Monthly Archives: May 2012

EVN AG – Cheap stock and good news

In an interview, Steve Romick from FPA said something like” You can have either good news or cheap stocks”.

In the case of “core value” stock EVN AG it seems you can have both.

In the half year report issued today, they report significantly higher profits (1.16 EUR per share against 1.04 EUR previous period).

And this despite only so-so numbers from electricity generation.

The “kicker” comes from one of the famous “extra assets” EVN is hiding on its balance sheet, a company called “RAG”, short for “Roh├Âlaufsuchungsgesellschaft”. This Austrian “on shore” oil upstream company seems to do quite well:

The main reason for this improvement was the increased income from investments in equity accounted investees, in
particular the higher earnings contribution from RAG, which rose by EUR 21.0m.

It looks like my valuation in my previous (German) replacement value analysis was much too conservative.

In the last few years, Q3 and Q4 for EVN were :

2008: -0.04 EUR per share
2009: +0.52 EUR
2010: -0.05 EUR
2011: +0.015 EUR

So if we assume a flat H2, we have a P/E of 8.3 which I find is still cheap compared to the quality of the Balance sheet.

Additionally they announced a 1 mn shares repurchase program (~0.55% of outstanding stock). Not much, but increases the total “shareholder yield” which we know now from O’S seems to be an important factor in the long run.

The stock chart doesn’t look pretty, but in this case I don’t care too much as the fundamentals are still strong:

All in all, EVN seems to be the cheap boring stock, howver with good news. So “strong hold” for the time being.

By the way, I think Verbund is now interesting as well. So I am actually considering adding some Verbund stocks to the portfolio as well.

Book Review: O’Shaughnessy – What works on Wall Street (4th edition)

A first remark: I haven’t read the previous editions and I am a maybe biased active value investor ­čśë

For many years, O’Shaughnessy’s book “What works on Wall Street” has been the Bible of many quantitative value investors who wanted to avoid analysing single companies and prefer an automated startegy to select stocks.

The book starts with some chapters loosely summarizing current behavioural finance knowledge which implies that human selection is inferior to automated systems.

For the large quatitative part of the book which follows, he seems to have used a new data set on US equities which wasn’t available before which is going back to 1926. He clearly lays out the methodology, with the major features being

– avoiding illiquid small caps

equal weighting of stocks in the portfolio (we’ll come to that one later !!!)

– reinvesting dividends

– enhanced rebalancing (not only on July 1st per year but the average of 12 annually rebalanced portfolios starting each month of the year)

– no transaction costs assumed

He then uses his data to run many different strategies. Some of the most interesting results for me were:

– small caps outperform large caps and indices pretty consistently by 1-2% p.a.

– low P/E stocks (cheapest decile) outperform by almost 5% p.a., interestingly with a lower beta

– low EV/EBITDA works even better as single factor model (5,5% p.a. out-performance)

– low Price/Cash Flow works, but “only” around 3.5% p.a. out-performance. Price to free cashflow and Price to operating cashflow work slightly better but not as good as EV/EBITDA

– the “old favourite” price to sales does not really work well (only 1.5% p.a.)

– Price to book: DOES NOT WORK for the cheapest decile !!!!

– Dividend yield DOES NOT WORK

– however stock buy back yield works with ~3% p.a. excess return

– Stock buy back yield and dividend yield work better, 3.3% p.a.excess return

– certain accounting ratios work also well, such as low accruals (2.8%), Asset to Equity, asset turnover etc.

– composite accounting ratios (4 factors) work even better, close to 5% p.a.

– composite ratio with only the 25 best stocks scores even better (7% p.a. out performance)

– composite Value factor (P/B, P/E, P/S, EBITDA/EV, P/CF) with 5.8% p.a. out-performance

– Earnings changes, profit margins and ROE DO NOT WORK

– Price momentum (6 and 12 months) works, with 2-3% p.a.

combining value and price momentum works best, some strategies yielding 10% p.a. excess returns or more


I don’t want to sound arrogant, but from earlier discussions I knew that O’S favoured the P/S ratio in the prior editions. I always thought that this doesn’t make any sense because then you end up with a portfolio of supermarket stocks and wholesale companies.

It is also not surprising that P/B doesn’t work if you don’t adjust for debt. So no wonder, EV/EBITDA does a much better job. But this is something many active value investors know without having to go through 90 years of data.

For any active investor it is also no surprise that it is better to look a various factors as single factors can always be influenced by certain special effects. So welcome to the club, Mr. O’S !!!

Maybe in his 5th edition, O’S then starts to look at the historical developments, who knows ?

For me, the relevance of price momentum is still difficult to really understand but I am willing to learn !!!!

Conceptual issue: Equal weighted performance

I have one big conceptual issue with the whole book: as described in the beginning, O’S just briefly notices that he uses equal weighted portfolios. He doesn’t test if this alone has an impact on the performance of the strategies.

Some recent papers indicate that equal weighted portfolios themselves create significant out-performance vs. market cap weighted indices.

So we do not know for sure, how much of the out-performance of O’S strategies is due to his equal weight assumption as he benchmarks against a market cap index and not against an equal weight index.


O’S book is of course a interesting read. Many of the newer combined strategies make intuitive more sense than some of the older strategies. He also correctly states that strategies work only long term and you have to avoid market timing at all costs !!!

Many investors will underestimate what it means to invest in a mechanical strategy which underperforms for 3 or more consecutive years.

Unfortunately, the conceptual issue with the equal weighted portfolio takes away a lot of my personal “trust” into those mechanical strategies.

For me the key take aways are:

1. Any more or less fully invested value startegy with some basic analysis will perform quite well against the general market

2. Also the most famous mechanical models can become outdated


4. Price momentum should not be ignored

Introducing the Boss Score part 4 – How it works in practice (KO, MUV2, Jumbo)

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

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.

Position sizing and cash quota

Especially among active Value investors, there is a big debate about diversification or concentration of portfolio investments. Within the comments we were debating this already quite intensively, I also commented on Stephan’s blog why I think 30% of the portfolio in three Greek stocks is too much.

I would divide the the argument into two camps:

1. The “Buffet / Munger camp”: If you have a good idea, you should invest as much as possible into those 3-5 ideas. Reader Setla provided as proof Berkie’s balance sheet from 1995, where the top 5 investments made almost 100%.

2. The “others”, like Graham, Walter Schloss, Klarman, FPA, Tweedy etc. which usally construct portfolios with 20-50 stocks, in the case of Graham and Schloss sometimes even more.

My view on this is the following: There is no right or wrong, position sizing depends on many factors. Some of the more important ones are:

A. Type of stock

It makes a big difference in my opinion if you prefer “bufffet” style shares like Nestle, Coca Cola, Gillete etc. or small caps like SIAS, Installux, Poujoulat or Hornbach.

Nestle and Coca Cola for instance are global companies active in almost every part of the world and in different segments. If one country or even a continent doesn’t perform you still have the other 4 continents. So they are stocks which are already diversified theselves.

If I look at my portfolio, my small cap stocks are not divdersified at all on a stand alone basis. SIAS for instance only runs Northern Italian motorways or Poujoulat is highly dependent on French wod pellet heating. So those stocks are not diversified at all but have very specific risks.

The same applies for Graham/Schloss type of Net-Nets or other “deep value” stocks where on an individual basis a lot could go wrong, but within a diversified portfolio you could expect significant outperformance.

It would be therefore financial suicide to invest only into 3 or 5 of those small cap stocks as very singular events can wipe out significant amounts of the portfolio.

B) Control position

Many investors who try to invest like Warren Buffet, forget one important thing: Buffet is always in some kind of control position.

Either he is actually a direct control investor (GEICO, Iscar etc.) or he is the largest investor in a public company. You can imagine, if Warren Buffet calls Coca Cola, he will not be put into the endless phone loop but transferred directly to the CEO.

So if he has tied up a lot of money in one stock, he can influence the company to a certain degree if he doesn’t like what they are doing. And make now mistake, Warren seems to be a nice guy on the outside, but he can get quite nasty if things don’t go his way.

Other examples for less diversified control investors are for instance private equity funds which usually invest into 5-10 control investments per fund but with full control over management.

As a private investor, one is definitely no control investors. I personally do not trust ANY company management enough to put a very large amount of my hard earned money into it.

C) Personal risk tolerance

One thing: Not every investor has the same risk tolerance or risk preference. Making money in the stock market long term means that you have to be able to stay in the game.

If you are very young and run a small portfolio (say a couple of monthly salaries), you can always get back into the game by saving part of your salaries and start over again. A pensioner who relies on his portfolio to generate a large anount of his income does not have this “luxury”.

For someone too rich to bother (Warren, Charlie ?) the same applies as for the young guy. He/She can take more risk.

For me personally, the approach of investing a max of 5% of the portfolio has worked quite well in the past. I also found it helpful to start with a “half” position of 2.5% first and then increase if things go fundamentally the right way. I have no problem, letting the position grow due to performance up to 10%, by then I will decide if I take some money of the table.

Cash Quota

There are as many opinions on cash as there are investors. Interestingly Warren Buffet of course is famous for holding always cash to be prepared for crisis investments, as well as very clever investors like Seth Klarman or FPA (Bob Rodriguez) which hold large amounts of cash if they think the market is generally overvalued.

For me, a “general” target cash quota of 10% has worked quite qell in the past. Due to my investment style ( inc. Special situations ect.) I normally have continuous cashflows into the portfolio. On the other hand I have usually some stocks in my watchlist in which I want to invest at a certain price without having to sell one of my other position.

So effectively, my cash quota is “oscillating” around 5-15% depending on specific events and valuations.

I think a certain cash quota is necessary to remain flexible. Howevr one should avoid increasing or reducing cash based on one’s market expecation. At least in my experience I am not able to add value consistently through this kind of “tactical” asset allocation.


I think both, for position sizing and cash quota, there is no “one fits all” strategy. In my opinion, many value investors make the mistake trying to apply the principles of one very succesful “guru” to any situation. It might also be difficult to copy any “Guru” because the “Guru” might have a very different kind of risk tolerance and risk capacity than the ordinary investor.

I do not want to give explicit advice, but most investors should NOT try to construct 3 or 5 stock portfolios without cash reserves as the probability of NOT SURVIVING the next crisis is quite high, no matter how “safe” the stocks look like.

Weekly links

Value investor Prem Wats (Fairfax) under fire for a murky deal in the past

Now it is official: Sino Forest was a fraud. Many interesting details provided.

csinvesting on a classic “pump and dump” scheme, Sun Peaks Ventures. Includes a good explanation how those schemes work in general.

Nate at Oddball on French (deep) value stock Nexaya

Bronte on shorting Santander US preferreds. However, I think its not only the grandmothers who are insane….

Great Sony sum-of-parts analysis from the Brooklyn investor. Great value blog by the way.

Introducing the “Boss Score” part 3 – First test with DAX 30 and own portfolio

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
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
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
BEIERSDORF AG 52.20 12.39 -0.77
BAYER AG-REG 50.98 24.19 -0.87
ALLIANZ SE-REG 75.81 106.62 -0.95
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
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)

Introducing the “Boss Score” part 2 – building the model

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

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.

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