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vamc (version 0.1.0)

A Monte Carlo Valuation Framework for Variable Annuities

Description

Implementation of a Monte Carlo simulation engine for valuing synthetic portfolios of variable annuities, which reflect realistic features of common annuity contracts in practice. It aims to facilitate the development and dissemination of research related to the efficient valuation of a portfolio of large variable annuities. The main valuation methodology was proposed by Gan (2017) .

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Version

Install

install.packages('vamc')

Monthly Downloads

134

Version

0.1.0

License

GPL-2

Maintainer

Ben Feng

Last Published

October 8th, 2018

Functions in vamc (0.1.0)

covariance matrix for 5 indices

Mortality rate for male and female from ages 5 to 115

Age a VA policy specified in inPolicy from currentDate (specified in inPolicy) to targetDate. The againg scenario is given in fundScen. The time step length is specified in dT. Here we input a rather irrelevant parameter df to "hack" for a more flexible user-defined projection function.

Historical scenario dates

Historical index scenario for 5 indices over 175 months

vamc: A package for pricing a pool of variable annuities.

valuatePortfolio

Valuate a portfolio VA policies specified in each curPolicy of inPortfolio based on the simulated fund scenarios fundScen. The time step length is specified in dT and the discount rate for each period is specified in df.

5 indices for 10 scenarios over 360 months

Swap rates across 30 years

valuateOnePolicy

Valuate a VA policy specified in inPolicy based on the simulated fund scenarios fundScen. The time step length is specified in dT and the discount rate for each period is specified in df.

calcMortFactors

Calculates the mortality factors (t - 1)px q(x + t - 1) and tpx required to valuate the inPolicy. Extract gender, age (birth date & current date), valuation date (current date), and maturity date from inPolicy, mortality rates from mortTable.

Constant forward curve

Calculate numScen-by-numIndex-by-numStep fund scenarios based on given index scenarios indexScen and fund map fundMap that maps indices to funds.

A randomly generated pool of variable annuities

Simulate a 3D array, numScen by numIndex by numStep, of Black-Scholes return factors for numIndex indices in each of numStep time steps and each of numScen scenarios. Covariances among indices are specified in covMatrix. Stepsize is given is dT and interpolated discount factors are given in vDF. Random seed is optional for reproducibility.

Bootstrap discount factors from a yield curve.

genPortInception

Generate a portfolio of VA contracts at inception based on given attribute ranges and investment fund information.

Fund map for 10 funds

Age a portfolio of VA policies specified in each inPolicy of inPortfolio from currentDate (specified in inPolicy) to targetDate. The againg scenario is given in fundScen. The time step length is specified in dT. Here we input a rather irrelevant parameter df to "hack" for a more flexible user-defined projection function.