An updated version of quantmod is now on CRAN. It includes an awesome new feature that allows you to import up to 7 days of intraday data from Yahoo Finance!

This is the second post in the series on using TimeBase to stream real-time market data. This post covers using Docker to run TimeBase and the TimeBase Web Administrator.

This is the first post of a series on using TimeBase to stream real-time market data. TimeBase is a high performance event-based time series database and message broker. I used it on a proprietary trading desk that made markets in futures, and currently use it to build and test equity trading strategies. It was released as open-source in February 2021. Preface I am not affiliated with the company that created and maintains TimeBase (Deltix, now EPAM).

quantmod and getSymbols() have been a core part of the R/Finance ecosystem for over 15 years. We want to change some things, but they would break existing code. We can make these changes in the new ‘rfimport’ package instead.

An updated version of xts is now on CRAN. This release patches a few issues with the features added in version 0.13.0 and addresses a few maintenance issues that popped up recently.

An updated version of quantmod is now on CRAN. It adds functions HL(), is.HL(), and has.HL() to check for ‘high’ and ’low’ price columns. It also makes accessing Yahoo Finance price, dividend, and split data more robust. getSymbols.FRED() got to and from arguments, like other getSymbols() methods. The remaining changes are bug fixes and maintenace chores.

An updated version of xts is now on CRAN. This release adds several exciting changes: open-ended time-of-day subsetting, smarter conversions to xts from data.frames/data.tables/tibbles; to.period() handles custom endpoint values, print() truncates rows like data.table, and str() provides more informative output. There are also changes to make xts more consistent with zoo, some minor speed improvements, and the usual smattering of bug fixes.

An updated version of xts is now on CRAN. This release is a big one, with lots of changes. Plotting functionality got a lot of attention. Another notable change is that merge.xts() now supports suffixes. Plus the obligatory bug fixes and refinements to make xts more robust.

I follow Quantocracy on Twitter, and I found Rolling mean correlation in the tidyverse by Robot Wealth. They say to let them know if you’d approach it differently. I would, so I thought it would be interesting to replicate the analysis using tools I’m familiar with: xts and TTR.

An updated version of xts reached CRAN on 2020-09-09. Time-of-day subsetting (e.g. x["T10:00/T13:00"]) is 200x faster! (This post includes some notes on some nifty changes in 0.12.0 too, since I didn’t post about 0.12.0 when it was released.)