In the previous posts we have seen how easy it is to price interest rate swaps using R. I am honoured to announce that I have decided to put all the functions I have described together into a package that is called…SwapPricer!

Ok, the name is not super original, but it should at least be easy to remember.

You can install it as follows:

# library(devtools)
devtools::install_github("DavideMagno/SwapPricer")

The package is still unfortunately not on CRAN but it has an official hexagon. Here it is:

Let me know if you like it in the Disqus form below in the post.

In order to price a swap you just need to run the following code.

library(SwapPricer)
SwapPortfolioPricing(SwapPricer::swap.basket, lubridate::ymd(20190414), SwapPricer::df.table)
## # A tibble: 5 x 7
##   swap.id    clean.mv dirty.mv accrual.pay accrual.receive      par    pv01
##   <chr>         <dbl>    <dbl>       <dbl>           <dbl>    <dbl>   <dbl>
## 1 Swap 25y    -8.82e5  -8.75e5       5441.           1379.  0.00771 -12394.
## 2 Swap 30y     2.34e5   1.24e5     -97222.         -12470   0.0111   20867.
## 3 Swap 10y     2.22e5   2.36e5       6702.           7361. -0.00138  -5724.
## 4 Swap 2y16y   3.60e5   3.60e5          0               0   0.0118  -11163.
## 5 Swap non …  -2.59e6  -2.87e6    -263836.         -14681.  0.0107   27914.

You can see that I have used two objects that are delivered with the package:

• swap.basket which consists in a 5 swaps portfolio that can be referenced as blueprint for your swap portfolio

• df.table this is the discount curve downloaded from Bloomberg as at the 14th of April 2019

We have tested the package using a 500 swaps portfolio and the results, in terms of performance are very encouraging. We analyse them using the amazing profvis tool.