This commentary is available as a PDF here.
SUMMARY
- Growth and value have intuitive definitions, but there are many ways to quantify each.
- As with broad factors, such as value, momentum, and dividend growth, the specific metrics used to describe growth and value may fall in and out of favor, depending on the market environment.
- Taking a diversified approach to quantifying value and growth can lead to more consistent performance over time.
In our commentary a few weeks ago, we pointed out a key flaw that many index providers have in their growth and value style indices. The industry norm lumps “low value” in with “growth” and “low growth” in with “value” when, in reality, growth and value are independent characteristics of companies. The result is that many of the growth and value ETFs that track these indices are not giving investors what they expect – or what they want.
Final index construction aside, let’s go down to a more fundamental level: what are growth and value in the first place, and how do we measure them?
Intuitively, growth refers to companies that are growing and expected to continue, and value refers to companies that are currently cheap relative to their fair price.
Simple enough.
But a quick survey of index providers finds that the characteristics they use to measure a stock’s growth and value characteristics vary across the board:
Growth Characteristics:
- Long-term forward earnings per share growth (EPS) rate (CRSP, MSCI, Russell)
- Short-term forward EPS growth rate (CRSP, MSCI)
- Current internal growth rate (MSCI)
- Long-term historical EPS growth trend (CRSP, MSCI, S&P)
- Long-term historical sales per share growth trend (CSRP, MSCI, Russell, S&P)
- 12-month price change (S&P)
- Investment-to-assets ratio (CRSP)
- Return on assets, ROA (CRSP)
Value Characteristics:
- Book-to-price ratio (CRSP, MSCI, S&P, Russell)
- Forward earning to price ratio (CRSP, MSCI)
- Earnings-to-price ratio (CRSP, S&P)
- Sales-to-price ratio (CRSP, S&P)
- Dividend yield (CRSP, MSCI)
Only one metric on each list is common to all four index providers (Sales per share growth trend for growth and book-to-price ratio for value).
So who is right?
We can test the performance of many of these metrics using data readily available online. The forward-looking growth data are more difficult to find historically, but general financial statement data is available on Morningstar’s website.
To keep matters simple, we will look at three metrics for each of growth and value. For growth: 3-year EPS growth, 3-year sales per share growth, and ROA. For value: the P/E, P/S, and P/B ratios.
And to keep things as realistic as possible, we will evaluate the stocks in the S&P 500 as they stood at the end of 2014. Relative to the current set of companies in the S&P 500, we added back in some companies that dropped out of the S&P 500 (mainly energy and materials companies) in 2015. Some mergers and acquisitions also make getting data for the companies more difficult. For example, Covidien was bought by Medtronic, AT&T bought DirecTV, and Kraft merged with Heinz. Since we will be focusing on relative performance differences rather than on absolute ones, we will simply reconstruct a proxy S&P 500 index using the data that is available. In all, our universe contains 481 companies.
Using the fundamental data from December 2014, we can sort based on each metric and select the top 160 companies (about one-third of the universe) and see how that “value” or “growth” portfolio would have performed in 2015. Within each portfolio, we equally weight for simplicity. Results are compared to an equal-weight benchmark to control for any out or underperformance arising from the equal-weight allocation methodology as opposed to stock selection.
There is significant variation during the year depending on which metric was used.
Source: Data from Yahoo! Finance and Morningstar, calculations by Newfound
Source: Data from Yahoo! Finance and Morningstar, calculations by Newfound
For growth, all of the portfolios tracked each other until mid-March when the portfolio formed on sales growth began to diverge. The portfolios formed on EPS growth and ROA continued to track each other until mid-June. At this time, ROA rallied hard, eclipsing the sales growth portfolio in the 4th quarter of 2015.
On the value front, the P/S ratio led through most of the year before falling back to the pack in the Fall. The P/E and P/B portfolios ended the year in very similar places, with the P/S portfolio eking out a ~65bp benefit over the other two portfolios.
Which Metric to Choose
One year is hardly enough data to make a sound judgment as to which metric is the best for selecting growth and value stocks. As we have said many times before, even though we may know a factor (e.g. value) has outperformed in the past and is likely to do so in the future based on behavioral evidence, stating whether that factor will outperform in any given year is tough.
Likewise, deciding which measure of a factor will outperform in a given year is also difficult. Even with value companies, a metric like P/E ratio may not work well when companies with strong sales experience short-term earnings shocks or when companies are able to inflate earnings based on accounting allowances. The P/B ratio may not work well in periods when service oriented companies, which rely on intangible human capital as a large driver of growth, are being rewarded in the market.
Let’s take a closer look at some popular ways of quantifying the value factor.
“Value”, as it stands in academic literature, is commonly measured using the P/B ratio. This is what the famous Fama-French Three Factor Model uses as its basis for calculating the value factor, high-minus-low (HML).
However, using data from Kenneth French going back to 1951, we can see that, for long-only portfolios, those formed both on P/E and P/S actually beat the portfolio formed on P/B both on an absolute and risk-adjusted basis.
Furthermore, AQR showed in their 2014 paper, “The Devil in HML’s Details,” that not only does the metric matter, but the method of calculating the metric matters, as well. While Fama and French calculated HML using book value data that was lagged by 6 months to ensure that data would be available, they also lagged price data by the same amount. The AQR paper proposed using the most recent price data for calculating P/B ratios and showed that their method was superior to the standard lagged-price method because using more current price data better captures the relationship between value and momentum.
The P/S and P/E ratios used in the table above are also calculated using lagged price data. Based on AQR’s research, we expect that those results might also be improved by using the current price data.
Different Measures of Factors May Ebb and Flow
We should be careful not to rush to judgment though. The fact that P/B has underperformed the other value metrics does not mean we should drop it entirely. It is helpful to remember that individual factors can go through periods of significant underperformance. The same is true for different ways of measuring a single factor. For example, over rolling 12-month periods, the return difference between portfolios formed portfolio on P/B, P/S, and P/E – all “value” metrics – has often been in excess of 2000bp!
Put bluntly: your mileage may vary dramatically depending on which value metric you choose.
Source: Data from Kenneth French Data Library, calculations by Newfound
With our 2015 example, we saw that P/S resulted in the best performing portfolio, but as we said before, different measures tend to cycle unpredictably. We can see which ones have been in favor historically by comparing each individual portfolio to the average of all three portfolios.
Source: Data from Kenneth French Data Library, calculations by Newfound
The fact that many index providers combine multiple metrics into a composite growth or value score is an acknowledgement of this unpredictability.
Averaging the different value portfolios would have led to a fraction of outperforming periods on par with the best individual portfolios, higher average outperformance than the P/S portfolio, and lower average underperformance than all three individual portfolios.
Source: Data from Kenneth French Data Library, calculations by Newfound
If you read our previous commentary about multi-factor portfolio construction, you’ll notice that the averaging we did above is approach #1 (the “or” method). In effect, we are investing in companies that have either low P/S, P/B, or P/E ratios. One way to implement this would be to form portfolios based on each metric and then average the allocations into a final value portfolio.
In practice, most index providers score companies based on each selected metric, normalize the scores, and then average them (sometimes using different weightings). The portfolio is then formed using this composite score. This is more in line with approach #2 from the commentary (the “and” approach), which favors companies that have some degree of combined strength across multiple metrics.
While we used value and momentum in the commentary to illustrate why using the “and” approach is problematic in multi-factor portfolios, using this approach isn’t as bad when attempting to identify a single factor. The problem with value and momentum stemmed from the difference in time that each factor took to mature. Using the “and” approach introduced drag from the shorter maturity factor.
If there is no convincing argument that an individual growth or value measure takes longer to mature than another (for instance, does P/S normalize faster than P/B), then taking the “and” approach is not likely to result in a worse outcome. In this case, where we are simply trying to identify growth or value, we care more about the predictive nature of each metric that goes into forming the portfolio.
The index providers vary considerably in regards to what characteristics they look at and how they weight them to arrive at a final portfolio. If you believe that the P/B ratio is the best determinant of company value then you will get the purest exposure with Russell. If you think return on assets is an important contributing factor to company growth, CRSP’s index will be more in line with your view.
However, if you are like us and concede that while there are many ways to quantify growth and value, no one method can outperform over every single period, a diversified approach may be your best option.
What are Growth and Value?
By Nathan Faber
On March 28, 2016
In Risk & Style Premia, Value, Weekly Commentary
This commentary is available as a PDF here.
SUMMARY
In our commentary a few weeks ago, we pointed out a key flaw that many index providers have in their growth and value style indices. The industry norm lumps “low value” in with “growth” and “low growth” in with “value” when, in reality, growth and value are independent characteristics of companies. The result is that many of the growth and value ETFs that track these indices are not giving investors what they expect – or what they want.
Final index construction aside, let’s go down to a more fundamental level: what are growth and value in the first place, and how do we measure them?
Intuitively, growth refers to companies that are growing and expected to continue, and value refers to companies that are currently cheap relative to their fair price.
Simple enough.
But a quick survey of index providers finds that the characteristics they use to measure a stock’s growth and value characteristics vary across the board:
Growth Characteristics:
Value Characteristics:
Only one metric on each list is common to all four index providers (Sales per share growth trend for growth and book-to-price ratio for value).
So who is right?
We can test the performance of many of these metrics using data readily available online. The forward-looking growth data are more difficult to find historically, but general financial statement data is available on Morningstar’s website.
To keep matters simple, we will look at three metrics for each of growth and value. For growth: 3-year EPS growth, 3-year sales per share growth, and ROA. For value: the P/E, P/S, and P/B ratios.
And to keep things as realistic as possible, we will evaluate the stocks in the S&P 500 as they stood at the end of 2014. Relative to the current set of companies in the S&P 500, we added back in some companies that dropped out of the S&P 500 (mainly energy and materials companies) in 2015. Some mergers and acquisitions also make getting data for the companies more difficult. For example, Covidien was bought by Medtronic, AT&T bought DirecTV, and Kraft merged with Heinz. Since we will be focusing on relative performance differences rather than on absolute ones, we will simply reconstruct a proxy S&P 500 index using the data that is available. In all, our universe contains 481 companies.
Using the fundamental data from December 2014, we can sort based on each metric and select the top 160 companies (about one-third of the universe) and see how that “value” or “growth” portfolio would have performed in 2015. Within each portfolio, we equally weight for simplicity. Results are compared to an equal-weight benchmark to control for any out or underperformance arising from the equal-weight allocation methodology as opposed to stock selection.
There is significant variation during the year depending on which metric was used.
Source: Data from Yahoo! Finance and Morningstar, calculations by Newfound
Source: Data from Yahoo! Finance and Morningstar, calculations by Newfound
For growth, all of the portfolios tracked each other until mid-March when the portfolio formed on sales growth began to diverge. The portfolios formed on EPS growth and ROA continued to track each other until mid-June. At this time, ROA rallied hard, eclipsing the sales growth portfolio in the 4th quarter of 2015.
On the value front, the P/S ratio led through most of the year before falling back to the pack in the Fall. The P/E and P/B portfolios ended the year in very similar places, with the P/S portfolio eking out a ~65bp benefit over the other two portfolios.
Which Metric to Choose
One year is hardly enough data to make a sound judgment as to which metric is the best for selecting growth and value stocks. As we have said many times before, even though we may know a factor (e.g. value) has outperformed in the past and is likely to do so in the future based on behavioral evidence, stating whether that factor will outperform in any given year is tough.
Likewise, deciding which measure of a factor will outperform in a given year is also difficult. Even with value companies, a metric like P/E ratio may not work well when companies with strong sales experience short-term earnings shocks or when companies are able to inflate earnings based on accounting allowances. The P/B ratio may not work well in periods when service oriented companies, which rely on intangible human capital as a large driver of growth, are being rewarded in the market.
Let’s take a closer look at some popular ways of quantifying the value factor.
“Value”, as it stands in academic literature, is commonly measured using the P/B ratio. This is what the famous Fama-French Three Factor Model uses as its basis for calculating the value factor, high-minus-low (HML).
However, using data from Kenneth French going back to 1951, we can see that, for long-only portfolios, those formed both on P/E and P/S actually beat the portfolio formed on P/B both on an absolute and risk-adjusted basis.
Furthermore, AQR showed in their 2014 paper, “The Devil in HML’s Details,” that not only does the metric matter, but the method of calculating the metric matters, as well. While Fama and French calculated HML using book value data that was lagged by 6 months to ensure that data would be available, they also lagged price data by the same amount. The AQR paper proposed using the most recent price data for calculating P/B ratios and showed that their method was superior to the standard lagged-price method because using more current price data better captures the relationship between value and momentum.
The P/S and P/E ratios used in the table above are also calculated using lagged price data. Based on AQR’s research, we expect that those results might also be improved by using the current price data.
Different Measures of Factors May Ebb and Flow
We should be careful not to rush to judgment though. The fact that P/B has underperformed the other value metrics does not mean we should drop it entirely. It is helpful to remember that individual factors can go through periods of significant underperformance. The same is true for different ways of measuring a single factor. For example, over rolling 12-month periods, the return difference between portfolios formed portfolio on P/B, P/S, and P/E – all “value” metrics – has often been in excess of 2000bp!
Put bluntly: your mileage may vary dramatically depending on which value metric you choose.
Source: Data from Kenneth French Data Library, calculations by Newfound
With our 2015 example, we saw that P/S resulted in the best performing portfolio, but as we said before, different measures tend to cycle unpredictably. We can see which ones have been in favor historically by comparing each individual portfolio to the average of all three portfolios.
Source: Data from Kenneth French Data Library, calculations by Newfound
The fact that many index providers combine multiple metrics into a composite growth or value score is an acknowledgement of this unpredictability.
Averaging the different value portfolios would have led to a fraction of outperforming periods on par with the best individual portfolios, higher average outperformance than the P/S portfolio, and lower average underperformance than all three individual portfolios.
Source: Data from Kenneth French Data Library, calculations by Newfound
If you read our previous commentary about multi-factor portfolio construction, you’ll notice that the averaging we did above is approach #1 (the “or” method). In effect, we are investing in companies that have either low P/S, P/B, or P/E ratios. One way to implement this would be to form portfolios based on each metric and then average the allocations into a final value portfolio.
In practice, most index providers score companies based on each selected metric, normalize the scores, and then average them (sometimes using different weightings). The portfolio is then formed using this composite score. This is more in line with approach #2 from the commentary (the “and” approach), which favors companies that have some degree of combined strength across multiple metrics.
While we used value and momentum in the commentary to illustrate why using the “and” approach is problematic in multi-factor portfolios, using this approach isn’t as bad when attempting to identify a single factor. The problem with value and momentum stemmed from the difference in time that each factor took to mature. Using the “and” approach introduced drag from the shorter maturity factor.
If there is no convincing argument that an individual growth or value measure takes longer to mature than another (for instance, does P/S normalize faster than P/B), then taking the “and” approach is not likely to result in a worse outcome. In this case, where we are simply trying to identify growth or value, we care more about the predictive nature of each metric that goes into forming the portfolio.
The index providers vary considerably in regards to what characteristics they look at and how they weight them to arrive at a final portfolio. If you believe that the P/B ratio is the best determinant of company value then you will get the purest exposure with Russell. If you think return on assets is an important contributing factor to company growth, CRSP’s index will be more in line with your view.
However, if you are like us and concede that while there are many ways to quantify growth and value, no one method can outperform over every single period, a diversified approach may be your best option.