Tactical Asset Allocation

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.

Here’s the complete live history of my Balanced Tactical Allocation Monthly Feature:

US Stocks (Vanguard Total Stock Market ETF as proxy)International Stocks (Vanguard Total International Stock Market ETF as proxy)Bonds (Vanguard Total Bond Market ETF as proxy)Real Estate (Vanguard REIT ETF as proxy)Gold (SPDR Gold ETF as proxy)Cash
September 20110%55%7%38%0%
October 20110%62%0%38%0%
November 20110%60%0%40%0%
December 20110%58%0%42%0%
January 20120%71%0%29%0%
February 20124%57%9%30%0%
March 201217%58%12%13%0%
April 201217%55%18%10%0%
May 201216%61%23%0%0%
June 20125%69%26%0%0%
July 201213%61%26%0%0%
August 201213%62%25%0%0%
September 201217%58%25%0%0%
October 201218%55%18%9%0%
November 201221%59%15%5%0%
December 201222%57%17%4%0%
January 201319%54%15%12%0%
February 201325%50%17%8%0%
March 201323%54%19%4%0%
April 201324%52%22%2%0%
May 201320%56%23%1%0%
June 201329%55%15%1%0%
July 201330%50%12%0%8%
August 201330%50%7%0%13%
September 201330%17%50%0%0%3%
October 201327%24%50%0%0%0%
November 201329%21%50%0%0%0%
December 201329%21%50%0%0%0%
January 201430%18%50%0%0%2%
February 201425%15%52%8%0%0%
March 201429%14%51%6%0%0%
April 201430%11%52%4%0%3%
May 201419%13%53%15%0%0%
June 201414%4%69%13%0%0%
July 201416%14%54%16%0%0%
August 201418%10%55%17%0%0%
September 201428%0%57%15%0%0%
October 201421%0%55%24%0%0%
November 201418%0%55%27%0%0%
December 201415%0%56%29%0%0%
January 201511%0%57%30%0%2%
February 201520%0%56%24%0%0%
March 201520%0%55%25%0%0%
April 201515%0%55%30%0%0%

Here’s the returns of the model including a backtest* going back to 1/1/2005:

Balanced Tactical Asset
Allocation Model
50% Total Stock Market
50% Total Bond Market
2015 (ytd)2.13%1.26%

Here’s the annualized returns and risk/reward metrics of the model including a backtest* going back to 1/1/1997:

Balanced Tactical
Asset Allocation Model
50% Total Stock Market
50% Total Bond Market
Annualized Return
(6/1997 to 1/2015)
(5 Yr Standard Deviation)
Best Month4.84%5.85%
Worst Month-4.64%-10.06%

*Backtest assumes perfect execution of trades and does not take into account slippage, assumes re-investment of all dividends and interest, no distributions from model, and assumes a hypothetical cost or fee of 2% per year deducted pro-rata on a monthly basis.  Slippage is the difference in price an investor might have actually gotten upon placing a trade order and the perfect closing price assumed in the model.  Including this limitation, backtesting has other limitations as well including an investors ability to completely remove emotion from their investing process and actually follow a statistical model.  Backtesting is also done with the benefit of hindsight; i.e., the model was created knowing it would have worked historically.  I feel backtesting is important but in no way is a guarantee a model will work the same in the future as it may have “hypothetically” worked as a model.  Performance published from 9/30/2011 to latest month end is live returns of an actual model account with real dollars invested paying a fee as described above.