Main points

  • We could do perfect (in a sense) performance measurement if we compared what was done to all of the possible alternatives
  • There are too many of those, but a random sample will do nicely
  • portfolio constraints are imposed as a form of insurance
  • random portfolios can help to show the cost and benefit of that insurance
  • R is a good environment for such work

annotated slides (pdf)

Presented 2009 June at the Thalesians.

There is a video of the talk on the Thalesian website (near the bottom).

Kommentarer inaktiverade för Using Random Portfolios with R

See more

Explore more content and blog posts.

  • jun 25, 26

    The email address patrick@burns-stat.com was out of action for a few hours today.  It is back now.

  • jun 25, 26

    Customization in R. Basics Several features benefit from being customizable — either because of personal taste or specifics of the environment. The way R implements this flexibility is through the [...]

  • jun 25, 26

    How to control the limits of data values in R plots. R has multiple graphics engines.  Here we will talk about the base graphics and the ggplot2 package. We’ll create [...]