks (2021)
  17. Kithinji, Martin M.; Mwita, Peter N.; Kube, Ananda O.: Adjusted extreme conditional quantile autoregression with application to risk measurement (2021)
  18. Koike, Takaaki; Hofert, Marius: Modality for scenario analysis and maximum likelihood allocation (2021)
  19. Lin, Liang-Ching; Chen, Ying; Pan, Guangming; Spokoiny, Vladimir: Efficient and positive semidefinite pre-averaging realized covariance estimator (2021)
  20. Liu, Fangda; Wang, Ruodu: A theory for measures of tail risk (2021)

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