Among stock investors, a common strategy/belief held is Value investing — buying stocks that are relatively cheaper on price/fundamental ratios.
Is Value investing dead?
The idea behind why value investing works is that Value stocks are either (1) riskier and/or (2) have been mispriced by the market. In theory, these elements of risk/mispricing lead to expected above-market returns.
However, this strategy has failed over the past couple of years, causing many to doubt/question what is going on with the strategy. Given the recent underperformance, there have been a lot of articles written about the “Death of Value Investing.”
Some of these articles that examine this question, “Is Value Dead?”, have examined the performance of two well-known indices, the Russell 1000 Value index, and the Russell 1000 Growth index. These are widely referenced in the industry, are market-cap-weighted, and have returns going back to 1979.
Value vs. growth: index performance
Since Value is supposed to beat Growth over the long-run, how have the indices performed?
Below is the performance from 1/1/1979 through 7/31/2020 of the Russell 1000 index, the Russell 1000 Growth index, and the Russell 1000 Value index.(1)
What immediately jumps out is that Value has lost to Growth over the entire time sample!
As a Value investor, a disappointment to say the least.
Digging deeper, let’s look at the performance over the past 10 years (8/1/2010-7/31/2020):
Viewed another way, since the human mind has issues with compounding:
And last, for the real pain, over the past 1, 3, and 5 years (through 7/31/2020):
Thus, in some people’s minds, Value investing is dead.
Let’s define the meaning of value investing
What is Value investing?
It is simply trying to buy stocks that are cheaper when compared to other stocks.
But what does it mean for a stock to be cheap?
Let us look at a simple example. Pretend that there are only 4 stocks in the universe in which we can invest. We are going to simply look at the firms’ earnings each year, and compare that to the price one would pay if you bought the entire company’s equity (i.e. the firm’s market capitalization). This is the simple P/E ratio.
So in my simple 4-stock example, Stocks 1 and 2 trade at a lower multiple of earnings relative to Stocks 3 and 4. A systematic Value investor, who only uses the P/E multiple, would prefer Stocks 1 and 2 compared to Stocks 3 and 4.
As a shopping example, Stocks 1 and 2 are “on-sale” compared to stocks 3 and 4. All 4 firms have the same market cap, but firms 1 and 2 make more $ (earnings) each year. So they “value” or “cheap” stocks.
Of course, my example above is very simplified and we are only looking at one point-in-time number–past year’s earnings.
Firms 3 and 4 may be growing at a faster rate, and we can create more advanced models to try to figure out the “best” investment. However, if it were the case that experts can create better models, then active managers wouldn’t lose to the market ~ 80% of the time over 5 years.
Academics have studied how Value stocks perform relative to Growth stocks. In general, they use the book value of assets divided by the market cap of the firm, as this was the measure used in the seminal 1992/1993 Fama and French papers.
What did they find?
They found that Value stocks outperformed Growth stocks. In the original paper, they highlight that this is most likely compensation for taking on additional risk (to underscore that this is not a free lunch).(2)
Of course, one can use other measures to identify cheap stocks, besides P/E and B/M. We examined different methods in our value metrics study. However, the big picture takeaway was the following — Value beat Growth.
So back to our Russell 1000 examples–why then, does the Russell 1000 indices have Growth beating Value?
Medium-term forecast earnings growth rate based on I/B/E/S two-year forecasts
Sales-per-share growth rate based on five-year historical sales
Without making any judgments on whether or not this is a good/bad process, one should note that the methodology is definitely different than the simple example above, which was simply splitting firms on the P/E multiple (or other value measures, like B/M or EBIT/TEV).
A test of the 1,000 largest firms
So what would happen if we went back and tested splitting the 1,000 largest firms(3) on a simple P/E multiple?
To answer that, I dug into the data. I annually rebalanced the portfolio on 6/30, using the firm’s market cap to identify the 1,000 largest firms. Firms’ earnings’ values were brought in as of 6/30 of each year, while only examining data available as of 3/31 each year.(4) This was done to eliminate a “look-ahead” bias.
All portfolios shown in the main text use market-cap weights, or value-weighting in the academic parlance.
How did they perform historically?
First, I wanted to check that the 1,000 largest firms reasonably matched the returns of the Russell 1,000 index. The results below show that the performance from 1/1/1979-12/31/2019 was very close, and the two returns are very highly correlated, at 99.83%.
1/1/1979 – 12/31/2019:
Next, I then split the universe on 1 variable as of 6/30, the Price/Earnings (P/E) multiple. Firms trading at higher multiples of earnings are deemed to be “Growth” firms, and firms trading at lower multiples of earnings are deemed to be “Value” firms. The results below are when I market-cap weight the two groups.
1/1/1979 – 12/31/2019:
What one sees is that, over the entire time cycle, there was about a 3% spread between Value and Growth.(5)
To drive home an important point here, given our universe is 1,000 stocks, I simply, once a year, split the firms into 500 cheap firms and 500 expensive firms using the P/E multiple and market-cap weighted the portfolio.
Nothing else is done.
Those 500 stocks are followed as a portfolio for one year, and above shows the returns to Value (“Cheap”) and Growth (“Expensive”)..
So what does 3% compound to over 42 years?
Thus, the difference is not negligible.
Since I already have the data, I decided to additionally split the universe into Terciles (3 groups), Quintiles (5 groups), and Deciles (10 groups).
You can see the performance below:
In general, the more one tilted towards the Value factor, moving from Terciles to Quintiles to Deciles, the larger the spread between Value and Growth.
However, this performance difference is definitely not a free lunch!
As shown inthe beginning of the article, the past 10 years, and especially the past 5 years, have not been kind to a Value Investor.
Thus, a true Value investor needs to be aware of this and understand the risk.
What about recent performance?
While the data I have above only goes through 12/31/2019, how has 2020 been for a Value investor using the simple P/E splits?
To study this, I updated the data through the end of 7/31 using Factset data to build portfolios as of 12/31/19.(6) One sees that Value definitely continued its underperformance this year. Below examines a simple split using P/E into Quintiles and Terciles, and market-cap weighting the portfolios.
Thus, Value can massively underperform Growth at times.
However, even if we appended the 2020 data, over the long-run, Value still beat Growth with a simple P/E split (while noting the relative performance shrank in 2020).
1/1/1979 – 12/31/2019 Data from CRSP/Compustat, 1/1/2020-7/31/2020 data from FactSet using a similar process. Below is the performance of the Deciles, Quintiles, and Terciles using the same data combination.
Jack Vogel, Ph.D., conducts research in empirical asset pricing and behavioral finance, and is a co-author of DIY FINANCIAL ADVISOR: A Simple Solution to Build and Protect Your Wealth. His dissertation investigates how behavioral biases affect the value anomaly. His academic background includes experience as an instructor and research assistant at Drexel University in both the Finance and Mathematics departments, as well as a Finance instructor at Villanova University. Dr. Vogel is currently a Managing Member of Alpha Architect, LLC, an SEC-Registered Investment Advisor, where he heads the research department and serves as the Chief Financial Officer. He has a PhD in Finance and a MS in Mathematics from Drexel University, and graduated summa cum laude with a BS in Mathematics and Education from The University of Scranton.
Performance figures contained herein are hypothetical, unaudited and prepared by Alpha Architect, LLC; hypothetical results are intended for illustrative purposes only. Past performance is not indicative of future results, which may vary. There is a risk of substantial loss associated with trading stocks, commodities, futures, options and other financial instruments. Full disclosures here.