Price Earnings Multiple: An exception to Occam's razor?

I entered my MBA specializing in Finance at S P Jain Mumbai in 2008 just a quarter before Lehman came crashing down. One of the first classes in Finance was related to Financial Statement Analysis and in one of the sessions our Professor said something which set indelibly in my mind - Every company gets the PE it deserves. A low PE always doesn't mean undervalued and a high PE doesn't always mean overvalued.

Sunset from the living room

The usual definitions and explanations are not required for this note. I would recommend to flip over the CFA chapter on multiples for that or perhaps refer to any standard text such as by Professor Damodaran. In this post we will try to look at a general landscape of PEs in India and peek into two hypothesis - 

  1. Buying a stock at low PE yields a better stock price CAGR
  2. A high PE stock cannot give excess market returns

Since investing is more of an art and not science the answers will 'tend' to one of these states and not be absolute in nature.

Data and assumptions

There are approximately 3900 companies listed across NSE and BSE with a total market capitalization of 2.14 Cr crores. We pick a sample from this list starting from the highest market capitalization company till 5000 Cr market capitalization. We omit a few companies for which we were not able to obtain the historical PE data. There were approximately 420 companies with 5000 or more market cap and in our final sample we have 209 companies. These 209 companies make up 68%+ of the entire market cap of the listed space. This set of 209 companies includes all industries, cyclicals as well compounders. Selection is not biased but is from available data set. Although there will still be other biases for instance companies which have fallen below 5000 market cap and thus do not influence the analysis. Some companies in the 420 odd are unprofitable (approximately 52 companies) so we do not pull them into our analysis. Approximately 85 companies in the list of 420 do not have a 10 year stock return history so we omit them since the time frame we have taken for this is a long 10 years. So finally this leaves us with 273 companies from which we have data of 209 companies in our sample. Having said that the overall set of 209 companies is a good representative of the listed space. Data sources are primarily screener and for 4 companies data from either tijorifinance or tikr has been used. We used a 10 year time frame from mid May 2011 to mid May 2021. Another point to note is that these are trailing 4 quarter PEs. A better metric is forward PEs but I refrain from estimates. From a cyclical point of view we have ignored the Molodovsky effect.

General landscape

A snapshot of how companies have performed in stock price CAGR vs their PE CAGRs. The chart below summarizes the 209 companies in our sample space. The x axis is the CAGR of stock price in a frequency format, the orange bars are count of companies and blue dots are CAGRs of PE from May 2011 to May 2021.


In this period of 10 years the Nifty PE went up close to 50% (49.65% from 20.x to 30.y, but please note that in 2011 the computation methodology was slightly different from what it is now). The Nifty returns in this period was 10.66% CAGR. None of this analysis includes dividends.

11% of these 209 i.e. 23 companies has a PE CAGR which was higher than their stock price CAGR. Within these 23 companies 7 had negative stock price returns and another 7 could beat the index. Thus only 30% in this 23 set beat the index.

In the remaining 186 companies which is 89% of 209 where PE CAGR was lower than the stock price CAGR 7 companies are still loss making, and another 38 could not beat the market. In this set 25% of the stocks could not beat the market. A scatter plot below.


Interesting point to note is that 106 companies (51% of sample space) had increase in PEs over their historical median PEs over 10 years which was less than the PE increase in the Nifty 50 index. This 106 companies median stock price CAGR was 14% with 35 companies not beating the index.

Buying a stock at low PE yields a better stock price CAGR

The problem with a ratio like PE is that the word 'low' is very relative and subjective. Is PE:

  1. Low compared to its own historical PE levels
  2. Low compared to the PEs of similar/competing companies
  3. Low compared to an underlying index PE

etc. etc.

In this we look at it two ways 1) own historical PEs and 3) compared to the index. We omit 2) which is comparing to similar companies as it becomes an exercise in extreme subjectivity.

Key results

  • There was a 52% probability to lose to the index if one chose a stock whose PE was not growing as fast the index PE.
  • While there was only a 12% probability of losing to the index if one chose a stock whose PE was growing faster than the index PE. 
  • From a Bayesian perspective there was a 77% probability to be with a stock which was growing 'overvalued' compared to the index if one beat the market in the last 10 years.

The matrix is below.

Note that the evolution of the 'under/over valuation' is similar to a series over time. This analysis is essentially normalized.  

A high PE stock cannot give excess market returns

In this test we divide the sample set into quartiles based on the ratio of stock PE to Index PE at the start of analysis (in May 2011) and then look at the excess market returns of these quartiles. We use this derivative to call a stock 'high' PE at the start of the analysis.

Key results

  • There is a very high probability of 84% to beat the index if stocks in the most undervalued quartile with respect to the index is selected. In addition this quartile gives the best excess market median returns.
  • There is also a very high probability of 81% to the beat the index if stocks in the most overvalued quartile with respect to the index is selected. But this overvalued quartile has the least excess market median returns.
  • The center two quartiles give a lower probability of ~66% of beating the market.

The matrix is below.

Conclusion

How do we interpret all this? The first callout is that there is no magic rule. Somehow I feel the application of PEs without proper context and understanding of the business is a fool's errand. Secondly the method of PEs is an exception to the Occam's razor. PE makes our minds think very linearly in taking valuation calls which is not what it is supposed to be.

From the above data I tend to say that (you can disagree with me) there is a better chance to beat the market being in stocks which keep gaining in valuations at a faster rate than the index even if the stock had a high valuation to start with. The icing on the cake is to start with stocks which are valued low and gain fastest over the index. But here we go again, we are back to the starting point of this whole discussion. Not my cup of tea. Sorry.

Ciao!

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