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) <https://jfi.pm-research.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://papers.ssrn.com/sol3/papers.cfm?abstract_id=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. (2020). 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,knitr,qpdf

Optimal pricing of assets with fixed expiry date.
Calculates the optimal price of assets (such as airline
flight seats, hotel room bookings) whose value becomes zero
after a fixed ``expiry date''.  Assumes potential customers
arrive (possibly in groups) according to a known inhomogeneous
Poisson process.  Also assumes a known time-varying elasticity
of demand (price sensitivity) function.  Uses elementary
techniques based on ordinary differential equations, solved
numerically via the method of Runge-Kutta.

Calculates the optimal price of assets (such as
airline flight seats, hotel room bookings) whose value
becomes zero after a fixed ``expiry date''.  Assumes
potential customers arrive (possibly in groups) according
to a known inhomogeneous Poisson process.  Also assumes a
known time-varying elasticity of demand (price sensitivity)
function.  Uses elementary techniques based on ordinary
differential equations, solved numerically via the method
of Runge-Kutta. Now uses the package deSolve to effect
the solution of the differential equations.