Michael Mauboussin is considered an expert in the field of behavioral finance and has some famous books on the topic including, Think Twice: Harnessing the Power of Counterintuition and More More Than You Know: Finding Financial Wisdom in Unconventional Places.
From January 18, 2008 Michael Mauboussin: ROIC Patterns and Shareholder Returns
Odey's Brook Absolute Return Fund was up 10.25% for the third quarter, smashing the MSCI World's total return of 2.47% in sterling. In his third-quarter letter to investors, which was reviewed by ValueWalk, James Hanbury said the quarter's macro environment was not ideal for Brook Asset Management. Despite that, they saw positive contributions and alpha Read More
We draw two morals for our readers:
- Obvious prospects for physical growth in a business do not translate into obvious profits for investors.
- The experts do not have dependable ways of selecting and concentrating on the most promising companies in the most promising industries.
– Benjamin Graham, The Intelligent Investor
From Modeling to Making Money
Our recent piece, “Death, Taxes, and Reversion to the Mean”, aimed to provide context for analysts building financial models by documenting return on invested capital (ROIC) patterns for a large sample of companies. But the report was silent on the question most relevant for investors: Does an understanding of ROIC patterns help with stock picking? This piece addresses that question.
Three main points emerged from the analysis of ROIC patterns. First, analysts need to consider the lessons of history when modeling rather than approaching each model as
unique. Analysts should view the experience of a large sample of companies as a rich reference class. Second, the empirical evidence shows ROICs tend to revert to the mean, a level similar to the cost of capital. Randomness plays an important role in the mean-reversion process. Finally, some companies do deliver persistently high or low results beyond what chance would dictate. Unfortunately, pinpointing the causes of persistence is a challenge.
In an efficient market, stock prices are an unbiased estimate of value. Market efficiency does not say that stock prices are always right; it only asserts that prices are not wrong in a systematic way. For this analysis, we combined our data on ROIC patterns with total shareholder returns to see whether there is a consistent way to generate excess returns.
Buy the Best, Sell the Rest
Investment pros often recommend buying good businesses. So we started our total shareholder return investigation by analyzing the returns from equal-weighted portfolios based on 1997 ROIC quintiles (our data are from 1997 through 2006). The first quintile represents the 20 percent of the companies with the highest ROICs, while the fifth quintile comprises the worst-ROIC companies. Exhibit 1 shows the annual total shareholder returns (TSR) and the combination of returns and standard deviations for each portfolio from 1997 through 2006. Appendix A provides the full distributions. To provide some context, the 1,000-plus companies in this sample came from the Russell 3000, which provided an 8.6 percent return during this period. Appendix B reconciles the index’s returns with those from our sample.
The results show that buying the best business as measured by beginning-year ROIC rank would have yielded undistinguished returns. In fact, portfolios of the middle-quintile companies delivered higher returns with lower standard deviations. Only the lowest-quintile portfolio generated markedly substandard TSRs, and did so with the highest standard deviations to boot.
These figures are broadly consistent with the notion of market efficiency. The market equilibrates shareholder returns by placing high valuations on good businesses and low valuations (although, apparently not low enough) on bad businesses. 3 The market is generally decent at recognizing and pricing businesses consistent with their prospects.
What if we had some sense of whether companies would realize improved, sustained, or worsened ROICs through the measurement period? Exhibit 2 analyzes the returns based on the combination of where companies start (1997 rank) and end (2006 rank). For example, Q1-Q1 represents the group of companies that were in the highest ROIC quintile both in 1997 and 2006.
The results are somewhat intuitive. The market rewards improvement. For instance, the companies that started in Q4 and Q5 (lowest returns) and ended in Q1 and Q2 (highest returns) generated TSRs in excess of 14 percent annually. You can re-create this result by studying the bottom-left corner of Exhibit 2. Symmetrically, the market punishes worsening ROICs. Those companies that started in Q1 and Q2 but fell to Q4 and Q5—represented in the upper-right corner—had TSRs of -4.7 percent.
Companies that defy the powerful force of mean reversion and sustain either good or poor performance also deliver noteworthy TSRs. To illustrate, the companies that started and ended in Q1 and Q2 enjoyed TSRs of 11.4 percent. Those companies that were in Q4 and Q5 at both the beginning and the end of the period suffered TSRs of -0.7 percent.
See full Michael Mauboussin: ROIC Patterns and Shareholder Returns in PDF format here via CSInvesting