About Jonathan Regenstein

Jonathan worked in the the world of finance and did graduate work in political economy before joining RStudio. He writes the R in finance blog series for Rviews and aspires to keep his github repos up-to-date.

Quandl and Forecasting

A Reproducible Finance with R Post by Jonathan Regenstein Welcome to another installment of Reproducible Finance with R. Today we are going to shift focus in recognition of the fact that there's more to Finance than stock prices, and there's more to data download than quantmod/getSymbols. In this post, we will explore commodity prices using [...]

Reproducible Finance with R: Interactive Maps and ETF Analysis

by Jonathan Regenstein In this post, I'll describe a Shiny app to support the Emerging Markets ETF Country Exposure analysis developed in a previous post I have done some additional work and updated the analysis to include five ETFs in the app, whereas we originally imported data on 1 ETF. The new notebook is available [...]

Reproducible Finance with R: ETF Country Exposure

by Jonathan Regenstein Today, we are going to tackle a project that has long been on my wish list: a Shiny app to take a fund or portfolio, analyze its exposure to different countries, and display those exposures on a world map. Now you know how exciting my wishlists are. Before describing our data importing/wrangling [...]

Reproducible Finance with R: Sector Correlations Shiny App

by Jonathan Regenstein In a previous post, we built an R Notebook that pulled in data on sector ETFs and allowed us to calculate the rolling correlation between a sector ETF and the S&P 500 ETF, whose ticker is SPY. Today, we’ll wrap that into a Shiny app that allows the user to choose a [...]

Reproducible Finance with R: Sector Correlations

by Jonathan Regenstein Welcome to the first installation of reproducible finance for 2017. It's a new year, a new President takes office soon, and we could be entering a new political-economic environment. What better time to think about a popular topic over the last few years: equity correlations. Elevated correlations are important for several reasons [...]

Reproducible Finance with R: A Shiny ETF Map

by Jonathan Regenstein In a previous post, we built an R Notebook that laid the groundwork for a Shiny app that allows users to graph country ETFs by clicking on a world map. In today’s Fun Friday post, we’ll charge forth to build that app, again using a flexdashboard so that we can stay in [...]

Reproducible Finance with R: Pulling and Displaying ETF Data

by Jonathan Regenstein It’s the holiday season, and that can mean only one thing: time to build a leaflet map as an interface to country Exchange Traded Fund (ETF) data! In previous posts, we examined how to import stock data and then calculate and display the Sharpe Ratio of a portfolio. Today, we’re going to [...]

Reproducible Finance with R: A Sharpe Ratio Shiny App

by Jonathan Regenstein In this previous post, we used an R Notebook to grab the monthly return data on three stocks, build a portfolio, visualize portfolio performance, and calculate the Sharpe Ratio. The Notebook format emphasized reproducibility and reuse by other R coders. Today, we’ll convert that Notebook into a Shiny application that allows end [...]

Reproducible Finance with R: The Sharpe Ratio

by Jonathan Regenstein Financial applications were an early driving force behind the adoption of the R language, but as data science becomes increasingly critical to banks, hedge funds, investment managers, data providers, exchanges, etc., R is becoming even more important to Finance. We are excited and inspired by what the future holds in the brave [...]

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