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Dimensional Perspectives

For nearly 40 years, research at Dimensional has focused on advancing the understanding of what drives differences in expected returns among securities. Recent research into the behaviour of stocks with high investment, as measured by asset growth, suggests new ways to potentially enhance expected returns for stock investors.

The Theory

Valuation theory provides a framework for analysing the drivers of expected returns. It says that a stock’s price reflects expected future cash flows to shareholders discounted to the present through an expected rate of return. Valuation theory therefore predicts that for a given level of expected future cash flows, the lower the stock price, the higher the expected return on the stock. Similarly, for a given stock price, the higher the expected future cash flows to shareholders, the higher the expected rate of return. Expected future cash flows to shareholders are related to the expected future profits of the company. However, not all profits are returned to shareholders because companies may make investments. Therefore, expected investment lowers expected future cash flows to shareholders, holding expected future profits constant. Simply put, a company that must invest heavily to sustain its profits should have lower cash flows to investors than a company with similar profits but lower investment. If both companies trade at the same price today, this implies that the company with higher investment and lower cash flows has a lower expected return.

The Data

How can we measure and quantify firm investment? There are three ways a firm can raise capital to invest: equity issuance, debt issuance, and growth in retained earnings. Asset growth aggregates financing from all three methods. Equity issuance and growth in retained earnings both lead to an increase in the book equity of a firm and, as a result, to an increase in total assets. Debt issuance leads to an increase in the liabilities of a firm and consequently also to an increase in its total assets. Thus, we can focus on asset growth as a broad measure of investment to examine the relation between investment and expected returns.

As outlined in academic studies such as Fama and French (2006 and 2015), when sorting all stocks on asset growth, we see large average spreads or differences in returns between stocks with high asset growth and stocks with low asset growth. This is driven by the underperformance of firms with high asset growth rather than the higher performance of firms with low asset growth. We see this pattern in returns among US stocks, developed markets ex US stocks, and emerging markets stocks over the sample periods examined in our study. Digging deeper, we find that the spreads in returns are mainly driven by the underperformance of small cap stocks with high investment. Exhibits 1a and 1b help illustrate this point. Exhibit 1a shows historical differences in returns for large cap stocks, sorted into deciles by year-on-year asset growth, in the US, developed ex US, and emerging markets. Exhibit 1b performs the same analysis within the small cap stock universe. In observing and interpreting these data, one can see that while the spreads in average returns in large caps are in the direction predicted by valuation theory, these spreads are weak, as indicated by the smaller magnitudes of the spreads and lower t-statistics. The magnitude of the spreads among small caps are larger and statistically unlikely to have occurred by random chance in all the markets tested. The weaker investment effect among large caps (when compared to small caps) is consistent with smaller differences in asset growth among large caps also shown in the exhibits. Therefore, it is not surprising the spreads in returns among large caps when sorting on asset growth are less than among small caps.


Exhibit 1a. Statistical Analysis of Hypothetical Large Cap Stock Returns Sorted by Asset Growth Deciles in the US, Developed ex US, and Emerging Markets 
  

Past performance, including hypothetical performance, is no guarantee of future results. Actual investment returns may be lower. Source: Dimensional, using CRSP, Compustat, and Bloomberg. Eligible large cap stocks in the US, developed markets ex US, and emerging markets are sorted into deciles based on year-on-year growth in assets. We measure asset growth as the annual growth rate of assets. Large cap is defined as the top 92% of market capitalisation in the US, top 87.5% in non-US developed markets, and top 85% in emerging markets. Deciles are rebalanced annually in the US and semi-annually outside the US. Filters were applied to data retroactively and with the benefit of hindsight. Groups of stocks and their returns are hypothetical; are not representative of indices, actual investments, or actual strategies managed by Dimensional Fund Advisors or any of its affiliates; and do not reflect costs and fees associated with an actual investment. See Investment Premium Appendix for additional important information.The sample periods are determined based on the availability of data. The t-Statistic for Top-Bottom Decile is the t-statistic for the average monthly return difference between the top and bottom deciles.

Exhibit 1b. Statistical Analysis of Hypothetical Small Cap Stock Returns Sorted by Asset Growth Deciles in the US, Developed ex US, and Emerging Markets
  

Past performance, including hypothetical performance, is no guarantee of future results. Actual investment returns may be lower. Source: Dimensional, using CRSP, Compustat, and Bloomberg. Eligible small cap stocks in the US, developed markets ex US, and emerging markets are sorted into deciles based on year-on-year growth in assets. We measure asset growth as the annual growth rate of assets. Small cap is defined as the bottom 8% of market capitalisation in the US, bottom 12.5% in non-US developed markets, and bottom 15% in emerging markets. Deciles are rebalanced annually in the US and semi-annually outside the US. Filters were applied to data retroactively and with the benefit of hindsight. Groups of stocks are hypothetical; are not representative of indices, actual investments, or actual strategies managed by Dimensional; and do not reflect costs and fees associated with an actual investment. See Investment Premium Appendix for additional important information. The sample periods are determined based on the availability of data. The t-Statistic for Top-Bottom Decile is the t-statistic for the average monthly return difference between the top and bottom deciles.

Other papers have shown that net stock issuance, net debt issuance, high capital investment, and high acquisitions are negatively related to future stock returns. Cooper et al. (2008), Lyandres et al. (2008), and Fama and French (2016) find investment helps explain the high average returns associated with share repurchases4 and the low average returns associated with equity and debt offerings. We also find that the investment effect helps explain the poor performance of firms with high stock issuance, high debt issuance, high merger and acquisition activity, high growth in physical capital, and high growth in intangible capital.5 Therefore, incorporating investment into an implementation process may help address a broad set of return patterns in the data in a comprehensive and systematic manner.

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1Standard deviation is a measure of the variation or dispersion of a set of data points.


2A t-Statistic is a measure used to assess the reliability of a statistical result, such as a return difference. A t-Statistic larger than two in absolute value is generally considered to be one indication that the statistic is reliable.


3A weighted average is an average in which each quantity to be averaged is assigned a weight, which determines the relative importance of each quantity.


4A share repurchase is a corporate action through which a publicly traded company buys back some of its shares outstanding.


5Intangible capital refers to assets such as patents, trademarks, copyrights, computer software, branding, and reputation. 

REFERENCES


Cooper, Michael J., Huseyin Gulen, and Michael J. Schill. “Asset growth and the cross-section of stock returns.” Journal of Finance 63.4 (2008): 1609–1651.


Fama, Eugene F., and Kenneth R. French. “Profitability, investment and average returns.” Journal of Financial Economics 82.3 (2006): 491–518.


Fama, Eugene F., and Kenneth R. French. “A five-factor asset pricing model.” Journal of Financial Economics 116.1 (2015): 1–22.


Fama, Eugene F., and Kenneth R. French. “Dissecting anomalies with a five-factor model.” Review of Financial Studies 29.1 (2016): 69–103.


Lyandres, Evgeny, Le Sun, and Lu Zhang. “The new issues puzzle: Testing the investment-based explanation.” Review of Financial Studies 21.6 (2007): 2825–2855.

INVESTMENT PREMIUM APPENDIX


The eligible universe includes all stocks in relevant regions. REITs, tracking stocks, and investment companies are excluded from the universe. In addition, to be included in the international analyses, stocks need to meet certain minimum market capitalization and liquidity requirements. Unless otherwise specified, we use the following definitions and methodologies. Small cap is defined as approximately the bottom 8%, 12.5%, and 15% in US, developed ex US, and emerging markets, respectively. Large cap is defined as approximately the top 92%, 87.5%, and 85% in US, developed ex US, and emerging markets, respectively. Stocks are sorted annually in the US and semi-annually outside the US. Decile sorts are based on market capitalization.

 

Profitability is defined as operating income before depreciation and amortization minus interest expense divided by book equity.

Past performance, including hypothetical performance, is no guarantee of future results. Filters were applied to data retroactively and with the benefit of hindsight. Groups of stocks are hypothetical; are not representative of indices, actual investments, or actual strategies managed by Dimensional; and do not reflect costs and fees associated with an actual investment. Actual investment returns may be lower.

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