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Your best investment is a global tax-managed mix of index funds (risk exposure) matched to your unique risk capacity. We call this CEO Investing: Capacity-Exposure Optimization.

The index portfolios that are the best long-term target asset allocations for investing are divided among three broad asset classes: fixed income (bonds); U.S. stocks; and foreign stocks. The stocks are further divided by size and value (book-to-market ratio). For an explanation as to why Investment Policy Explains All, please read this article. This article essentially confirms that your asset allocation of a portfolio of index funds explains 100% of your long term expected risk and return. If you are having trouble understanding this article, please call IFA, 888-643-3133.

To confirm the consensus of opinion of Financial Economists for the use of risk-scaled index portfolios as simulated historical benchmarks, please refer to the Financial Economists Roundtable: Statement on Risk Disclosure by Mutual Funds, September 18, 1996.

Matching People with Portfolios

Once the above article is understood, the only decision left is where should an investor be on the risk capacity versus risk exposure line. This is very important because returns are optimized when investors are on the line. Risk capacity can be estimated using the Risk Capacity Survey and risk exposure correlates to the 20 investment policies (asset allocations of indexes) shown in Figure 2 below. Where are you and your investments on the graph in Figure 1 If you do not know, your investments are equivalent to an uninformed guess or speculation. In Figure 1, investment policies with the lowest expected risk and return are tilted toward fixed income with a moderate investment in stocks.

Conversely, index portfolios with the highest expected risk and return have less fixed income and more stocks and are tilted toward small companies and value companies in the U.S., International and Emerging Market, as seen Figure 2 below.

Figure 1

Figure 2

Modern Portfolio Theory considers 3 parameters when constructing a portfolio on the efficient frontier; risk, return and the correlation of the different assets to each other. Rollover of Figure 1 illustrates risk versus reward for the twenty different index portfolios. Harry Markowitz received a Nobel prize for coming up with the idea illustrated in Figure 2, also see Step 2: Nobel Laureates; 1952 Harry Markowitz. The resulting portfolios are referred to as efficient portfolios, which are portfolios that provide the greatest expected return for a given level of risk, or equivalently, the lowest risk for a given expected return. These portfolios are said to exist on the efficient frontier.

Figure A Standard Error

The Risk Return Table below includes standard deviations for twenty portfolios of indexes. The standard deviation is a statistic that tells you how tightly all the various annual returns are clustered around the average of the total period. When the annual returns are pretty tightly bunched together and the bell-shaped curve is steep, the standard deviation is small. When the annual returns are spread apart and the bell curve is relatively flat, it tells you that you have a relatively large standard deviation. The combination of the average and the standard deviation characterize various bell curve shapes and those shapes represent the risk and return of the portfolio.Computing the value of a standard deviation is a little complicated. Figure A shows you graphically what a standard deviation represents. One standard deviation away from the average in either direction on the horizontal axis (the green area on the graph) accounts for somewhere around 68 percent of the annual returns in the time period. Two standard deviations away from the mean (the green and blue areas) account for roughly 95 percent of the annual returns. And three standard deviations (the green, blue and red areas) account for about 99 percent of the annual returns. Standard deviation expresses the spread of individual observations around the mean or average. A standard deviation is the square root of the variance. Variance is the measure of the spread of variability of quantitative measurements. The standard error of the mean indicates the degree of uncertainty in calculating an estimate from a sample, like a series of returns data. A standard error can be calculated from the standard deviation by dividing the standard deviation by a square root of n (with n representing the number of years measured). So with only 3 years of returns data on the S&P 500, the error in the average return is 2.6 times larger than having 20 years of data.