Jae Jun

# Using the O-Metrix Score to Find Cheap Stocks with High Potential

October 08, 2012

I get a good stream of comments and requests by current users of the OSV stock analysis spreadsheet to add certain valuation tools and metrics, but rather than just adding user requests, I like to make sure that it will really benefit and adds to fundamental analysis instead of just trying to pack as much features as possible.

One interesting valuation method that came up was designed by Jeremy Siegel from his book, Stocks the for Long Run.

As far as I know, there is no official name for the valuation method, and there is only one website that uses this method and has called it the O-Metrix score.

I’ll stick with the name. So let’s go through what it is, how it is used and my verdict on how useful I find it.

#### What is the O-Metrix Score?

You know about the Piostroki F Score, Altman Z Score and the Beneish M Score. All created by Professors based upon their intense research.

The O-Metrix score too was developed by a professor. Jeremy Siegel is a professor of Wharton School of Business, and describes the O-Metrix method as well as other in his book, Stocks for the Long Run.

The O-Metrix is based upon a combination of three metrics.

A rule of thumb for stock valuation that is found on Wall Street is to calculate the sum of the growth rate of a stock’s earnings plus its dividend yield and divide by its P-E ratio. The higher the ratio the better, and the famed money manager Peter Lynch recommends investors go for stocks with a ratio of two or higher, avoiding stocks with a ratio of one or less.
We all want to buy stocks with high growth, a dividend and low price and the following equation is supposed to be able to identify such stocks.

O-Metrix = (Dividend Yield + Earnings Growth) / PE Ratio

and if you are dividend income investor, more emphasis is required for dividends, so the dividend variation is referred to as the Double Dividend O-Metrix Score.

DD O-Metrix = (2 x Dividend Yield + Earnings Growth) / PE Ratio

Going back to that quote a little higher up; “Peter Lynch recommends investors go for stocks with a ratio of two or higher, avoiding stocks with a ratio of one or less”, the above two equations can be multiplied by 5 to make the scale range from 0 to 10 instead of betwen 0-1, which makes it easier to identify and classify stocks.

The equations now become:

O-Metrix = 5 x [(Dividend Yield + Earnings Growth) / PE Ratio]

DD O-Metrix = 5 x [(2 x Dividend Yield + Earnings Growth) / PE Ratio]

EFSInvestment has provided his grading system which I’ll go by.

• 10+ : A+ Grade Stock
• 8 to 10: A Grade Stock
• 6 to 8: B Grade Stock
• 4 to 6: C Grade Stock
• 2 to 4: D Grade Stock
• 0 to 2: F Grade Stock
• <0 : Sub-F Grade Stock
The objective of the O-Metrix score is to find stocks that score above 10.

#### Hunting for a 10+ O-Metrix Stock

This took me a while to compile but based on a random search through various tickers, here is a compilation of 13 stocks that are rated in the A+ to B grade using the O-Metrix score.

Rather than just using the current PE, I took the average of the current and Forward PE.

Growth rates were taken from the Yahoo Finance analyst prediction section.

Topping the list is STX which is perfectly represents what the O-Metrix score tries to find. Stocks trading at a low PE, high dividend yield and good growth potential.

#### Potential Adjustments to the O-Metrix Formula

More testing and work will have to be done, but here are a couple of changes that could be made.

• Instead of PE, EV/EBITDA could be used.
• Could make it FCF based, but using FCF growth instead of EPS growth and P/FCF or EV/FCF instead of PE.

#### Closing Thoughts on the O-Metrix Score (For Now)

I was hesitant at first but I can see how it could be useful with some adjustments.

In the current format, I believe a lot of companies could come up incorrectly, based on how EPS has been calculated, and what the expected growth rate is, but I do see potential.

Not ready to employ it full time, but interesting enough to do some further research and testing.

Any thoughts?

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Jae Jun
Jae Jun is the author of Old School Value, a value investing blog dedicated to the Old School methodologies and teachings of the investment greats such as Graham, Buffett and Fisher. The blog deals with finding intrinsic value, fundamental stock analysis and special situations including spinoffs and merger arbitrage.

Visit Jae Jun's Website

 Currently 3.94/512345 Rating: 3.9/5 (17 votes)

Bpengelly - 4 years ago    Report SPAM
Crastogi - 4 years ago    Report SPAM
All this is good, but do we have any results from backtesting? Does it make real money, or just finds businesses in a decline.
Valu2day - 4 years ago

I don't know if Jeremy Siegel is someone who I would include in the value camp. I think you answered your own question, Jae, in your Closing Thoughts. Those would be the same concerns I would have and I would be especially wary of forward PE projections. I do like the concept of Shareholder Yield or FCF Yield mentioned above. Please don't take my comments as a negative. These are just my initial thoughts upon reading your analysis. I appreciate your article and effort. Keep up the good work!
Jae Jun - 4 years ago
All good comments. It's worth testing though and I'm doing some tests and backtesting to see whether it actually is worth pursuing as an idea.
Batbeer2 - 4 years ago
Assuming you were interested in buying a business outright, what factors would you consider?

Would you ignore LUK, BRK, DJCO, LVB, and IBM because they score worse than GNI, CALM and WHX?

I think this metric is almost useless in identifying businesses that you would want to own outright. To me, that makes it useless for selecting companies you would wish to own part of.

Just random thoughts.

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