In this post we’ll focus on showcasing Plotly’s WebGL capabilities by charting financial portfolios using an R package called PortfolioAnalytics. The package is a generic portfolo optimization framework developed by folks at the University of Washington and Brian Peterson (of the PerformanceAnalytics fame). You can see the vignette here Let’s pull in some data first.
This post comes hot off the heels of the nigh-feature-complete release of vegalite (virtually all the components of Vega-Lite are now implemented and just need real-world user testing). I’ve had a few and seen a few questions about “why Vega-Lite”? I think my previous post gave some good answers to “why”. However, Vega-Lite and Vega
I previously wrote about some ad hoc R code for downloading Option Chain data from Google Finance. I finally wrapped it up into a package called flipsideR, which is now available via GitHub. Since I last wrote on this topic I've also added support for downloading option data from the Australian Securities Exchange (ASX). Installation
Doing quantitative research implies a lot of data crunching and one needs clean and reliable data to achieve this. What is really needed is clean data that is easily accessible (even without an internet connection). The most efficient way to do this for me has been to maintain a set of csv files. Obviously this
There are tons of resources to help you learn the different aspects of R, and as a beginner this can be overwhelming. It’s also a dynamic language and rapidly changing, so it’s important to keep up with the latest tools and technologies. That’s why R-bloggers and DataCamp have worked together to bring you a learning path for R. Each section...
I was surprised to see there weren’t more of these types of calculators in the R community. Inflation and adjusted payments seem like they would be more common. I was able to find a way to gather Consumer Price Index data using the quantmod package but quantmod leaves you to your own devices in converting
This post is in response to Michael Harris' Price Action Lab post, where he uses some simple R code to evaluate the asymmetry of returns from the day's close to the following day's open. I'd like to respond to his 3 notes, which I've included below.The R backtest assumes fractional shares. This means that equity is fully...
Markets are very smart in absorbing and reflecting information. If you think otherwise, try making money by trading. If you are new to it, make sure you don’t bet the house. In other words, markets are efficient. At least most of the time. So then why people trade? The general believe is that there are