R package Dowd: Functions Ported from ’MMR2’ Toolbox Offered in Kevin Dowd’s Book Measuring Market Risk. ’Kevin Dowd’s’ book Measuring Market Risk is a widely read book in the area of risk measurement by students and practitioners alike. As he claims, ’MATLAB’ indeed might have been the most suitable language when he originally wrote the functions, but, with growing popularity of R it is not entirely valid. As ’Dowd’s’ code was not intended to be error free and were mainly for reference, some functions in this package have inherited those errors. An attempt will be made in future releases to identify and correct them. ’Dowd’s’ original code can be downloaded from It should be noted that ’Dowd’ offers both ’MMR2’ and ’MMR1’ toolboxes. Only ’MMR2’ was ported to R. ’MMR2’ is more recent version of ’MMR1’ toolbox and they both have mostly similar function. The toolbox mainly contains different parametric and non parametric methods for measurement of market risk as well as backtesting risk measurement methods.

References in zbMATH (referenced in 32 articles )

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  1. Chang, Tsung-Sheng; Tone, Kaoru; Wu, Chen-Hui: Nested dynamic network data envelopment analysis models with infinitely many decision making units for portfolio evaluation (2021)
  2. Seyfi, Seyed Mohammad Sina; Sharifi, Azin; Arian, Hamidreza: Portfolio value-at-risk and expected-shortfall using an efficient simulation approach based on Gaussian mixture model (2021)
  3. Huo, Yanli; Xu, Chunhui; Shiina, Takayuki: Modeling and solving portfolio selection problems based on PVaR (2020)
  4. Luo, Sheng-Feng: Dynamic mean-variance portfolios with risk budget (2020)
  5. Sousa, J. Beleza; Esquível, Manuel L.; Gaspar, Raquel M.: Pulled-to-par returns for zero-coupon bonds historical simulation value at risk (2020)
  6. Zhu, Bangzhu; Ye, Shunxin; He, Kaijian; Chevallier, Julien; Xie, Rui: Measuring the risk of European carbon market: an empirical mode decomposition-based value at risk approach (2019)
  7. Faria, Adriano; Almeida, Caio: A hybrid spline-based parametric model for the yield curve (2018)
  8. Scheller, Felix; Auer, Benjamin R.: How does the choice of Value-at-Risk estimator influence asset allocation decisions? (2018)
  9. Xu, Yu-Hong: Robust valuation, arbitrage ambiguity and profit & loss analysis (2018)
  10. Mitra, Sovan: Efficient option risk measurement with reduced model risk (2017)
  11. Nie, Chun-Xiao: Dynamics of cluster structure in financial correlation matrix (2017)
  12. Vilar-Zanón, José L.; Vilar, Eduardo; Heras, Antonio: Online product returns risk assessment and management (2017)
  13. Lönnbark, Carl: Approximation methods for multiple period value at risk and expected shortfall prediction (2016)
  14. Postek, Krzysztof; den Hertog, Dick; Melenberg, Bertrand: Computationally tractable counterparts of distributionally robust constraints on risk measures (2016)
  15. Spierdijk, Laura: Confidence intervals for ARMA-GARCH value-at-risk: the case of heavy tails and skewness (2016)
  16. Korn, Ralf; Pupashenko, Mykhailo: A new variance reduction technique for estimating value-at-risk (2015)
  17. Calabrese, Raffaella; Osmetti, Silvia Angela: Modelling small and medium enterprise loan defaults as rare events: the generalized extreme value regression model (2013)
  18. Mitra, Sovan; Date, Paresh; Mamon, Rogemar; Wang, I-Chieh: Pricing and risk management of interest rate swaps (2013)
  19. Stoyanov, Stoyan V.; Rachev, Svetlozar T.; Fabozzi, Frank J.: Sensitivity of portfolio VaR and CVaR to portfolio return characteristics (2013)
  20. Alonso-Cifuentes, Julio César; Serna-Cortés, Manuel: Intraday-patterns in the colombian exchange market index and var: evaluation of different approaches (2012)

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