COMPOSITE SECTOR ETF VALUATION REPORT [7.6.2015]

Check out the updated IPython notebook by following the link. In this update we see the interest rate sensitive sectors like Financials, Real Estate, Utilities may be offering a good tactical buying opportunity. 

Composite Sector ETF Valuation Report [6.15.2015]

Check out the updated IPython Notebook where I take a look at changes and trends in ETF valuations using the Implied Cost of Capital model. To learn more about the model and the methodology used see here and here

For reference here is a Table of Contents, but due to some technical issues the TOC is not working properly on the nbviewer.org page. I'll keep working to fix it for the next issue.

COMPOSITE SECTOR ETF VALUATION UPDATED [5.24.2015]

Check out my updated IPython Notebook where I take a look at changes and trends in ETF valuations using the Implied Cost of Capital model. To learn more about the model and the methodology used see here and here

Composite Sector ETF Valuation updated [5.24.2015]

Composite Sector ETF Valuation updated [5.10.2015]

Check out my updated IPython Notebook where I take a look at changes and trends in ETF valuations using the Implied Cost of Capital model. To learn more about the model and the methodology used see here and here

Composite Sector ETF Valuation updated [5.10.2015]

Sector ETF Valuation Using the Implied Cost of Capital (ICC) Model

This post is part of a series examining the ICC model's use as a valuation tool. I first introduced the topic in this post, where  I outlined the following:

  • how I calculate the ICC formula for use in this sector ETF relative valuation model
  • my assumptions for the model
  • expected model output and sanity check
  • why and how I use the model results to enhance my investing

Recently I expanded on the subject by detailing the Python code I use to run the analysis along with my interpretations of the output from the model.  For detailed coding/quant analysis I will be using the IPython Notebook and NBviewer to distribute and share the code. Unfortunately, Squarespace.com (my current host) doesn't have a good way to show the IPython notebook, so I will post the link to my research with a screenshot below. Take a look and as always I can be contacted @blackarbsCEO for feedback.