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Historical Valuation Ratios by Industry Book


west

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Hi all.  In the last week I've finally been sitting down and reading Security Analysis.  It's great!  I wish I would have read it earlier.  It's much more modern in its thinking than I would have ever expected.

 

The problem though is much of the stuff they source is very out of date.  So you can't really look into it.  For example, in Chapter 41, Graham and Dodd talk about how the market will value companies in different industries by using different E/P ratios, saying (with a warning):

 

Different "multipliers" are used for different sorts of enterprise, but these distinctions are themselves subject to change with the changing times.

- Security Analysis, 6th Edition, p526-527

 

In the footnotes they source Common Stock Indexes by Alfred Cowles as a study of these historical ratios.  The problem is, that book is almost eighty years old!

 

Does anyone have a more modern study of industry ratio shifts?  I'd love to read about how they've changed over time.

 

Thanks in advance!

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Is the different multiplier due to investor certainty - or uncertainty of the stability of earnings in various industries? Or is the message that these multipliers are just tradition since a shoe company and a biotech company that have the same profitability for many years should technically be worth the same to an investor.

 

 

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Examples of Graham's multipliers can be found in Stock Selection for the Enterprising Investor: the Appraisal Method section 1949 Intelligent Investor pages 150 to 151.  Graham lays out a range of multipliers of 10 to 20 based upon "quality".  This is similar to the approach I use to identify cheap stocks amongst particular industry groups.  In later editions, he develops the 8.5 + 2G formula to estimate a "fair" multiple

 

Packer

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Examples of Graham's multipliers can be found in Stock Selection for the Enterprising Investor: the Appraisal Method section 1949 Intelligent Investor pages 150 to 151.  Graham lays out a range of multipliers of 10 to 20 based upon "quality".  This is similar to the approach I use to identify cheap stocks amongst particular industry groups.  In later editions, he develops the 8.5 + 2G formula to estimate a "fair" multiple

 

Packer

 

Thanks Packer.  I guess I was more interested in looking how multiples have shifted over time than how to use them or come up with them for valuations.  I wanted to understand how investor psychology has shifted over time so I can (hopefully) better understand where different industries are at now in terms of that psychology.  For example, I don't know, but I have strong feeling that telecom ratios were very high in the late 90s and early 2000s.  And since then they've only drifted down?  It would be interesting to see, say, if we're at a nadir, or anywhere close, for telecom/cable multiples.

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Examples of Graham's multipliers can be found in Stock Selection for the Enterprising Investor: the Appraisal Method section 1949 Intelligent Investor pages 150 to 151.  Graham lays out a range of multipliers of 10 to 20 based upon "quality".  This is similar to the approach I use to identify cheap stocks amongst particular industry groups.  In later editions, he develops the 8.5 + 2G formula to estimate a "fair" multiple

 

Packer

 

Thanks Packer.  I guess I was more interested in looking how multiples have shifted over time than how to use them or come up with them for valuations.  I wanted to understand how investor psychology has shifted over time so I can (hopefully) better understand where different industries are at now in terms of that psychology.  For example, I don't know, but I have strong feeling that telecom ratios were very high in the late 90s and early 2000s.  And since then they've only drifted down?  It would be interesting to see, say, if we're at a nadir, or anywhere close, for telecom/cable multiples.

 

I think the best way to find this is to get the historic M&A multiples per industry over the years.  Industry P/E's trend towards M&A multiples.  I have no idea where to get this data.

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