value and opportunity

After my previous posts about the “Boss Score”, I think I had lost some of the readers. So I try to show with some hopefully interesting examples how the score works in more detail.

Low Price /Book ? – example Coca Cola

One reader commented that the strategy is designed to look for low P/B stocks. This is not the case. Lets have a look at CoCa Cola, maybe one of the most famous Warren Buffet / Moat style investments.

Coca Cola trades at a P/B of 5.2 and a PE of ~20, so how does this work in the screener ? In the current “simple” version without share repurchases, the database shows the following 10 year history:

	Book per Sh	Div	TROE %
2001	4.57
2002	4.78	0.8	22.0%
2003	5.77	0.88	39.3%
2004	6.61	1	31.9%
2005	6.90	1.12	21.3%
2006	7.30	1.24	23.7%
2007	9.38	1.36	47.1%
2008	8.85	1.52	10.6%
2009	10.77	1.64	40.1%
2010	13.53	1.76	42.0%
2011	13.98	1.88	17.2%

This results in a 10 year average TROE of 29% and a standard deviation of 9.8%. If we plug this into the CAPM formula, Coca Cola gets an adjusted (fundamental) CoC of 5.4%. Assuming now a constant 29% ROE based on a book value results in an assumed 4.21 USD constant earning per share going forward.

Divided by the 5.4% CoC, the “fair Value” of Coca Cola turns out to be ~74.80 USD, -0.8 below yesterdays close. The corresponding “boss Score” is -0.01, indicating a “fair valuation“.

So one clearly sees that the model is reacting very positively on high ROEs, solid balance sheets and stable owner’s earnings. However by design, any future growth is not included. So CoCa Cola might be even a great investment if one is sure that they will grow going forward.

Low P/B Financials – Example Munich Re

Munich Re has become a favourite for many conservative investors. It trades below book, has a low P/E and pays a good dividend, so what could go wrong ?

	Book	Div.	“Owner Earnings”	Stated earnings
2001	104.14
2002	74.40	1.19	-28.55	5.78
2003	82.76	1.19	9.55	-2.25
2004	88.38	1.25	6.87	8.01
2005	105.01	2.00	18.64	11.74
2006	114.54	3.10	12.63	15.05
2007	120.09	4.50	10.05	17.90
2008	106.42	5.50	-8.17	7.74
2009	114.89	5.50	13.97	12.95
2010	126.31	5.75	17.16	13.06
2011	129.86	6.25	9.81	3.94
Total			61.9471	93.93

If we look at the comparison of “owner’s earnings” and stated EPS, we can see the problem clearly: EPS only reflect part of value creation or destruction. Munich Re is booking a lot of negative stuff directly into equity, thanks to the benefit of modern IFRS accounting.

Over the last 10 years, Munich Re reported a total of ~93 EUR in EPS, but summing up equity and dividends, the owner only received 62 EUR. This in turn leads to a relatively miserable TROE of 5,1%. In the “Boss model”, together with the relatively high volatility, this is considered as “value destruction” and the “fair value” of Munich Re if they continue like that is something like 15 EUR.

As I have mentioned, this should be not considered to be a hard price target. As Winter pointed out, one could also argue for some general “mean reversion”, however this is not the goal of the exercise.

I am looking for boring companies with a historical good track records of value creation and Munich Re is definitely not such a company.

Greek Stocks: Example Jumbo SA

Some Greek stocks score incredibly well, for instance Jumbo SA

	BV	Div	Oes	TROE
2001	0.45
2002	0.55	0.04	0.15	29.1%
2003	0.69	0.05	0.19	30.0%
2004	0.91	0.07	0.29	36.6%
2005	1.39	0.09	0.57	49.5%
2006	1.83	0.12	0.56	34.6%
2007	2.35	0.16	0.68	32.5%
2008	2.93	0.20	0.79	29.8%
2009	3.48	0.23	0.78	24.3%
2010	4.03	0.19	0.73	19.5%
2011	4.26	0.19	0.42	10.2%

Despite the relative decline in 2011, the company still scores extremely well in the model, as to a certain extent the 10 year average would imply some kind of “mean reversion”. In any other country, Jumbo might be just the boring stock I would be looking for, but being a Greek stock, it is more like the “hot potato stock” (TM rueckzugsgut) I want to avoid.

In the case of Greece, one has to judge potential future developments. So any Greek investment would be definitely a “special situation” and not part of my “Boring sexy stock” universe.

Summary: As expected, the score should not be used for automated investment decision but adds some interesting historical information to the “standard” set of value indicators. The three examples (Coca Cola, Munich Re and Jumbo) show that results seem to be within expectations but should be taken as a starting point only.

At the moment, I am still building up the database, I hope I will be able to show some more comprehensive tables later this week.

As already announced in the previous post, let’s have a look what results we get for the German DAX companies, sorted by the Trailing 10 year “boss score”:

Name	Price	Book	“Boss Score”
RWE AG	29.72	31.38	0.89
DEUTSCHE LUFTHANSA-REG	8.43	16.57	0.65
K+S AG-REG	33.75	16.90	0.53
MERCK KGAA	77.15	48.72	0.44
FRESENIUS MEDICAL CARE AG &	53.15	28.75	0.30
METRO AG	23.99	19.74	0.24
ADIDAS AG	59.43	26.33	0.01
DEUTSCHE BOERSE AG	39.51	17.52	-0.07
BAYERISCHE MOTOREN WERKE AG	62.17	43.42	-0.10
E.ON AG	15.10	19.58	-0.13
DEUTSCHE POST AG-REG	13.02	9.45	-0.15
BASF SE	57.28	27.62	-0.19
VOLKSWAGEN AG	121.40	130.55	-0.21
SAP AG	47.28	10.95	-0.22
HEIDELBERGCEMENT AG	36.04	65.06	-0.34
MAN SE	79.59	41.25	-0.36
FRESENIUS SE & CO KGAA	75.10	37.28	-0.41
SIEMENS AG-REG	66.46	35.92	-0.53
LINDE AG	122.45	68.65	-0.54
HENKEL AG & CO KGAA VORZUG	52.98	20.76	-0.60
MUENCHENER RUECKVER AG-REG	102.85	136.28	-0.71
DAIMLER AG-REGISTERED SHARES	37.85	38.81	-0.75
BEIERSDORF AG	52.20	12.39	-0.77
DEUTSCHE BANK AG-REGISTERED	29.08	59.58	-0.81
BAYER AG-REG	50.98	24.19	-0.87
ALLIANZ SE-REG	75.81	106.62	-0.95
DEUTSCHE TELEKOM AG-REG	8.75	8.13	-1.00
INFINEON TECHNOLOGIES AG	6.33	3.15	-1.17
COMMERZBANK AG	1.42	4.22	-2.51

It is interesting to see that only 7 companies are above 0, which would indicate that they are undervalued.

Not surprisingly, financials including Insurers look relatively ugly. Also I am not surprised that we don’t see really great scores. Everything below 0.5 is not really interesting.

To a certzain extent surprising, Henkel and Beiersdorf are not performing really well. For Beiersdorf this has to do with a big drop in shareholder’s equity from 2003 to 2004 which creates volatility plus the fact that market value is already 4 times book value.

Also Henkel has a much more volatile equity positions than earnings would indicate which increases volatility in the model. This might have to do with FX effects but combined with the relatively high valuation it is neither boring nor sexy.

Just as a comparison, how are the scores for some of my portfolio companies ?

Name	Price	Booc Value	10Y B-Score
INSTALLUX SA	140.00	178.16	3.11
OMV AG	22.91	34.59	2.36
POUJOULAT	132.00	124.66	2.00
TONNELLERIE FRANCOIS FRERES	30.05	29.46	1.88
AS CREATION TAPETEN	25.19	33.71	1.79
BUZZI UNICEM SPA-RSP	3.38	15.47	1.37
HORNBACH BAUMARKT AG	24.93	25.54	1.16
EVN AG	9.32	16.44	0.62
FORTUM OYJ	15.43	11.65	0.57

As one can see, for some of the stocks, the “Boss Scores” are much much higher.

At the moment I am building up a database and will then post from time to time interesting “Boss” stocks. But remeber: This is only one specific way to look at the stock and should be used as starting point only.

(More to follow)

After introducing the goal of the Scrrener / Score with the last post, let’s jump directly into the calculations:

Building the model – Step 1: Total Return on equity

Before starting to build the model, one has to define how to identify a stable, value adding business. One could use many variables, past earnings, free cashflows etc.

I personally view the long term developement of shareholders equity (including dividends and buybacks) as the best indicator if true “value” was created. This is of course not my original idea but essentially how Warren Buffet is reporting his yearly results at Berkshire.

In the times of modern IFRS accounting, one should mention that EPS (adjusted for dividends and buy backs) does not have to be equal the developement of equity from year to year. The real number usually is hidden on the second page of the P&L under “comprehensive income” which includes all kind of effects which get booked directly into equity (I.e. defined benefit pension plan valuation changes etc.)-

As comprehensive income is not very well maintained in the bloomberg historic database, I calculate “Total return on equity” with the following “basic” equation:

Total Return for (t) = Equity per share (t) – Equity per share (t-1) + Dividend paid (t)

A little bit trickier are capital increases and stock repurchases. As long as they are executed at book value, nothing changes on a per share basis. However if they are executed belw or above one will have direct impact on the per share equity and should be adjusted.

For the time being, I will stick with the “basic” formula and adjust on a case by case basis. In general I would assume that shares with significant capital increases or massive share repurchase programs don’t fit my “boring but sexy” category anyway.

The final computation than is relatively easy:

Total Return on Equity % (t) = Total return on Equity (t) / Equity (t-1)

If I do this for 10 years for example, I get TROE’s for those 10 years. With those 10 Yields, I can then calculate the average TROE in %

So the result of Step 1 is: Average Total return on Equity for period (t; t-x) where X can be 10 or 5 or any other period.

In theory the following applies: The higher the average TROE the better.

Step 2: Quantifying business volatility

The TROE average itself does not mean a lot. If we have for instance a company which has 20% TROE in one year and 0% in the next year, the average TROE will be the same as a company which shows 10% in both years.

As I am looking for “boring” companies, I have a high preference for stable TROEs. In contrast to classical CAPM, I will completely ignore stock market volatility (“Mr. Market”) and focus only on fundamental volatility.

So in order to account for fundamental volatility, I will use the standard deviation of the single period TROEs calculated above.

If we calculate the standard deviation of the TROEs, we can then in a next step calculate something similar to a Sharpe ratio which I would call the “fundamental sharpe ratio” for a company which is:

Fundamental Sharpe Ratio = Average TROE (t;t-x) / standard deviation TROE (t,t-x)

As an example, I have calculated those numbers for 4 random German DAX companies:

	Avg 10 Y TROE	10 Y std. dev	Fundamental sharpe
BASF SE	12.6%	8.1%	1.5
ADIDAS AG	17.7%	12.1%	1.5
BAYER AG-REG	5.4%	13.2%	0.4
BAYERISCHE MOTOREN WERKE AG	11.5%	9.7%	1.2

We see some significant differences here. On a first look, BASF and Adidas look very attractive, whereas Bayer looks rather bad. However, the fundamental Sharpe Ratio says nothing about how the volatility of the results is related to the valuation of the stock.

Step 3: Valuation model

In order to determine if a stock is attractively valued compared to the volatility of its business model, we have to build a simplified valuation model.

For the Boss Score I assume the following:

– the company will earn constantly its average past TROE going forward (without any growth) based on its current book value

So for Adidas for example: Adidas had a book value of 26.33 EUR and a average TROE of 17.7%, I will assume (26.33*17.7%)= 4.66 EUR per share for every year in the future, howver on a constant basis without any growth. This is somehow a similar perspective to the “EPV” from Greenwald.

In order to come up with a real value, I have to discount the future cashflows with somthing. And here comes the trick:

I use the CAPM formula to determine the discount rate, but intead of the market based “Beta” factor, I use the “fundamental Sharpe ratio” to determine the final equity ratio. I am not sure if this is mathematically correct in any way, but the intuitive idea is that the better the relationship between TROE and volatility of the TROE, the lower the discount rate.

As we all (hopefully) now, the CAPM calculates teh discount rates in the following way:

Discount rate (x) = risk free rate + Beta x (Equity market premium)

For the “Boss Score”, this changes into

Discount rate (x) = risk free rate + (1/fundamental sharpe ratio) x (Equity market premium)

With the discoutn rate we can then easily calculate the “intrinsic value” of any share under our model which is:

Intrinsic value = Assumed constant Profit / Model discount rate

As a final step, in order to have a direct relation to the current market Price, the “Boss Score” is then calculated the following way:

Boss Score = (Intrinsic Value / Market price) – 1

The final Boss Score can be interpreted the following way:

Boss Score > 0: Stock is based on the model undervalued

Boss Score < 0: Stock is based on the model overvalued, does not earn its cost of capital

The higher the Boss Score the better.

Before actually applying the screen to “live” data, it might make sense to define expectations in order to be able to “test” the outcomes of the “Boss Sore”. I would expect that (among others)

– companies with high leverage and / or cyclical business models will score relatively badly
– banks should score badly
– companies which a lot of one off write offs should score badly
– companies which earn below their cost of capital or which are in terminal decline should score badly
– “boring” comanies with stable returns and low P/B should score well
– the screen should bring up companies which might not show up in other screens

In the next post I will test the “Boss Score” first with the German DAX companies to see if the results make sense.