In this post I will show how easy is to price a portfolio of swaps leveraging the purrr package and given the swap pricing functions that we introduced in a previous post. I will do this in a “real world” environment hence using real market data as per the last 14th of April. Import the discount factors from Bloomberg Let’s start the pricing of the swap portfolio with purrr by loading from an external source the EUR discount factor curve.
Introduction I am a big passionate of the tidyverse packages: I think they make the code very clean and clear. In particular, I like the lubridate packages for managing and making operations with dates but its major drawback is that it doesn’t manage financial holidays, which are key when projecting financial cashflows linked to instruments like interest rte swaps. In this case, I prefer to use the RQuantLib package.
This week's #TidyTuesday is about federal spending. I was interested in understanding if spending had shifted towards clean energy sub-agencies in the last 20 years. Spoiler alert: unfortunately no! 😰#Rstats #tidyverse cc @thomas_mock @R4DScommunity pic.twitter.com/AbQzheSagU — Davide Magno (@DavideMagno) February 12, 2019
Here's my #TidyTuesday submission.I studied the total increase in the housing index for each US State compared to the US federal index. No surprise in California house price has increased much more than the rest of US.The #mapdata library was 👍🏼@thomas_mock @R4DScommunity #rstats pic.twitter.com/sYI1zKhIpC — Davide Magno (@DavideMagno) February 10, 2019
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