Why should you consider being a value investor?  Over the long-term, value investing has performed very well – generating higher compound annual returns other strategies.  These long-term returns are typically based on formulaic strategies that classify securities into Value and Growth categories based on basic fundamental metrics such as P/E, P/B or P/S multiples.  For example, the Fama/French database classifies the 30% of stocks with the lowest Price to Book ratios as value and the 30% of stocks with the highest Price to Book ratios as growth.   The Remaining 40% are classified as neutral.  Ibbotson portfolios created in the past took a similar approach using relative Price Earnings ratios.  The Russell 1000 Value Index classifies those companies with lower price to book ratios and lower forecasted growth rates as value.  The S&P 500 Value index uses a blend of relative price to book, price to earnings and price to sales ratios.

The problem with classifying stocks as value in this manner and then creating an index or investment strategy on such an index is that some stocks that have low price multiples may be selling at those price levels because they deserve to be – perhaps future earnings, sales or book value are expected to decline. We would also argue that many stocks classified as growth using these methodologies may also be value investments if they are selling at reasonable prices given their growth opportunities.  (see Its Value + Growth not Value versus Growth).  While we do not a fan of the way these indices classify value stocks and contrast them with growth, there are not currently any better value indices and it is useful to see how returns to such a basic formulaic approach compare.

Professor Kenneth French of Dartmouth makes data sets available based on the classic work of Fama and French on risk factors and stock returns.  Using annual return data from 1927 to 2019 (93 years) for equally weighted portfolios of stocks traded on the NYSE, AMEX and NASDAQ that have required data to compute Price to Book (P/B) multiples one can compute long term returns and standard deviation for both small stocks and large stocks (classified simply based on those below and above the median market equity of the NYSE).  We will focus on large stocks (the data on small stocks gets similar results):

1927 to 2019 Growth Value
Arithmetic Average 11.9% 16.7%
Geometric Average 9.6% 13.0%
Standard Deviation 22.0% 28.8%

The geometric average is the compound annual return realized for the 93 year period and is a function of both the arithmetic average and the standard deviation (a measure of volatility).  The portfolio of value stocks (the 30% of stocks that have lower price multiples) have a higher geometric return than the 30% considered to be growth.  This would have translated into higher ending wealth for value portfolios if you had invested from 1927 to 2019.  Many would attribute the higher returns to the value portfolio to higher risk as is seen in the higher standard deviation of returns.  I would agree.  As noted earlier many of these so-called value stocks deserve a lower valuation due to higher risks.  The investor is at least partially compensated for that risk through higher compound returns.

If you look at annual periods and rolling 5, 10 and 15 year periods value has outperformed growth over the long term a higher percentage of time:


Note in particular that the longer the holder period the higher the probability that value outperformed.  We do need to be careful though, the world, business and markets are quite different in 2020 than they were in 1927.  Lets just look at returns over the last 20 years:

2000 to 2019 Growth Value
Arithmetic Average 10.4% 11.6%
Geometric Average 8.0% 8.9%
Standard Deviation 22.4% 23.9%

While Value has outperformed growth over this recent 20-year period the so-called value premium has declined as has the difference in volatility. Unfortunately, the most recent decade has not been kind to value investors.  The last decade is one of those 10-year periods that growth has outperformed value:

2010 to 2019 Growth Value
Arithmetic Average 16.0% 12.6%
Geometric Average 15.1% 11.0%
Standard Deviation 15.2% 19.9%

None of us know what the world will look like in the next 10 or 20 years, particularly in a post COVID-19 world.  However, long term returns suggest that value investing does have value.  You must be prepared, however, for periods when value will underperform.  Also keep in mind that these indices are based on basic classifications of value versus growth stocks.  If you take a broader strategic view of value investing you would not simply buy stocks selling at low multiples or funds comprised of those stocks.  Instead you would evaluate the company’s managment, fundamentals and price (or in the case of funds the strategy of the fund managers) to find good companies with good managers selling at reasonable prices relative to their current fundamentals and future prospects.

Contributed by:  Tom Robinson

The Value of Value Investing:  Long Term Returns
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