inst/doc/my-vignette.R

In vamc: A Monte Carlo Valuation Framework for Variable Annuities

## ---- echo = FALSE------------------------------------------------------------
  knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
  library(vamc)

## -----------------------------------------------------------------------------
# Initialize required inputs to boostrap a curve
swap <- c(0.69, 0.77, 0.88, 1.01, 1.14, 1.38, 1.66, 2.15)*0.01
tenor <- c(1, 2, 3, 4, 5, 7, 10, 30)
fixFreq <- 6
fixDCC <- "Thirty360"
fltFreq <- 6
fltDCC <- "ACT360"
calendar <- "General"
bdc <- "Modified_Foll"
curveDate <- "2016-02-08"
numSetDay <- 2
yieldCurveDCC <- "Thirty360"
holidays <- NULL

# Bootstrap a forward curve 
buildCurve(swap, tenor, fixFreq, fixDCC, fltFreq, fltDCC, calendar, bdc,
            curveDate, numSetDay, yieldCurveDCC, holidays)


## ---- echo=FALSE, results='asis'----------------------------------------------
# Default randomly generated covariance matrix
knitr::kable(mCov, col.names = indexNames)

## ---- echo=FALSE, results='asis'----------------------------------------------
# Default index names
knitr::kable(indexNames, col.names = c("Index Names"))

## -----------------------------------------------------------------------------
# We will show the index simulated path for five months of the first scenario 
indexScen <- genIndexScen(mCov, 100, 360, indexNames, 1 / 12, cForwardCurve, 1)
indexScen[1, 1:5, ]

## -----------------------------------------------------------------------------
# Again, we show the fund simulated path for five months of the first scenario 
fundScen <- genFundScen(fundMap, indexScen)
fundScen[1, 1:5, ]

## -----------------------------------------------------------------------------
# For illustration purposes, we will only simulate one guarantee contract for each of 
# the 19 guarantee types. Please note that due to randomness the generated portfolio 
# under this code block may not align with the default VAPort under lazy data.
if(capabilities("long.double")) {
VAport <- genPortInception(issueRng = c("2001-08-01", "2014-01-01"), numPolicy =  1)
}

## -----------------------------------------------------------------------------
# In this vignette, we will arbitrarily use the first two scenarios from fundSen to 
# valuate a portfolio of two guarantees to speed up the execution of the example.
# The input cForwardCurve is a vector of 0.02 with dimension 360. 
valuatePortfolio(VAPort[1:5, ], mortTable, fundScen[1, , ], 1 / 12, cForwardCurve)

## -----------------------------------------------------------------------------
# Again, we will arbitrarily age a portfolio of two guarantees to speed up the execution.
targetDate <- "2016-01-01"

# Here we generate historical fund scenarios using default index data stored under "histIdxScen"
histFundScen <- genFundScen(fundMap, histIdxScen)

# Perform aging
agePortfolio(VAPort[1:2, ], mortTable, histFundScen, histDates, dT = 1 / 12, targetDate, cForwardCurve)


## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## -----------------------------------------------------------------------------
exPolicy <- VAPort[1, ]
valuateOnePolicy(exPolicy, mortTable, fundScen[1:2, , ], 1 / 12, cForwardCurve)

## -----------------------------------------------------------------------------
# Similarly, users can age this single policy before pricing it. We use the same 
# target date and historical fund scenario as generated before
exPolicy <- VAPort[1, ]
ageOnePolicy(exPolicy, mortTable, histFundScen, histDates, dT = 1 / 12, targetDate, cForwardCurve)