Quantitative Value Research: Long-term P/E Ratio

Quantitative Value Research: Long-term P/E Ratio

November 10, 2014 Research Insights, Value Investing Research
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(Last Updated On: January 18, 2017)

The Long-Term Price-Earnings Ratio

Abstract:

The price-earnings effect has been thoroughly documented and widely studied around the world. However, in existing research it has almost exclusively been calculated on the basis of the previous year’s earnings. We show that the power of the effect has until now been seriously underestimated, due to taking too short-term a view of earnings. We look at all UK companies since 1975, and using the traditional P/E ratio we find the difference in average annual returns between the value and glamour deciles to be 6%, similar to other authors’ findings. We are able to almost double the value premium by calculating P/E ratios using earnings averaged over the last eight years. Averaging, however, implies equal weights for each past year. We further enhance the premium by optimising the weights of the past years of earnings in constructing the P/E ratio.

Core Idea:

The paper finds that multiple years of earnings are a better predictor of returns than the traditional one-year P/E, and that the average of the earnings over of the previous 8 years (EP8) is almost twice as effective as using last year’s earnings (EP1). The concept used is similar to Robert Shiller’s Cyclically Adjusted P/E or “CAPE,” which compares historical S&P earnings from the previous 10 years to current market prices. The idea is that looking at the longer-term record of some fundamental signal “normalizes” it, and reduces the noisiness of recent observations.

This paper examines UK data from 1975-2003.

Key results are as follows:

  • Adding more years increases the power of the P/E ratio to predict returns, although not monotonically.
  • The Sharpe Ratio was particularly good for the EP7 and EP8 value deciles, offering an excess return to standard deviation ratio more than twice as high as that for the EP1 glamour decile.

Alpha Highlight:

2014-10-03 14_09_52-0Value Reseach Recap.pptx - Microsoft PowerPoint (Product Activation Failed)
The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request

 

Note that this paper uses data from the UK; by contrast, Gray and Vogel 2013, using data from the US, were unable to replicate these results. Gray and Vogel show that longer term ratios do not work for US Equity, and that one-year valuation metrics are superior. Thus, it may be that the observed effect is not robust across markets.


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About the Author

Wesley R. Gray, Ph.D.

After serving as a Captain in the United States Marine Corps, Dr. Gray received a PhD, and was a finance professor at Drexel University. Dr. Gray’s interest in entrepreneurship and behavioral finance led him to found Alpha Architect. Dr. Gray has published three books: EMBEDDED: A Marine Corps Adviser Inside the Iraqi Army, QUANTITATIVE VALUE: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors, and DIY FINANCIAL ADVISOR: A Simple Solution to Build and Protect Your Wealth. His numerous published works has been highlighted on CBNC, CNN, NPR, Motley Fool, WSJ Market Watch, CFA Institute, Institutional Investor, and CBS News. Dr. Gray earned an MBA and a PhD in finance from the University of Chicago and graduated magna cum laude with a BS from The Wharton School of the University of Pennsylvania.


  • sx

    Thanks, Wes! I know that Alpha architect has been a big fan of academic research, and has a strong belief in quant equity. And I was wondering if you can talk how Alpha architect generally select and cite a reference given the fact that every one has a bias?

  • Steve

    “We further enhance the premium by optimising the weights of the past years of earnings in constructing the P/E ratio.”

    Hmmm…

  • Michael Milburn

    Steve, excluding more exotic weightings, they say the best way they found is averaging current earnings + earning from y8 and calcing PE based on current price. Interestingly adding recent years earnings doesn’t help much (actually probably hurts due to reversion), but adding in earnings from years farther back (maybe beyond 5+yrs) seemed to give a bit of edge.

  • Michael Milburn

    from paper: “This is an important and counter-intuitive result: calculating your P/E ratio by dividing today’s price by the earnings from five, six, seven or eight years ago gives a better predictor of returns than the usual P/E ratio.”

    Is there any plausible mechanism that could make older data more valuable than fresher data? Is this some kind of recency bias carried out on 5+yr timescales?

  • Remmelt

    Hi Wes, something has been on my mind for a while.

    Why can’t I find studies which use absolute P/E, P/TBV, EV/EBIT, 12-month return, etc. values and diversifies a portfolio amongst a set number of stocks with, for example, an EV/EBIT of >6, >7, >8 and puts the rest in cash?

    The same for valuing the market (why not EV/EBIT all stocks and chart the CAGRs/ Sortino ratios / drawdowns vs. the average cap-weighted multiple). This seems to already be done when a linear regression is done for historic CAPE or Tobin Q ratios / vs market returns (though the repeatability of this can be doubted I guess).

    Would this be statistically unreliable (e.g. a mild form of data-mining)? Personally, I was thinking that this intuitively makes more sense than deciles and quartiles and is a strategy that many well-performing value-investors seem to be approximating.

    My apologies if you’ve already covered this somewhere or if it shows my inexperience.

    And thank you for all the great analytical work you and your team posts. I enjoy the humility shown with human biases & in the finding of trends in historic returns.

  • Rellen,

    http://www.alphaarchitect.com/blog/2013/02/26/graham-quantitative-value-tool-new-free-feature/#.VGTFsvnF9MU

    Graham outlines a strategy similar to the one you mention–a hard cut off on price paid. That strategy earned 15% according to Graham. We’ve updated that research from 1972–> and also found that it returns 15%. Of course, the volatility is insane, but the returns are definitely there. Whether you do a “cutoff” approach of a decile approach, you’ll end up in approximately the same place and have the same takeaway–value investing works, but the volatility is intense and the tracking-error is high. No free lunch.

  • Remmelt

    Thank you very much. I recall now having seen this in the value screen tools. It’s interesting to see that both approaches work with similar returns even though one differs in max. multiples and the other doesn’t.

    To me personally the volatility and tracking error seem to be more psychological (though not with a short investing horizon) than actual risk, but I can definitely see how this would be excruciating at times.

    Kind regards,

    Remmelt