Backtesting Simple Asset Allocation Strategies
Easy and quick testing of customizable asset allocation strategies.
Users can rely on their own data, or have the package automatically
download data from Yahoo Finance (<https://finance.yahoo.com/>). Several
pre-loaded portfolios with data are available, including some which are
discussed in Faber (2015, ISBN:9780988679924).

PerformanceAnalytics, quantmod, RiskPortfolios, xts, zoo,
NMOF, riskParityPortfolio

Estimating Asset Correlations from Default Data
Maximilian Nagl [aut,cre], Yevhen Havrylenko [aut], Marius Pfeuffer [aut], Kevin Jakob [aut], Matthias Fischer [aut], Daniel Roesch [aut]
Functions for the estimation of intra- and inter-cohort correlations in the Vasicek credit portfolio model. For intra-cohort correlations, the package covers the two method of moments estimators of Gordy (2000) <doi:10.1016/S0378-4266(99)00054-0>, the method of moments estimator of Lucas (1995) <doi:10.3905/jfi.1995.408124> and a Binomial approximation extension of this approach. Moreover, the maximum likelihood estimators of Gordy and Heitfield (2010) <http://elsa.berkeley.edu/~mcfadden/e242_f03/heitfield.pdf> and Duellmann and Gehde-Trapp (2004) <http://hdl.handle.net/10419/19729> are implemented. For inter-cohort correlations, the method of moments estimator of Bluhm and Overbeck (2003) <doi:10.1007/978-3-642-59365-9_2>/Bams et al. (2016) <https://ssrn.com/abstract=2676595> is provided and the maximum likelihood estimators comprise the approaches of Gordy and Heitfield (2010)/Kalkbrener and Onwunta (2010) <ISBN: 978-1906348250> and Pfeuffer et al. (2018). Bootstrap and Jackknife procedures for bias correction are included as well as the method of moments estimator of Frei and Wunsch (2018) <doi:10.21314/JCR.2017.231> for auto-correlated time series.
VineCopula, mvtnorm, bootstrap, stats4, boot, numDeriv,
mvQuad, ggplot2, methods, Rdpack, knitr,grid

Functions for the estimation of intra- and inter-cohort correlations in the Vasicek credit portfolio model. For intra-cohort correlations, the package covers the two method of moments estimators of Gordy (2000) <doi:10.1016/S0378-4266(99)00054-0>, the method of moments estimator of Lucas (1995) <http://jfi.iijournals.com/content/4/4/76> and a Binomial approximation extension of this approach. Moreover, the maximum likelihood estimators of Gordy and Heitfield (2010) <http://elsa.berkeley.edu/~mcfadden/e242_f03/heitfield.pdf> and Duellmann and Gehde-Trapp (2004) <http://hdl.handle.net/10419/19729> are implemented. For inter-cohort correlations, the method of moments estimator of Bluhm and Overbeck (2003) <doi:10.1007/978-3-642-59365-9_2>/Bams et al. (2016) <https://ssrn.com/abstract=2676595> is provided and the maximum likelihood estimators comprise the approaches of Gordy and Heitfield (2010)/Kalkbrener and Onwunta (2010) <ISBN: 978-1906348250> and Pfeuffer et al. (2018). Bootstrap and Jackknife procedures for bias correction are included as well as the method of moments estimator of Frei and Wunsch (2018) <doi:10.21314/JCR.2017.231> for auto-correlated time series.
VineCopula, mvtnorm, boot, numDeriv, mvQuad, ggplot2, Rdpack