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Dimensions of Expected Return: Patience is a Virtue – 2019 Update

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A goal of investment advice should be to educate investors and increase their level of understanding. We do not expect everyone to have a PhD in Economics, so it is important to focus on big ideas that are the most crucial to understand. This can include ideas such as diversification, costs, and discipline.

With that said, we also recognize that many investors who have been engaged with their finances for some time or have a long standing relationship with their wealth advisor, deserve to continually learn more about investing, specifically how Index Fund Advisors manages their money. Today, we are going to venture further down the rabbit hole with the investment strategy that we implement.

The dimensions of expected return is a finer topic that most of our own investors are aware of, but not necessarily the greater population. It is difficult enough to motivate individuals to embrace a passive investment strategy let alone educating them about multiple regressions and time-tested data. Nonetheless, it is extremely important not only from an academic standpoint, but also from a successful investment experience standpoint.

History

Starting in the 1960s, financial economists began researching the behavior of stock prices. Two major events led to this particular movement in the field of economics: the development of computers and the establishment of the Center of Research in Security Prices (CRSP) at the University of Chicago. Economists now had the most comprehensive dataset of stock prices and large machines that could make many computations in a reasonable amount of time. You put these two things together and all of sudden you have an entirely new concentration in the field of economics.

Decades of research and thousands of peer review academic studies of the drivers of stock market returns have led to amazing discoveries about how different types of stocks move in relation to one another. We can slice and dice the market by different factors such as market capitalization, fundamentals like book value or sales compared to market price and region to see how different types of stocks compare to one another around the world. From a practical standpoint, in terms of being able to translate academic findings into actual investment strategies, 4 factors or "premiums" have been found within stocks and successfully implemented (there are 2 factors that drive the behavior of bond prices):

Figure 1:

We know that, historically, stocks have outperformed bonds, small cap stocks have outperformed large cap stocks, value stocks have outperformed growth stocks, and stocks that have high profitability have outperformed stocks with low profitability. Furthermore, we have been able to design investment strategies around these different factors.

Now we are not suggesting that focusing on these "premiums" is a free lunch: quite the contrary. Traditional economic theory would suggest that higher expected returns must be associated with higher risk, which we believe is most accurate. Other theories have suggested that these premiums may be associated with behavioral biases, but unfortunately, proponents of the behavioral theory have not presented an economic model to support and test their theory. We are, in essence, pursuing different areas of the market that have been shown to reward investors, but that involves taking risk. As we will show later on, there are periods of time where investors are not rewarded for pursuing these areas in the market, hence, why they are considered "risk premiums." It is important for investors and advisors to have a healthy respect for these risk premiums when suggesting a particular asset allocation.

Why These 4 in Particular?

Before we go further, it is important to understand that there have been many factors found in academic research, but we stick with these particular 4 factors for the following reasons:

  • They are sensible
  • Persistent across time periods
  • Pervasive across markets
  • Robust to alternative specifications
  • Cost-effective to capture in a diversified portfolio

In other words, there is a very high degree of confidence that investors will benefit from focusing on these particular factors. From a fiduciary standpoint, it is crucial that we only suggest investment strategies that have been shown to be successful through rigorous scientific inquiry.

Historical Performance of These Factors

We now have a general understanding about dimensions of expected return. Historically, investors who have focused on these particular factors within equities have been rewarded with higher returns. Figure 2 below shows the historical size, relative-price, and profitability premiums for US, International/Developed, and Emerging Markets using the longest dataset available for each market.

Figure 2:

For example, within the Emerging Markets Stocks, value stocks have outperformed growth stocks (Relative Price premium) by approximately 3.66% per year from 1989-2018. The highest premium has been the Profitability premium in International Developed markets, delivering 5.60% per year from 1996-2018. The smallest premium has been the Size premium in the Emerging Markets, delivering 1.87% per year from 1989-2018.

No Such Thing as a Free Lunch

As we mentioned earlier, pursuing these different premiums in the market is no free lunch. If we want to be rewarded with higher expected return, then we have to take risk. While we should expect these premiums to be positive in any year, there are periods of time where they are not. Many clients of IFA are probably well aware that the Relative Price premium (value stocks) in the U.S. has not been favorable over the last 10-year period ending 12/31/2018. Figure 3 below shows the annual performance for each premium in the U.S. from 1928-2018. A blue bar indicates a positive premium while a red bar indicates a negative premium.

 Figure 3:

As you can see, there are definitely more blue bars than red bars, but there are stretches of time where different premiums do not show up.

Although the average premium observed overtime has been positive, there is extreme variation around that average. For example, just looking at the Relative Price premium in the U.S., we can see that the simple historical average has been 4.70%. There have only been 11 out of 90 calendar years where the observed premium was within 2% of the historical average. See Figure 4 below.

 Figure 4:

The dashed line represents the arithmetic average (4.70%). The gray shaded area represents the 2.00% range around that average. The dark blue bars represent the annual observations that fall within the range (2.70% - 6.70%).

While the average Relative Price premium in the U.S. has been approximately 5%, it is more likely that you will experience a much higher or much lower premium in any given calendar year. The same conclusion holds for the Size and Profitability premiums in the U.S. and around the world.

Patience is a Virtue

While many investors are well aware of diversification in terms of investments, it is also important to understand diversification in terms of time. We diversify our investments as a risk control. Because we do not know with a high degree of certainty which area of the market is going to be the next winner, we hold many different types of stocks. Time diversification is the idea of following a particular investment style over time. As we mentioned before, premiums do not always show up in any given year, but the longer we hold onto them, the likelier we are to capture their benefits.

If instead of looking at 1-year returns we now looked at 5-year rolling returns, how do the premiums in the U.S. look?

 Figure 5:

In Figure 5, each bar shows the 5-year period ending in that particular year. For example, the first red bar under the "Market premium" is for the 5-year period ending 1932. The next red bar is the 5-year period ending 1933 and so on and so forth.

What do you notice?

Compared to the 1-year annual returns shown above, there are less red bars in the 5-year rolling returns. In other words, once we move from looking at premiums from 1 year to 5 years, the probability of seeing a positive premium increases. This is the concept of time diversification.

Again, just to highlight the Relative Price premium in the U.S., Figure 6 below is a chart showing the historical 5-year annual rolling returns.

 Figure 6:

Looks like a smoother ride for the investor versus annual returns.

Following the same logic, what if we looked at 10-year rolling periods in the U.S.?

 Figure 7:

As you can see in Figure 7, this looks even better than the 5-year rolling returns as there are even less red bars across all 4 premiums.

Once again, just to highlight the Relative Price premium in the US, Figure 8 below shows the 10-year annual rolling return.

 Figure 8:

As you can see, once we present the data in terms of 10-year rolling periods, the pursuit of this premium looks very attractive. From 1941-1997, there was not a single 10-year rolling period where value stocks underperformed growth stocks. With that said, you can also see that each of the 10-year rolling periods from 2011 through 2018 is one of the worst periods for value stocks since the Great Depression. 

Figure 9 below shows the historical performance of the Market, Size, Relative Price, and Profitability premiums in the U.S. over 1,5 and 10 year rolling periods. As you can see, the longer the rolling period for each premium the greater the probability of experiencing a positive premium. 

 Figure 9:

For example, looking at historical 10-year rolling periods for the Market premium, investors have experienced a positive premium 85% of the time. You can see a similar trend across all other premiums.

 

Things Can Turn Quickly

We have already discussed the extreme variability around the historical averages for each premium. This variability means that things can turn either positive or negative rather quickly, highlighting the importance of long-term discipline when pursuing these risk premiums within an investment portfolio. Figure 10 below shows the historical 10-year annual rolling observations for the Relative Price premium sorted from lowest to highest.

 Figure 10:

You can see, for the 10-year period from 2009-2018, the value premium was the second lowest in history. But if we go back just eight years and look at the 10-year period from 2001 to 2010, the value premium switches to positive. This just emphasizes the importance of having a long-term focus when deciding to pursue these risk premiums within a portfolio.

Conclusion

As advisors it is our duty to constantly educate our clients about the reasoning behind their particular investment strategy. This not only allows us to be transparent, but it is crucial in building long-term investment discipline. Beyond investing in index funds, academic research has found certain factors or premiums within the market that explain the variation in its returns. By pursuing these premiums we can increase the expected return of the portfolio for our investors, but this does not come without accepting a higher degree of risk. Because there is significant variability around these premiums in any given year, it is important to maintain a long-term focus. Historically, the number of positive observations for each premium around the world increases as we increase the time horizon. Because IFA takes a long-term approach to the investment process, pursuing these premiums within our portfolios is expected to be beneficial for our clients with the ultimate goal of creating a positive investment experience.

Should you have any questions in regards to these risk premiums and how we pursue them within your portfolio, feel free to reach out to one of IFA's Wealth Advisors.

This article is distributed for informational purposes, and it is not to be construed as an offer, solicitation, recommendation, or endorsement of any particular security, products, or services. Data in this article is provided for illustrative purposes only, it does not represent actual performance of any client portfolio or account and it should not be interpreted as an indication of such performance. IFA utilizes standard deviation a quantification of risk, for more detailed explanation of standard deviation and other important investment terms go to IFA glossary. There is no guarantee investment strategies will be successful.  Investing involves risks, including possible loss of principal.

Index Descriptions

Dimensional US Small Cap Index was created by Dimensional in March 2007 and is compiled by Dimensional. It represents a market-capitalization-weighted index of securities of the smallest US companies whose market capitalization falls in the lowest 8% of the total market capitalization of the Eligible Market. The Eligible Market is composed of securities of US companies traded on the NYSE, NYSE MKT (formerly AMEX), and Nasdaq Global Market. Exclusions: Non-US companies, REITs, UITs, and investment companies. From January 1975 to the present, the index also excludes companies with the lowest profitability and highest relative price within the small cap universe. Profitability is measured as operating income before depreciation and amortization minus interest expense scaled by book. Source: CRSP and Compustat. The index monthly returns are computed as the simple average of the monthly returns of 12 sub-indices, each one reconstituted once a year at the end of a different month of the year. The calculation methodology for the Dimensional US Small Cap Index was amended on January 1, 2014, to include profitability as a factor in selecting securities for inclusion in the index.
Dimensional US High Profitability Index was created by Dimensional in January 2014 and represents an index consisting of US companies. It is compiled by Dimensional. Dimensional sorts stocks into three profitability groups from high to low. Each group represents one-third of the market capitalization. Similarly, stocks are sorted into three relative price groups. The intersections of the three profitability groups and the three relative price groups yield nine subgroups formed on profitability and relative price. The index represents the average return of the three high-profitability subgroups. It is rebalanced twice per year. Profitability is measured as operating income before depreciation and amortization minus interest expense scaled by book. Source: CRSP and Compustat.
Dimensional US Low Profitability Index was created by Dimensional in January 2014 and represents an index consisting of US companies. It is compiled by Dimensional. Dimensional sorts stocks into three profitability groups from high to low. Each group represents one-third of the market capitalization. Similarly, stocks are sorted into three relative price groups. The intersections of the three profitability groups and the three relative price groups yield nine subgroups formed on profitability and relative price. The index represents the average return of the three low-profitability subgroups. It is rebalanced twice per year. Profitability is measured as operating income before depreciation and amortization minus interest expense scaled by book. Source: CRSP and Compustat.
Dimensional International Small Cap Index was created by Dimensional in April 2008 and is compiled by Dimensional. July 1981–December 1993: It Includes non-US developed securities in the bottom 10% of market capitalization in each eligible country. All securities are market capitalization weighted. Each country is capped at 50%. Rebalanced semiannually. January 1994–Present: Market-capitalization-weighted index of small company securities in the eligible markets excluding those with the lowest profitability and highest relative price within the small cap universe. Profitability is measured as operating income before depreciation and amortization minus interest expense scaled by book. The index monthly returns are computed as the simple average of the monthly returns of four sub-indices, each one reconstituted once a year at the end of a different quarter of the year. Prior to July 1981, the index is 50% UK and 50% Japan. The calculation methodology for the Dimensional International Small Cap Index was amended on January 1, 2014, to include profitability as a factor in selecting securities for inclusion in the index.
Dimensional International Low Profitability Index was created by Dimensional in January 2013 and represents an index consisting of non-US developed companies. It is compiled by Dimensional. Dimensional sorts stocks into three profitability groups from high to low. Each group represents one-third of the market capitalization of each eligible country. Similarly, stocks are sorted into three relative price groups. The intersections of the three profitability groups and the three relative price groups yield nine subgroups formed on profitability and relative price. The index represents the average return of the three low-profitability subgroups. The index is rebalanced twice per year. Profitability is measured as operating income before depreciation and amortization minus interest expense scaled by book. Source: Bloomberg.
Dimensional International High Profitability Index was created by Dimensional in January 2013 and represents an index consisting of non-US developed companies. It is compiled by Dimensional. Dimensional sorts stocks into three profitability groups from high to low. Each group represents one-third of the market capitalization of each eligible country. Similarly, stocks are sorted into three relative price groups. The intersections of the three profitability groups and the three relative price groups yield nine subgroups formed on profitability and relative price. The index represents the average return of the three high-profitability subgroups. The index is rebalanced twice per year. Profitability is measured as operating income before depreciation and amortization minus interest expense scaled by book. Source: Bloomberg.
Dimensional Emerging Markets Low Profitability Index was created by Dimensional in April 2013 and represents an index consisting of emerging markets companies and is compiled by Dimensional. Dimensional sorts stocks into three profitability groups from high to low. Each group represents one-third of the market capitalization of each eligible country. Similarly, stocks are sorted into three relative price groups. The intersections of the three profitability groups and the three relative price groups yield nine subgroups formed on profitability and relative price. The index represents the average return of the three low-profitability subgroups. The index is rebalanced twice per year. Profitability is measured as operating income before depreciation and amortization minus interest expense scaled by book. Source: Bloomberg.
Dimensional Emerging Markets High Profitability Index was created by Dimensional in April 2013 and represents an index consisting of emerging markets companies and is compiled by Dimensional. Dimensional sorts stocks into three profitability groups from high to low. Each group represents one-third of the market capitalization of each eligible country. Similarly, stocks are sorted into three relative price groups. The intersections of the three profitability groups and the three relative price groups yield nine subgroups formed on profitability and relative price. The index represents the average return of the three high-profitability subgroups. The index is rebalanced twice per year. Profitability is measured as operating income before depreciation and amortization minus interest expense scaled by book. Source: Bloomberg.
Dimensional Emerging Markets Small Cap Index was created by Dimensional in April 2008 and is compiled by Dimensional. January 1989–December 1993: Fama/French Emerging Markets Small Cap Index. January 1994–Present: Dimensional Emerging Markets Small Index Composition: Market-capitalization-weighted index of small company securities in the eligible markets excluding those with the lowest profitability and highest relative price within the small cap universe. Profitability is measured as operating income before depreciation and amortization minus interest expense scaled by book. The index monthly returns are computed as the simple average of the monthly returns of four sub-indices, each one reconstituted once a year at the end of a different quarter of the year.
Source: Bloomberg. The calculation methodology for the Dimensional Emerging Markets Small Cap Index was amended on January 1, 2014, to include profitability as a factor in selecting securities for inclusion in the index.
Fama/French Total US Market Research Index: July 1926–Present: Fama/French Total US Market Research Factor One-Month US Treasury Bills. Source: Ken French Website.
Fama/French US Value Research Index Provided by Fama/French from CRSP securities data. Includes the lower 30% in price-to-book of NYSE securities (plus NYSE Amex equivalents since July 1962 and Nasdaq equivalents since 1973).
Fama/French US Growth Research Index Provided by Fama/French from CRSP securities data. Includes the higher 30% in price-to-book of NYSE securities (plus NYSE Amex equivalents since July 1962 and Nasdaq equivalents since 1973).
Fama/French International Value Index: 2008–present: Provided by Fama/French from Bloomberg securities data. Simulated strategy of MSCI EAFE Canada countries in the lower 30% price-to-book range. 1975–2007: Provided by Fama/French from MSCI securities data.
Fama/French International Growth Index: 2008–present: Provided by Fama/French from Bloomberg securities data. Simulated strategy of MSCI EAFE Canada countries in the higher 30% price-to-book range. 1975–2007: Provided by Fama/French from MSCI securities data.
Fama/French Emerging Markets Value Index: 2009–present: Provided by Fama/French from Bloomberg securities data. Simulated strategy using IFC investable universe countries. Companies in the lower 30% price-to-book range; companies weighted by float-adjusted market cap; countries weighted by country float-adjusted market cap; rebalanced monthly. 1989–2008: Provided by Fama/French from IFC securities data. IFC data provided by International
Finance Corporation.
Fama/French Emerging Markets Growth Index: 2009–present: Provided by Fama/French from Bloomberg securities data. Simulated strategy using IFC investable universe countries. Companies in the higher 30% price-to-book range; companies weighted by float-adjusted market cap; countries weighted by country float-adjusted market cap; rebalanced monthly. 1989–2008: Provided by Fama/French from IFC securities data. IFC data provided by International
Finance Corporation.