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.
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References in zbMATH (referenced in 398 articles , 1 standard article )
Showing results 1 to 20 of 398.
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- Dalessandro, Antonio; Peters, Gareth W.: Tensor approximation of generalized correlated diffusions and functional copula operators (2018)
- Damian, Camilla; Eksi, Zehra; Frey, Rüdiger: EM algorithm for Markov chains observed via Gaussian noise and point process information: theory and case studies (2018)
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- Bee, M.: Density approximations and VaR computation for compound Poisson-lognormal distributions (2017)
- Belzile, Léo R.; Nešlehová, Johanna G.: Extremal attractors of Liouville copulas (2017)
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- Cambou, Mathieu; Hofert, Marius; Lemieux, Christiane: Quasi-random numbers for copula models (2017)
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- Chen, Yiqing; Yuan, Zhongyi: A revisit to ruin probabilities in the presence of heavy-tailed insurance and financial risks (2017)
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- Goldberg, Lisa R.; Mahmoud, Ola: Drawdown: from practice to theory and back again (2017)
- Gribkova, N.; Zitikis, R.: Statistical foundations for assessing the difference between the classical and weighted-Gini betas (2017)