Step 9: History

Understand the historical risks and returns of indexes

9.4

Solutions

9.4.1

Long-term History Characterizes Risk and Return

Looking over the long term, David Booth reviews the history of the stock market and highlights the importance of time, not timing, in the achieving long term investment success.

The bar chart below shows how a passive investor in a balanced 60/40 portfolio did after various market crises. The results consistently showed a healthy gain after five years (or four years in the case of the Lehman bankruptcy in September, 2008). Selling out in response to a market crisis is usually not a good idea.

Figure 9-1A

IFA’s founder and president, Mark Hebner, produced the following video to help investors avoid being sucked in by the gloom and doom that is so pervasive in the financial media.

The history of several U.S. stock markets are captured in Figure 9-2. In essence this chart captures the effectiveness of capitalism over the last 81 years. The numbered events in Figure 9-2 are taken from the historical events in Table 9-2 below it, titled “Market Turmoil and the Dow Jones Industrial Average.” Despite several set backs, capitalism continues to work. Also note that the value of a dollar scale is a log scale, so each unit increases by a factor of 10. These are indexes and therefore the growth of a dollar does not reflect any fees or transaction costs. This long-term history of quality data allows investors to create the best set of probabilistic estimates of future performances of these indexes.

Figure 9-2

Table 9-2

Market Turmoil and the Dow Jones Industrial Average

9.4.1a

Effects of Government Intervention on Equity Returns

History shows that after nearly every major economic downturn, questions arise as to whether the free market system remains an appropriate way to organize and direct the nation’s resources.

Many individuals may be surprised to learn that government intervention can play a key role in free market systems. Milton Friedman, widely known as the most vocal proponent of the free market system cited that the true cause of the Great Depression was the US government’s failure to act swiftly to inject capital into the failing banking system.

"The Federal Reserve system stood idly by when it had the power and the duty and the responsibility to provide the cash that would have enabled the banks to meet the insistent demands of their depositors without closing their doors," Friedman stated in “Free to Choose 3: Anatomy of a Crisis.”

[ Click here to play ]

The chart below shows the relationship between equity returns and economic freedom rank. Economic freedom rankings data from Heritage Foundation awards their rankings in consideration of 10 specific elements.

As the chart shows, the US ranks very high in the area of economic freedom, while France came in significantly lower. It would be widely determined then, that the equity returns of a more Socialist-leaning France would be lower than those of the US. The reality, however, is quite different (the returns are very close). The chart’s vertical axis measures the equity returns of the countries. It shows that higher returns over the 43-year period were not always delivered to the countries with the highest degrees of economic freedom. Notoriously socialist-leaning countries relative to the US include Norway, Sweden, Japan, the Netherlands, France, Belgium, and Germany. The 43-year annualized returns of each of these countries defy the presumption that increased returns come from increased economic freedom.

Figure9-2A

The figure directly below depicts the annualized standard deviation, or the Risk, of each of the above countries, plotted against their annualized return, the Reward, over the last 43 years.

Figure9-2B

The bar chart directly below depicts the 43-year returns shown in figure 9-2A.

Figure 9-2C

The bar chart below shows the 10-year returns for countries based on their economic freedom rankings, as well. As you can see, in both long-term and short-term data, economic freedom indicators dispute the commonly held belief that government intervention hampers returns.

Figure 9-2D

(Click to play the Weston Wellington's DFA video: "What Should Investor Do Now- Part 5: Is Nationalization a Threat to the Free Enterprise System?" )

While the data presented here may seem surprising, the explanation is very straightforward. Just as value investments demand a higher return relative to growth investments to compensate for the higher risk associated with them, so too should investments in countries with increased government intervention demand higher expected returns to compensate investors for the increased perceived risk of investing in them.

This research, once again points to the simple and profound truth that investment returns come from investment risk, proving once again that there is no free lunch — even for perceived free market economic systems. Ken French talks about this subject and more in this interview.

The global history of the size and value effect on stocks is made even clearer by reviewing Figure 9-3. Next, Table 9-4 provides a thorough analysis of many indexes over the 1928 to 2012 period. Both the chart and table indicate that over the 85-year period, small-value has outperformed the S&P 500 and large-cap growth. Also, it is clear that value has had higher returns in international and emerging markets, even though available data only dates back to 1975 for international and 1989 for emerging markets.

Figure 9-3

Figure 9-4

Table 9-4

Table 9-3

To expand the range of asset classes to include art, farmland and gold, let’s take a look at Table 9-3.

It is interesting that over the 48-year period emerging market public equities outperformed venture capital, and at a lower risk level. In addition, the S&P 500 outperformed real estate by more than 50%, although the S&P 500 had about three times the risk. Figure 9-4 graphs the data from Table 9-3 on the Markowitz risk/return plot and adds in index portfolios 5, 50 and 100 for comparison. Note where venture capital and emerging markets sit on the plot. Gold and silver are also interesting, reinforcing the idea that they have lots of risk and returns pretty close to T-bills and bonds.

The May 2012 Ewing Marion Kauffman Foundation Report states that venture capital has delivered poor returns for more than 10 years. The title of the report is, " 'We Have Met the Enemy, and He is Us' - Lessons from Twenty Years of the Kauffman Foundation's Investments in Venture Capital Funds and The Triumph of Hope over Experience".

The authors report that the Limited Partner (LP) model is broken, for which investment committees and trustees are responsible. To determine whether a VC fund provided a successful investment experience, the authors compared the return received to what would have been obtained from a comparable investment in the public equity markets, specifically the Russell 2000 Index of small cap stocks. The majority of funds (62%) studied failed to exceed the return of the Russell 2000 on an absolute (non-risk adjusted) basis. Not surprisingly, the authors found that the larger funds (those in excess of $400 million) were more likely to underperform. These results are not surprising given that the average VC fund fails to return investor capital after fees.

Table 9-5

Venture Economics, an information provider for equity professionals, compiled a 20-year data series of various types of private equity strategies for the period ending December 31, 2005. According to the survey, venture and private equity strategies generally performed well over the period. But, the premium relative to public securities appears rather small considering the higher risk, investment concentration, absence of liquidity, transparency and daily pricing. The results are shown in Table 9-5.

Table 9-5A

9.4.1b

Recovery of the IFA Index Portfolios

Rare and severely punishing drops in the stock market can find investors wondering how long it might take for their portfolios to recover from a big loss. The table below shows the percentage amount of loss for the S&P 500 Index as well as for IFA Index Portfolios 100, 75, 50, 25, and 5 during the 16-month time period from November 2007 through February 2009, as well as the percentage gain that was required to restore each portfolio to its end of October 2007 high and the month in which the portfolio had made a recovery from the drop.

	Loss from 11/1/2007 to 2/28/2009	Percentage Gain Required to Offset Loss	Recovery Month
S&P 500	-50.95%	103.87%	August 2012
IFA Index Portfolio 100	-57.04%	132.77%	December 2012
IFA Index Portfolio 75	-50.16%	100.64%	September 2012
IFA Index Portfolio 50	-36.34%	57.08%	December 2010
IFA Index Portfolio 25	-20.73%	26.15%	March 2010
IFA Index Portfolio 5	-6.88%	7.39%	July 2009

Figure 9-4A

The 10 years ending in 2009 is often referred to as the "lost decade" due to the 9% loss for the S&P 500 Index over the period. However, with proper global and fixed income diversification and a small value tilt, the chart below shows how much better investors would have been. Please note that this gap is larger than what we have seen in other ten-year periods.

Figure 9-4B

9.4.2

Cross Correlation Among Indexes

In addition to the long-term risk and return of indexes, a third input used to create optimal portfolios is cross correlation. Cross correlation refers to the extent to which performances of different asset classes move in relation to each other. The lower the correlation among different indexes in a portfolio, the greater the diversification, which means lower volatility of returns.

If indexes are highly correlated, then their prices tend to respond to market news in the same direction at the same time. Market news that affects prices in all markets includes the overall strength of the U.S. economy, consumer confidence, the level of interest rates and expectations for inflation rates. A negative correlation means that market prices of different indexes commonly react in different directions to the same news. A near zero correlation indicates that These indexes have market price movements that are not connected, showing a low similarity in movement to each other.

For example, stocks and fixed income historically have a low correlation. As seen in Figure 9-5, large company stocks and one-year fixed income have a correlation that is close to zero, which means that the market prices of these two asset classes move independently of each other.

After negative and near zero correlations, the next best diversifier of risk is low positive correlation among asset classes in a portfolio. By designing the proper mix of low correlation index funds, it is possible to lower a portfolio’s risk and increase its risk-adjusted return at the same time. More historical data on the correlation among indexes found in the global financial markets appears in Figure 9-5.

Figure 9-5

The data in Figures 9-6, 9-7and 9-8 is attributable to the three risk factors documented by Eugene Fama, Kenneth French, and Jim Davis. These factors are used in a multiple regression analysis to risk adjust returns of other investments and to establish the cost of capital of firms that sell their equity. Remember that a firm’s cost of capital is equal to the investor’s expected return. The Fama/French data indicates that these three factors explain 95% of stock returns in diversified portfolios. In those calculations, average instead of annualized returns are used. The average annual returns of these risk factors are known as the risk premiums.

Figure 9-6

Figure 9-7

Figure 9-8

Figure9-8B

(also see this money chimp calculator )

A Comparative History of Several Indexes using Rolling Periods

At times investors doubt whether the fundamentals of capitalism and the relationship between risk and return will hold up in the future. For example, the August 13, 1979 issue of BusinessWeek featured this question on the cover: “Are Equities Dead?” After 10 years of lousy performance, it really must have appeared that way. For the 11-year period of 1969 to 1979, the S&P 500 average annual compound return was only 4.5%. And, it was even worse, 3.2%, for the more than seven-year period of 1973 to 1979, just before the article. These kinds of returns made it seem as if stocks were no longer a viable investment. Thus, many investors decided to invest only in Treasury bills, which outperformed stocks for both periods, and avoid the risk of stocks. Of course, the concern that the fundamental relationship between risk and return wouldn’t hold up was as ridiculous then as it is now.

An analysis of multiple year rolling periods offers an interesting way to sort out these kinds of concerns. This data shows that large value does not always outperform large growth stocks. In fact, the size and value risk factors come and go unpredictably. This is consistent with the Random Walk Theory of changes in stock prices. In addition, the cycle of good or bad returns for small company stocks compared to large company stocks can last for many years.

Figure 9-9

In "The Little Book of Common Sense Investing", page 160, there is a mention of the difference
between value stocks and growth stocks returns. Here is a table comparing these returns, growth of $1, and standard deviations of returns over the periods mentioned and also an 81 year period (all the data available for these dimensions). Click here for backtested data sources and disclosures. The links in the IFA Index column will take you to the IFA Risk Return Calculator, which was used to calculate the data.

Table 9-A	Table 9-C
Table 9-B	Table 9-D

A Comparative History of Market Cap Deciles

Figure 9-10 clearly lays out the history of the size effect. The several charts breaks out a number of time periods in history to illustrate the diversifying power of small-cap stocks. This chart is created using CRSP market capitalization data broken down into one-tenth size buckets, referred to as deciles. All 10 deciles are then measured and charted in different time periods. It illustrates that especially in shorter periods, small company stocks don’t always outperform large company stocks, but as seen in the top left chart, over the whole time period of 1927 to 2006, there is a clear advantage to have some exposure to small companies. But, in shorter periods anything can happen. For example, during the five-year period of 2002 to 2006, small company stocks widely outperformed large company stocks, while during the seven-year period of 1984 to 1990, and six years from 1994 to 1999, large-cap stocks were the king of the hill.

Figure 9-10 (Chart Link)

The Returns Matrix

The use of a returns matrix is yet another interesting way to look at long-term data. Figures 9-11 brings together annual and annualized returns covering every combination for a 35-year period for an IFA Index Portfolio 90. This big triangle identifies the years along all three borders. The intersection of any two years shows the annualized return over that period. The diagonal lines show one-year returns on the first diagonal and rolling period returns can be found on each diagonal line below the first one. For example, the first gray diagonal shows five year rolling periods. The very bottom left hand corner shows the annualized return over the entire 35-year period.

Figure 9-11 (Chart Link)

Click on the image to see the full matrix for all IFA Indexes, Portfolios and S&P500.

*How to read the Annualized Returns Matrix: You can locate the annualized compounded rate of return for this simulated Index Portfolio for a designated time period by following these easy instructions: Locate the column for the beginning year of the period. Years are labeled at the top and the bottom of each column. Then, locate the ending year of the period on the left-most vertical column. The annualized return can be found where the first year's column intersects with the ending year's row. IFA advisory fees of 0.9% per year and DFA mutual fund expense ratios have been deducted from these results. The 10-Yr diagonal (highlighted, starting from far left column) represents the estimated average holding period for investors who score 90 on the Risk Capacity Survey at ifa.com. Sources, Updates, and Disclosures: ifabt.com.

9.5

Summary

A good understanding of the long-term historical risk and return of various indexes enables an investor to know how to construct an efficient asset allocation according to risk capacity. Risk and return will work themselves out or revert to the mean over the long run. In the meantime, the best bet is to diversify among index funds that are structured for optimal exposure to risk factors that history has shown to be most rewarding.

9.6

Review Questions

Please answer the following questions before moving on to the next Step:

1. Stock markets are best characterized when looking at:

a. 1 year period
b. 5 year periods
c. 80 year periods
d. 3 year periods

2. The long-term characteristics of indexes are important because:

a. they better reflect the relationship between risk and return
b. margin rules are the same throughout history
c. favored industries change with time
d. the law of large indexes is not applicable to market returns

3. Many high net worth investors try to get allotments of venture capital partnerships. According to Morgan Stanley, over a 48-year period venture capital had a 16% return and a 35.4 risk index. Emerging market equities over the same period had the following:

a. 4.9% return, 26 risk
b. 16% return, 29.6 risk
c. 5.4% return, 6.2 risk
d. 12.7% return, 8.2 risk

4. Many people look at 80-year risk and return data and say that it is not relevant to them because they don’t have 80 years to invest. This is faulty logic because:

a. the basic concept of sampling error means short-term data is worse than long-term data
b. three years of data contains a large sampling error
c. one year of data has no predictive value on the following year's data
d. five years of data have no predictive value on the following year's data
e. all of the above

5. The index with the highest return since 1928 is:

a. large growth index
b. large value index
c. small growth index
d. small value index
e. total market

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Step 1: Active Investors

Definitions

Problems

Solutions

Step 2: Nobel Laureates

Definitions

Problems

Solutions

Step 3: Stock Pickers

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Problems

Step 4: Time Pickers

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Problems

Step 5: Manager Pickers

Problems

Step 6: Style Drifters

Definitions

Problems

Step 7: Silent Partners

Problems

Solutions

Step 8: Riskese

Definitions

Problems

Step 9: History

Definitions

Solutions

Step 10: Risk Capacity

Definitions

Problems

Solutions

Step 11: Risk Exposure

Definitions

Problems

Solutions

Step 12: Invest and Relax

Definitions

Problems

Step 9: History

Step 1: Active Investors

Definitions

Problems

Solutions

Step 2: Nobel Laureates

Definitions

Problems

Solutions

Step 3: Stock Pickers

Definitions

Problems

Step 4: Time Pickers

Definitions

Problems

Step 5: Manager Pickers

Problems

Step 6: Style Drifters

Definitions

Problems

Step 7: Silent Partners

Problems

Solutions

Step 8: Riskese

Definitions

Problems

Step 9: History

Definitions

Solutions

Step 10: Risk Capacity

Definitions

Problems

Solutions

Step 11: Risk Exposure

Definitions

Problems

Solutions

Step 12: Invest and Relax

Definitions

Problems