Shiny portfolio

Nov 11, 2020

I will use this post as repository of all the publicly available shiny dashboards I have developed through time. Online Interest Rate Swap Monitor An online application developed using R shiny to monitor in realtime the change in the the Interest Rate Swap market by scraping the web. Source data is automatically scraped from a third party website . Interactive Dashboard on Covid19 data in Italy An interactive dashboard to track the evolution of the Covid19 contagion in Italy.

Multi Currency Swap Pricing with SwapPricer

Sep 9, 2019

I have released a new version of the package SwapPricer on GitHub here. As we are now at version 1.0.1 the toolbox is able to price using just a one-curve framework but is able to price multiple currencies (ie. CHF, EUR, GBP, JPY and USD) and any convention in terms of coupon frequency, day count convention. We are working to introduce OIS Discounting in the next releases SwapPricer: instructions for use To run a multi-currency swap portfolio valuation you need the following three “ingredients”:

SwapPricer is on Github

Jul 7, 2019

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:

Pricing floating legs of interest rate swaps

Jul 7, 2019

In this post we will close the trilogy on (old style) swap pricing. In particular, we will look at how downloading the data for the variable rate needed to calculate the variable leg accrual. Part 1 gave the general idea behind tidy pricing interest rate swaps using a 7 lines pipe Part 2 went much more into detail and priced some real world contract comparing the results obtained vs Bloomberg and showing significantly good results.

Real world tidy interest rate swap pricing

Apr 4, 2019

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.

Using the tidyverse for swap pricing

Mar 3, 2019

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.

US Federal Spending Analysis

Feb 2, 2019

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

Geospatial Analysis on Housing Price Index

Feb 2, 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

My First #TidyTuesday Submission

Feb 2, 2019

Finally my first #TidyTuesday submission! 🎊🎉I am starting from week 1 2019 but I will catch up soon😉When do people submit their visualisations?Mostly on Tuesday and Wednesday afternoon, but also on Monday before the new set is released #rstats #ggplot @rstats4ds @thomas_mock pic.twitter.com/pKZAyL8vp1 — Davide Magno (@DavideMagno) February 3, 2019

Convert foreign currency valuations

Feb 2, 2018

One of the most common problems when dealign with financial data is to have assets (or liabilities) denominated in a currency that is different from the domestic one. I propose a tidy solution to this problem that involves no use of for cycles. The principle of the solution is that converting each currency can be done in parallel using the map function while the consolidation of the results will be done using the reduce logic.