Boxplots and Day of Week Effects

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After following some R-related quant finance blogs like Timely PortfolioSystematic Investor or Quantitative thoughts–  to name some of my favourites – I decided to start my own. I’ll first focus on R snippets which come in handy, and will potentially expand to quant trading and backtesting as time allows.

I’ll start with a simple graphical boxplot analysis of “days of the week effects” with two R snippet/tidbits regarding:
  1. How do you adapt the ggplot2 plotting of boxplots to a mundane 50%-box 95%-line 5%-dots view?
  2. How do you subdivide your days in weekdays easily and robustly? 

Lets jump directly into the code which can be downloaded at

Running the code, we get following output:
From MarginTale

These boxplots now show 50% of the observations in the box, the vertical lines cover 95% and the dots 2.5%. I find this easier to communicate than the standard definition. This is implemented in the functions myBoxPlotSummary and myBoxPlotOutliers which are in turn called from stat_summary in ggplot.

A second issue I tripped over is the sorting of days in the above boxplot. If one uses the obvious way and just defines a factor as “weekdays(index(…))” then the plot function will alphabetically sort the days – not exactly what you want. If you then try to order the factors, your solution will depend on how locale (the language you use) specifies the abbreviations of the weekdays. A robust solution shown  in the code is to use the function .indexwday from the package xts.

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