Quantext, Inc.
March 2, 2010
The consistency between the third and fifth data columns was the first evidence that QPP and Grantham yielded remarkably similar outlooks.
At that time, both Grantham and QPP were projecting US high-quality stocks to be substantial out-performers.
In February of this year, I again compared Grantham to QPP using all baseline settings in the Monte Carlo and three years of historical data through 2009 to initialize the model. The results are shown below. The trailing historical volatility of the ETFs is used to convert between CAGR (annualized return) and arithmetic average annual return.
Comparison between QPP and Grantham (Feb 2010)
Again, the Monte Carlo projections for average annual return that QPP generates are very close to Grantham’s for a number of major asset classes. To make the numbers comparable, I have added Grantham’s expected inflation of 2.5% to his expected real returns and converted his annualized returns (CAGR) into average annual returns using the following equation:
(1+Avg. Annual Return)2 - (Annualized Volatility)2 = (1+CAGR)2
To convert from CAGR to average annual return, I used the trailing three-year volatility for each of the representative ETFs.
Grantham is projecting average annual returns of 3.9% for US Government bonds and 3.7% for inflation indexed bonds, whereas QPP expects those to yield 4.0% and 4.2%, respectively. These projections are remarkably close. For international developed equities, Grantham expects no meaningful difference between large and small cap, and he believes that the category as a whole will have average annual returns of 10.1%. The Monte Carlo projections project an average annual return of 10.3% per year for international developed market equities.
For emerging markets, the asset class where Grantham expects the highest returns, Grantham’s projects 11.2% in average annual return. The Monte Carlo simulation yields a similar outlook, projecting 13% per year.
Grantham believes that emerging market stocks are overpriced, which lowers his estimates. Emerging markets were the outperforming asset class over recent years, so his point is well taken. The uncertainty in estimates of future return are a function of the volatility in that asset class, and the annualized volatility of EEM, my proxy for emerging markets, is 32.4% per year over the three years through 2009. Volatility that high is sufficient to explain the differences between my Monte Carlo projections and Grantham’s.
Up to this point, we have seen remarkable consistency between my Monte Carlo projections for various asset classes and Grantham’s projections. One area, though, exhibits substantial differences: broad market-cap weighted domestic equity indexes. Grantham’s projections reflect his belief that these indexes are greatly over-valued. The Monte Carlo’s baseline projection for the S&P500 is 8.3% per year, whereas Grantham projects 5.7% from large cap domestic equities. A similar disparity exists for small-cap stocks.
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