Here you can find quick updates to the tables used in monthly features on my blog. Currently we have 2 free monthly features:
RPA is a measurement of economic strength in the United States. I’ve taken the most common measurements of the economy such as unemployment, same store sales, GDP growth, business confidence, consumer comfort, and home values – and built a simple algorithm to measure their current strength compared to historical norms. The measurement is on a scale of 1 to 100, with 1 being the best and 100 being the worse. After publishing this information (started in November of 2007) and studying the backtests of the model we’ve found that the stock market generally is unfavorable (plain english=it goes down more than up) when the measurement is over 50.
I’ve studied asset allocation significantly since 1999. In Nobel Winning studies on Economics it’s been found that an investors asset allocation will determine more than 90% of their likelihood of success. Even with this overwhelmingly important fact, most investors fail significantly at understanding what the study means and how to actually use asset allocation effectively.
Beginning in October of 2011 I started publishing a free Tactical Asset Allocation model that measures what I feel to be the 4 key investment asset classes: Stocks, Bonds, Real Estate, and Gold. These are measured by index funds managed by Vanguard (for stocks, bonds, and real estate) and State Street Global Advisors (for gold). The reason to keep the asset classes simple is so that the actual data is easy to understand. Many investors over-complicate their asset allocation by using 20 different stock asset classes and just as many for bonds, alternatives, etc. This creates noise, volatility, and more expensive portfolios. Keeping it simple, cost effective, and easy to understand and use is the name of the game for how I measure effective Asset Allocation.
For the most up to date measurements of each of these free monthly features just click on the items above.
Thanks and enjoy responsibly,