Pricing of Variable Annuities

Pricing of variable annuity life insurance contracts by means of Monte Carlo methods. Monte Carlo is used to price the contract in case the policyholder cannot surrender while Least Squares Monte Carlo is used if the insured can surrender. This package implements the pricing framework and algorithm described in Bacinello et al. (2011) . It also implements the state-dependent fee structure discussed in Bernard et al. (2014) .


Valuer aims at pricing a type of life insurance contract called variable annuity. The package implements the valuation framework and algorithms described in BMOP2011 where Monte Carlo methods are adapted to the life insurance case. It's written using R6 and comes with classes which describe the variable annuity contracts and other classes, called pricing engines, which are used to price those contracts.

The following code prices a 10 years VA with GMAB guarantee by means of a pricing engine which models the underlying fund as a geometric Brownian motion. Please check the introductory vignette for an explanation of this example and a description of the package structure.

library(valuer)
#> Loading required package: orthopolynom
#> Loading required package: polynom
 
rate <- constant_parameters$new(0.01)
 
premium <- 100
rollup <- payoff_rollup$new(premium, rate)
 
#Ten years time-line
begin <- timeDate::timeDate("2016-01-01")
end <- timeDate::timeDate("2025-12-31")
 
#Age of the policyholder.
age <- 60
# A constant fee of 4% per year (365 days)
fee <- constant_parameters$new(0.04)
 
#Barrier for a state-dependent fee. The fee will be applied only if
#the value of the account is below the barrier
barrier <- Inf
#Withdrawal penalty applied in case the insured surrenders the contract
#It is a constant penalty in this case
penalty <- penalty_class$new(type = 1, 0.01)
#Sets up the contract with GMAB guarantee
contract <- GMAB$new(rollup, t0 = begin, t = end, age = age, fee = fee, barrier = barrier, penalty = penalty)
#Interest rate
r <- constant_parameters$new(0.03)
#Initial value of the underlying fund
spot <- 100
#Volatility
vol <- constant_parameters$new(0.2)
#Dividend rate
div <- constant_parameters$new(0.0)
#Gatherer for the MC point estimates
the_gatherer <- mc_gatherer$new()
#Number of paths to simulate
no_of_paths <- 1e3
 
#Sets up the pricing engine specifying the va_contract, the interest rate
#the parameters of the Weibull intensity of mortality, the initial fund
#value, the volatility and dividends rate
engine <- va_bs_engine$new(contract, r, c1=90.43, c2=10.36, spot,
volatility=vol, dividends=div)
 
#Estimates the contract value by means of the static approach.
 
engine$do_static(the_gatherer, no_of_paths)
the_gatherer$get_results()
#>       mean        se
#> 1 92.12345 0.9508671

Valuer is currently on release 1.1.0

Get the development release from GitHub:

# install.packages("devtools")
 
devtools::install_github("IvanZoccolan/valuer")

BMOP2011 - Bacinello A.R., Millossovich P., Olivieri A. e Pitacco E. "Variable annuities: unifying valuation approach." In: Insurance: Mathematics andEconomics 49 (2011), pp. 285-297.

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install.packages("valuer")

1.1.1 by Ivan Zoccolan, 2 months ago


http://github.com/IvanZoccolan/valuer


Report a bug at http://github.com/IvanZoccolan/valuer/issues


Browse source code at https://github.com/cran/valuer


Authors: Ivan Zoccolan [aut, cre]


Documentation:   PDF Manual  


GPL-3 license


Imports R6, RcppEigen, timeDate, yuima, ggplot2

Depends on orthopolynom

Suggests testthat, knitr, rmarkdown, doParallel, foreach

Linking to Rcpp


See at CRAN