Tactical Asset Allocation – May 2017

Strategy Update


The Global Core Tactical Asset Allocation Strategy finished May up 0.87% and up 5.38% year to date.

Domestic Equities, International Equities, Fixed Income and Precious Metals all contributed to this month's gains. The Core Strategy allocation shift from US Small and Mid Cap Equities into International turned out particularly well. As has been the norm, the volatility of our Core Strategy has remained well below the muted market volatility.


If you were in big caps, the Info Tech sector, Europe, and Emerging Markets this month; the market rallied. If you were in mid caps, small caps, and most other sectors this month; the market declined. Fixed income gained a bit and collected dividends this month.

The Importance of Data

The Tactical Asset Allocation Model uses "dividend adjusted" historical closing data to insure that total return is calculated accurately. Early on, I satisfied myself that the data I was using was reasonably accurate; however I've long wanted some redundancy in sourcing the data used by the Model. As the saying goes "stuff happens".

A year or so ago, I sketched out plans to build a historical quote server which could pull data from multiple sources. I finally started on the project about six weeks ago. Accurate exchange closing prices are widely available although the format and consistency varies by vendor. Accurate "dividend adjusted" historical closing data requires adjusting (factoring) closing prices for dividends paid (and reinvested). This assures that funds in our baskets are accurately ranked during the selection process for total return.

While development was time-consuming, it was the dividend data which proved challenging. It also turned out that the subscription cost in no way reflects the quality of the data. I ended up with the ability to pull data from four sources; and while the sources generally agreed on the exchange close, none of them agreed on the "dividend adjusted" closing price. Getting to the root of the problem was an exercise in clerical patience during which I obtained the official dividend data from the fund providers and then compared it to the dividends used by the quote provider. The degree of sloppiness in some of the data was astounding!  Perhaps it is the sheer magnitude of dealing with thousands of symbols.

I ended up building a dividend history plant for the funds used in the Strategy fund baskets. This is used to insure that historical dividends are properly applied to historical exchange closing prices. The Tactical Asset Allocation Model now has redundant data sources and uses what I consider to be "perfect" dividend adjusted closing prices.

Consider that we use Market On Close orders to obtain execution at the same closing prices reported by the exchanges. There should be zero"slippage". Insuring that the dividends applied to our data match those which arrive in our account are another step in insuring that historical performance posted on the website reflects what is achievable for subscribers.

Earl Adamy

Tactical Asset Allocation Strategy Performance

Global Strategy (Conservative)

Month: 0.87% gain
Year-to-date: 5.39% gain
Full cycle-to-date (Sep 2007): 12.76% CAGR, 6.52% Max Monthly Drawdown

Global Strategy (Aggressive)

Month: 0.87% gain
Year-to-date: 5.39% gain
Full cycle-to-date (Sep 2007): 15.28% CAGR, 8.22% Max Monthly Drawdown

Tactical Asset Allocation Fund Basket Performance

Global Core

Month-to-date: 0.97% gain
Year-to-date: 4.47% gain
Full cycle-to-date (Sep 2007): 10.3121% CAGR, 6.52% Max Monthly Drawdown

Global Satellite

Month-to-date: hibernating since Nov 2014
Year-to-date: hibernating since Nov 2014
Full cycle-to-date (Sep 2007): 25.94% CAGR@Risk*, 8.22% Max Monthly Drawdown

*CAGR for the "Favorable" Market Conditions during which Global Satellite was invested