In the old legend the wise men finally boiled down the history of mortal affairs into the single phrase, "This too will pass." Confronted with a like challenge to distill the secret of sound investment into three words, we venture the motto, MARGIN OF SAFETY.

- Benjamin Graham, 1949

The Rationale For Businesslike Quantitative Value Investing

August 2013

1.    Introduction

My journey in the financial world started at age 17 when, for the first time, I read Benjamin Graham’s The Intelligent Investor (edition 1949). It took approximately ten years of readings in finance and economics, research and experience to truly understand and appreciate the enormous added value of the book for equity investors.

By far the best book on investing ever written.
Warren Buffett

In Security Analysis (1934) but even more so in The Intelligent Investor Benjamin Graham lays both the technical and psychological foundations of what has become known as value investing. From the book the reader comes to understand that Grahamite value investing involves buying financially sound companies at significantly below average valuations.

In the following paragraphs, from numerous perspectives, I will briefly explain why a businesslike quantitative value investing approach is one of the soundest approaches to long-term wealth accumulation.

2.    The Business-Economic Perspective

In The Intelligent Investor Graham sets forth two dangers related to investing in growth stocks. Growth companies that have realized high earnings growth rates over the past years and/or companies with good earnings prospects usually quote at correspondingly high valuations. In the most optimistic scenario the growth firm succeeds in meeting the high hopes, but even in this condition chances are high that the growth stock will realize an inferior stock return, due to the fact that the growth investor has paid in full (and perhaps overpaid) for the expected prosperity. When the scenario is less rosy the growth firm is confronted with an earnings growth rate showing a significant slackening. High earnings growth rates attract competition, which results in systematically lower sales growth and lower profit margins. Very few companies truly live on an economic island. High ex ante valuations combined with slackening and disappointing earnings growth rates usually result in decimating the share price of the growth stock and consequently inferior stock returns (see also “The Behavioral Perspective”).

This second warning against growth investing is supported by the research paper “The Level and Persistence of Growth Rates” by Chan, Karceski and Lakonishok (2003) published in The Journal of Finance. The authors document that past earnings growth rates cannot be considered to be a reliable guide to future earnings growth; past above median earnings growth rates are no guarantee for consistent future above median earnings growth. Their findings are consistent with the economic intuition where above average earnings growth rates are skimmed off due to competitive forces. The researchers consequently caution against extrapolating past success in earnings growth into the future and paying high valuation multiples, in accordance with Benjamin Graham’s warnings in his discussion on the adoption of a growth stock program.

In 2000 when the Internet period reached its peak, the same authors published the study “New Paradigm or Same Old Hype in Equity Investing” in the Financial Analysts Journal. At the time they correctly warned that the valuations of many technology- and/or internet-related companies could not be supported by underlying business fundamentals, i.e. as reflected in their sales and earnings growth rates. In November 1999 Chan, Lakonishok and Karceski document that 25 percent of the 100 stocks with the highest market capitalizations traded at price-to-sales multiples above 7! From the March 2000 high, the Nasdaq subsequently tumbled more than 75 percent to a low of approximately 1,175 points. Even today the technology-related index is almost 30 percent in nominal terms below its 2000 all-time high. The episode was again a perfect example on how dangerously high price levels translate into permanent losses for investors.

Consequently, from a business-economic perspective I conclude that it is advisable not to overpay for future growth expectations as reflected in traditional valuation measures such as price-to-book, price-to-sales and/or price-to-earnings ratios. By adopting a quantitative value approach, investors automatically avoid companies with lofty valuations.

3.    The Empirical Perspective

Many studies have documented the attractive returns to value stocks. In the academic literature value stocks are defined as stocks with low price-to-book, price-to-sales, price-to-earnings, and/or price-to-cashflow ratios without, it should be noted, taking into account the financial strength or fundamental health of the company (see also “The A Priori Perspective”).

Recently I have updated the study titled “Value and Growth Investing: Review and Update” by Chan and Lakonishok (2004) from the Financial Analysts Journal. The graph below shows the ten-year real total returns to value stocks and growth stocks over the 1980-2012 period using the following methodology: at the end of May non-financial, large-cap US stocks are annually sorted based on the aforementioned four valuation measures. Subsequently stocks are divided into equally-weighted decile portfolios and portfolio returns are computed over a one-year period. The final bar in the graph below shows the average ten-year real total return for both value stocks and growth stocks over the 1980-2012 period. The first bar indicates that over the May 1970 – May 1980 period value stocks realized a real total return of 122 percent. Growth stocks lagged with a real total return of 25 percent over that same ten-year time period.

-

-

Value stocks (decile 1) outperform growth stocks (decile 10) in 32 out of 33 ten-year periods. Please note that even in the one ten-year period of underperformance, concentrated around the Internet period, the ten-year real total returns to value stocks still can be considered to be very attractive (see also “The Agency Perspective”).

4.    The Behavioral Perspective

A number of studies try to explain the long-term outperformance of value stocks vis-à-vis growth stocks. According to Benjamin Graham in The Intelligent Investor the inferior returns to many growth stocks can be explained by overoptimistic growth expectations as reflect by their dangerously high price levels. A research paper by Skinner and Sloan (2002) published in the Review of Accounting Studies with the subtitle “Don’t let an earnings torpedo sink your stock portfolio” provides very compelling evidence that the inferior returns to growth stocks are indeed directly linked to expectational errors about their future earnings performance. Publication of below expected earnings results in an average stock price drop of 7.32 percent for growth companies over the 1984-1996 period; for value stocks Skinner and Sloan document a drop of 3.57 percent. After taking into account this asymmetric price response, the researchers document no remaining evidence of a return differential between value stocks and growth stocks. Their findings are consistent with the aforementioned warnings by Benjamin Graham with respect to the implementation of a growth stock program. More recent evidence in this regard is provided by, for example, Arnott, Li and Sherrerd (2009) in The Journal of Portfolio Management and by Piotroski and So (2012) in The Review of Financial Studies.

5.    The A Priori Perspective

As part of the empirical perspective I emphasized that the academic literature does not take into account the financial strength or the fundamental health of a company as part of the definition of a value stock or growth stock. A lot of academic studies initially assumed that within a value or growth portfolio companies are substantially uniform in terms of business fundamentals and consequently also with respect to the underlying risk profile. Important examples of these can be found in Lakonishok, Shleifer and Vishny (1994) and Fama and French (1995). However, looking at an academic value portfolio, for example established based on the price-to-book ratio, shows that within such a portfolio there is a substantial heterogeneity with respect to corporate solvency, liquidity and profitability.

It does not matter how frequently something succeeds if failure is too costly to bear.
Nassim Nicholas Taleb, Fooled by Randomness

Based on a priori reasoning we cannot exclude that at some point in time an academic value portfolio will uniquely contain companies having very precarious business fundamentals, business fundamentals which in extreme circumstances such as The Great Depression will cause that the majority of these fundamentally weak value companies will go down, causing a permanent loss of capital for the corresponding alleged value investors. Since the exact timing of the onset of such an economic dislocation is not ex ante predictable, a businesslike value investor will definitely want to avoid those companies with significantly below average business fundamentals. By avoiding these fundamental risky companies I can guarantee that both as an investor and as a fiduciary your nights will be much more comfortable in times of financial and economic distress.

A quantitative value investing approach is the only form of safety first investing and one of the very few investment approaches that puts risk management at the heart of the strategy.
James Montier, The Tao of Investing

6.    The Agency Perspective

As part of “The Empirical Perspective” it was shown that of the 33 ten-year periods value stocks underperform growth stocks during only one ten-year period. Even in that one ten-year period of underperformance, the ten-year real total return to value stocks was still very impressive. In the following graph I consider the real total returns to value stocks and growth stocks over two-year periods. The final bar in the graph below shows the average two-year real total return for both value stocks and growth stocks over the 1972-2012 period. The first bar indicates that over the May 1970 – May 1972 period value stocks realized a real total return of 46 percent. Growth stocks outperformed with a real total return of 79 percent over that same time period. Now I find that value stocks underperform growth stocks in twelve (!) of the 41 two-year periods, the highest underperformance being more than 60 percent in the Internet period.

-

The fiduciaries of institutional investors (pension funds, insurance companies, trust and endowment funds) are traditionally subject to severe penalties for short-term underperformance relative to a broad stock index such as for example the S&P500. Being a market-cap weighted index the S&P500 is dominated by (expensive) growth stocks. Considering the possibility of short-term underperformance of value strategies, as illustrated in the graph above, professional investors consequently are sorely afraid to take advantage of the long-term outperformance of value stocks. If the institutional investors stay put and do not change their obsession with short-term performance relative to a benchmark index, the long-term outperformance of value stocks will remain available to businesslike investors who deal in value rather than in short-term (random) price movements.

Moreover my experience as fiduciary has indicated that a transparent communication vis-à-vis investors substantially helps to prevent them to concentrate on short-term performance. Both the stock selection criteria (see “The Empirical Perspective”) need to be communicated transparently and the underlying reasons for selecting the criteria clearly need to be motivated (see “The Behavioral Perspective” and “The A Priori Perspective”). In addition, the fiduciary needs to guarantee that the investment strategy meticulously will be implemented.

7.    Conclusions

In this document I explained, from numerous perspectives, the rationale for adopting a businesslike quantitative value investing approach. From a business-economic perspective investors avoid overpaying for unrealistic, over-optimistic growth expectations. As part of the empirical perspective many studies have documented the attractive long-term returns to value stocks. From a behavioral perspective we are able to explain the long-term outperformance of value stocks vis-à-vis growth stocks due to over-optimistic errors about the future earnings performance of growth stocks. In the a priori perspective I highlighted the deficiency of the initial studies on value investing in the academic literature. The majority of investors definitely want to avoid a permanent loss of capital and, as a consequence, require minimal safety margins with respect to corporate financial strength. Finally I discussed the agency perspective. I showed that over short time horizons value investing strategies can suffer from underperformance. Professional investors usually are judged based on short-term results vis-à-vis a benchmark index, which prevents them to implement (opportunisitic) value investing strategies. By focusing on value and safety rather than short-term price movements relative to a benchmark index, businesslike investors avoid the perverse psychological pressures related to the practice of benchmarking.

Overall I conclude that a businesslike quantitative value investing approach is one of the soundest approaches to long-term wealth accumulation.

8.    References

Arnott, R.D., F. Li, and K.F. Sherrerd. (2009a). “Clairvoyant Value and the Value Effect.” The Journal of Portfolio Management.

Arnott, R.D., F. Li, and K.F. Sherrerd. (2009b). “Clairvoyant Value II: The Growth/Value Cycle.” The Journal of Portfolio Management.

Chan, L.K.C., J. Karceski, and J. Lakonishok. (2000). “New Paradigm or Same Old Hype in Equity Investing?” Financial Analysts Journal, 23-36.

Chan, L.K.C., J. Karceski, and J. Lakonishok. (2003). “The Level and Persistence of Growth Rates.” The Journal of Finance, Vol. LVIII, No. 2, 643-684.

Chan, L.K.C., and J. Lakonishok. (2004). “Value and Growth Investing: Review and Update.” Financial Analyst Journal, 71-86.

Fama, E.F., and R.F. Kenneth. (1995). “Size and Book-to-Market Factors in Earnings and Returns.” The Journal of Finance, Vol. L, No. 1, 131-155.

Graham, B. (1949). The Intelligent Investor. New York, NY: HarperCollins Publishers, Inc.

Graham, B., and D.L. Dodd. (1934). Security Analysis. New York, NY: McGraw-Hill Book Company, Inc.

Lakonishok, J., A. Shleifer, and R.W. Vishny. (1994). “Contrarian Investment, Extrapolation, and Risk.” The Journal of Finance, Vol. XLIX, No. 5, 1541-1578.

Piotroski, J.D., and E.C. So. (2012). “Identifying expectation errors in value/glamour strategies : a fundamental analysis approach.” Review of Financial Studies, Vol. 25, 2841-2875.

Skinner, D.J., and R.G. Sloan. (2002). “Earnings Surprises, Growth Expectations, and Stock Returns or Don’t Let an Earnings Torpedo Sink Your Portfolio.” Review of Accounting Studies, 7, 289-312.

The making of an ultra-safe global value-oriented investment strategy with potential AUM of +$25 billion

April 2013

Coming soon !

Quantitative Value – “We are each our own worst enemy”

January 2013

In the coming weeks I will spend some time discussing parts of the book Quantitative Value – A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors by Wesley Gray and Tobias Carlisle (2013). Many elements in the book already have been discussed on this website. Since investors invariably fall victim to the same behavioral mistakes I am convinced it makes for a good exercise to go through the most important parts of the book.

One of the four pillars of this website is Old-School Value Investing: Psychology. The pillar emphasises the critical role of psychological factors in our investment decision processes. Remember: “Intelligent investing is a mental approach.” As part of this pillar we referred to the example given by Joel Greenblatt (2011) in his book The Big Secret for the Small Investor. Greenblatt indicates that the best mutual fund over the 2000-2009 period realised an annual return of +18%. Yet the average investor in this fund lost 11% annually. On page 23 of the book by Gray and Carlisle we find some further details about this example. In 2007 the concerned fund surged 80%. Investors subsequently poured in $2.6 billion. In 2008 – the year of the so-called Great Recession – the fund sank almost 50%, which is not abnormal considering the stock market crash in 2008 and the beginning of 2009. Investors pulled out more than $750 million. Said Heebner, fund manager, gave the following comment:

A huge amount of money came in right when the performance of the fund was at a peak. I don’t know what to say about that. We don’t have any control over what investors do.

In other words the average investor in the fund has consistently bought on high levels and sold on low levels. We all know that this is the perfect road to extremely low or subpar investment returns. Nevertheless investors keep making the same mistakes.

Let’s reflect for a moment on the irrational behavior of the investors. At the end of 2007 the investors who entered the fund clearly believed that the investment manager would be able to repeat the strong performance (+80% in 2007) in subsequent years. They also – most likely implicitly – assumed that the assets selected by the fund manager would continue their extraordinary performance without fully realising that the valuation of those same assets had experienced a dramatic increase, the result of which were significantly lower expected future returns. In 2008 investors left the fund believing that the return of minus 48% was representative for the future. At the same time they did not realise that the assets in the investment fund could be bought at a discount of almost 50% compared to the beginning of 2008.

The graph below shows the performance of value investing in emerging Asia over the 1995-2012 period. Over this period investors in Asian value stocks realise a compound annual return of 17.1% (before transaction costs), consistent with the results of quantitative value investing in other parts of the world over a sufficiently long period of time. Nevertheless, the period was very turbulent with subpar investment returns for the 1995-2000 and 2007-2011 periods. The graph clearly shows – consistent with other studies – that value investing requires the adoption of a long-term time horizon, implying that the approach is definitely not suited for all investors. This point was also made by Benjamin Graham (1976) in one of his latest interviews (emphasis added):

The investor needs the patience to apply these simple criteria consistently over a long enough stretch so that the statistical probabilities will operate in his favor.

GRAPH I: VALUE INVESTING IN EMERGING ASIA 1995-2012

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The above example illustrates that investors focus on completely irrelevant aspects when making investment decisions. They focus on past returns and/or price movements as the critical and almost only factor in their investment decisions, which Benjamin Graham (1949) warned us about in The Intelligent Investor. In this seminal work we find at least three warnings in relation to this issue (emphasis added):

The third form of endeavor – the famous buy-cheap-sell-dear principle commonly ascribed to the original Rothschild – may seem at first blush to be only a special case of trading in the market. Actually it differs in a fundamental sense from what we have just been discussing, because this approach lays its first emphasis on value received rather than on the expected next movement of the market.

By shifting his emphasis from price movements as such to their effect on the level of values the investor can retain his original and proper status as the buyer of sound securities and at the same time react intelligently to the recurrent fluctuations of the stock market.

He must deal in values, not in price movements. He must be relatively immune to optimism or pessimism and impervious to business or stock-market forecasts. In a word, he must be psychologically prepared to be a true investor and not a speculator masquerading as an investor. If he can meet this test, he will be a member not of the public at large but of a specialized and self-disciplined group.

The example above clearly illustrates that investors’ investment decisions mainly are influenced by price movements, not by the underlying valuations. Otherwise they would show the opposite behavior, they would buy at low valuations and/or sell at high valuations. Is there a way out of the problem? Yes, we are convinced there is, and the answer is provided by Benjamin Graham in the above statements – a systematic focus on value rather than price movements.

Value investors should build a systematic investment system around focusing on value. The need for a quantitative system is summarised by Gray and Carlisle in their book as follows:

The power of quantitative investing is in its relentless exploitation of edges. The objective nature of the quantitative process acts both as a shield and a sword. As a shield, it serves to protect us from our own cognitive biases. We can also use it as a sword to exploit behavioral errors made by others. It can give us the confidence to sit down at the poker table and know we’re not the patsy.

The investment system should consist of at least the following elements:
(a)    a quantitative stock selection model with a focus on value and safety, consistent with the investment philosophy of Benjamin Graham and with a solid and proven historical track record;
(b)    a system of rules in order to determine when additional investments will be made.

Part (b) of the investment system forces investors to consider value investing as a long-term savings plan instead of a one-time (hopefully lucky shot) investment. This point will be elaborated on in a later article.

As regards part (a) the book of Gray and Carlisle can help investors developing their own quantative value investment methodology. In Value Investing – Tools and Techniques for Intelligent Investing, James Montier (2009) distinguishes three types of fundamental risks: valuation risk, business risk and financial risk. In Quantitative Value by Gray and Carlisle valuation risk is dealt with in Chapters 7, 8 and 11. Business risk is treated in Chapters 5 and 8. Financial risk is considered in Chapter 3 with the PROBM-score, in Chapter 4 with the Altman Z-score and the score developed by Campbell et al. (2008), and in Chapter 6 with the F-SCORE measure developed by Piotroski. I’m convinced that most investors need some further assistance in selecting their own quantitative value investing methodology. As a consequence, in the next contributions I will spend some time discussing the various quantitative chapters of the book.

Value investing in emerging Asia over the 1995-2012 period

November 2012

-Introduction

In reply to our previous study on emerging Asia we were asked to extend the study to the 1995-2012 period and to include companies with market capitalization of at least $100 million dollar (in 2012 terms). In order to increase the number of companies taken into consideration, companies need a public track-record of at least two instead of at least five years. The other steps in the methodological set-up are not changed. In this way the historical returns during the Asian crisis of 1997-1998 are introduced in the empirical analysis. The explanation is identical to our former contribution. First we discuss the (total) number of stocks in the dataset. In a second step we document the annual returns to value, value+ and growth investing over the 1995-2012 period. Remember that value+ is an investment strategy where the value decile is purged from companies with a weak financial position (refer to Value and the rest).

-Number of companies

The three aforementioned changes of the methodological set-up lead to a significant increase in the general number of companies in the dataset to 25,643. In 1995 the number of companies taken into consideration is 245. This implies 25 companies per decile portfolio. At the end of July 2011, in the twelve Asian countries there are 2,831 appropriate companies that meet the renewed requirements.

-Annual returns to value and growth decile portfolios

TABLE II and GRAPH I give an overview of the annual returns to value, value+ and growth investing over the 1995-2012 period. The 2011 portfolio runs from the end of July 2011 to the end of July 2012. The row “# stocks” indicates the number of companies in the annual value and growth deciles on the one hand and the remaining companies in the annual value+ portfolios on the other.

TABLE II:
RETURNS TO VALUE AND GROWTH INVESTING IN EMERGING ASIA

 

1995

1996

1997

1998

1999

2000

2001

2002

2003

Value

-8,1%

5,2%

-65,3%

124,5%

-18,5%

1,5%

60,6%

43,6%

35,9%

#stocks

25

82

103

84

71

82

81

94

121

 
Value+

6,4%

10,5%

-50,7%

126,6%

-11,5%

1,9%

66,6%

29,4%

30,5%

#stocks

14

45

57

45

60

59

54

78

87

 
Growth

-6,2%

2,3%

-37,9%

8,7%

-4,5%

-35,9%

0,8%

1,8%

12,3%

#stocks

25

82

103

84

71

82

81

94

121

TABLE II:
RETURNS TO VALUE AND GROWTH INVESTING IN EMERGING ASIA (continued)

 

2004

2005

2006

2007

2008

2009

2010

2011

Mean

Value

85,9%

10,7%

106,7%

-19,8%

-5,8%

44,6%

36,4%

-22,3%

24,5%

#stocks

142

165

197

248

268

222

245

283

 
   
Value+

65,4%

9,3%

100,7%

-21,4%

-8,4%

49,7%

34,2%

-16,7%

24,9%

#stocks

98

145

157

223

179

147

180

223

   
Growth

38,0%

25,0%

72,7%

-29,6%

-13,7%

26,0%

16,7%

-16,1%

3,5%

#stocks

142

165

197

248

268

222

245

283

Academic value experienced a decline of 65.3% during the Asian crisis. Grahamite value investors observed halving their equity invested over the period July 1997 – July 1998. Growth stocks recorded a smaller decrease (-37.9%) during this crisis period. With regard to the year 1998 the rebound in value stocks was much bigger compared to the rebound in growth stocks. The overall results are not changed compared with our previous study. The value decile portfolio realizes an average annual return of 24.5% over the sample period. The value+ portfolio realizes an average annual return of 24.9%. For growth investing we document an average annual return of only 3.5%.

GRAPH I: RETURNS TO VALUE AND GROWTH INVESTING IN EMERGING ASIA

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-Conclusion

In this contribution we document the returns to value and growth investing in twelve emerging Asian countries over the 1995-2012 period, including the dramatic experience of the Asian crisis. Value stocks significantly outperform growth stocks over the sample period. In a next contribution we will document the results to (diversified) global value investing over the 1995-2012 period, providing an update to the study Going Global: Value Investing Without Boundaries by James Montier (2008).

Value investing in emerging Asia over the 1999-2012 period

November 2012

Value investing is a bumpy ride, but if you are a long-term investor, there are few better ways to invest.
Joel Greenblatt, 2009

-Introduction

In reply to the publication by Dr. Marc Faber of our study Value and the rest we were asked to document the returns to value investing in emerging Asia. In this contribution we present the results over the 1999-2012 period.

The methodology can be summarized as follows:

* companies need a public track-record of at least five years;

* annual stock portfolios are established at the end of July, i.e. taking into account a time lag of 7 months to account for delayed availability of the annual reports;

* companies with a market capitalization less than $250 million (in 2012 terms) are removed from the analysis;

* value and growth decile portfolios are established using the methodology of Chan and Lakonishok (2004) (refer to Value and the rest);

* value+ is an investment strategy where the value decile is purged from companies with a weak financial position (refer to Value and the rest);

* we include the following Asian countries in our dataset:

Singapore from 1987;
Hong Kong and South-Korea from 1989;
India, Indonesia, Malaysia, Philippines, Taiwan and Thailand from 1994;
Bangladesh, Sri Lanka and Vietnam from 2005.

* annual portfolio returns are measured in US dollar.

-Number of companies

TABLE I shows the number of companies for each country at the end of July over the 1999-2011 time period using the methodology explained above. There are only few companies in the database that meet the required criteria before the year 1999. In 1999 the number of companies taken into consideration is 289. This implies 29 companies per decile portfolio, an absolute minimum in order to achieve typical results. At the end of July 2011, in the twelve Asian countries there are 1743 appropriate companies that meet the requirements. Over the 1992-2011 period, the dataset contains 12,255 companies.

TABLE I:
NUMBER OF COMPANIES PER COUNTRY

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Total

Singapore

37

43

52

39

40

58

71

84

114

99

88

87

113

1185

Hong Kong

50

64

73

75

93

111

150

163

233

190

191

223

275

2141

South-Korea

36

38

37

55

70

80

148

161

266

212

161

172

232

1872

India

32

39

38

56

70

88

161

186

220

232

250

293

324

1989

Indonesia

6

13

13

18

22

24

34

43

64

66

67

77

105

552

Malaysia

50

59

57

60

67

76

90

89

133

111

92

115

134

1133

Philippines

16

19

13

15

16

17

20

28

46

38

38

53

56

375

Taiwan

48

82

56

63

65

137

174

189

338

271

220

296

360

2299

Thailand

14

10

15

25

35

51

50

53

76

69

54

88

111

651

Bangladesh

6

10

16

Sri Lanka

7

15

22

Vietnam

12

8

20

Total

289

367

354

406

478

642

898

996

1490

1288

1161

1429

1743

12255

-
-Annual returns to value and growth decile portfolios

TABLE II and GRAPH I give an overview of the annual returns to value, value+ and growth investing over the 1999-2012 period. The 2011 portfolio runs from the end of July 2011 to the end of July 2012. The row “#stocks” indicates the number of companies in the annual value and growth deciles on the one hand and the remaining companies in the annual value+ portfolios on the other.

TABLE II: RETURNS TO VALUE AND GROWTH INVESTING IN EMERGING ASIA

 

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Mean

Value

-29.6%

-0.6%

69.7%

45.8%

32.5%

84.9%

18.4%

99.1%

-16.7%

-3.1%

38.0%

37.0%

-25.3%

26.9%

#stocks

29

37

35

41

48

64

90

100

149

129

116

143

174

 
Value+

-23.1%

-5.9%

79.8%

43.1%

27.2%

66.8%

14.9%

105.8%

-16.4%

-5.3%

37.6%

39.9%

-23.9%

26.2%

#stocks

21

30

25

28

32

38

67

74

112

84

66

87

104

 
   
Growth

-6.5%

-33.1%

-3.4%

10.2%

18.7%

42.8%

22.0%

73.2%

-32.2%

-8.7%

27.8%

20.6%

-12.5%

9.2%

#stocks

29

37

35

41

48

64

90

100

149

129

116

143

174

In accordance with the US data (refer to Value and the rest) we find poor performance of value stocks over the period 1999-2000, the period 2007-2008 and in 2011. Nevertheless the results again indicate that patience will be rewarded. The value decile portfolio realizes an average annual return of 26.9% over the sample period. The value+ portfolio realizes an average annual return of 26.2%. For growth investing we document an average annual return of only 9.2%. As explained in our previous contribution A note on the difference between academic and Grahamite value we advise investors to always implement Grahamite value rather than academic value.

It should be noted that the average market capitalization of the selected companies is significantly lower compared to the ones in the study Value and the rest. In this latter study we focus on US companies ranked in the top six deciles of market cap based on NYSE breakpoints. The above returns also don’t take transaction costs into account, no doubt costs that for the majority of investors will be higher compared to the transaction costs on US stock exchanges. Finally we would like to remind investors that emerging Asia experienced a dramatic decline in the 1997-1998 period.

GRAPH I: RETURNS TO VALUE AND GROWTH INVESTING IN EMERGING ASIA

-
-Conclusion

In this contribution we document the returns to value and growth investing in twelve emerging Asian countries over the 1999-2012 period using the same methodology as Chan and Lakonishok (2004) on the US dataset. Value stocks significantly outperform growth stocks over the sample period. In a next contribution we will perform a robustness analysis on the Asian dataset, extending the sample period to the 1994-2012 period. In this way the historical returns during the Asian crisis of 1997-1998 are introduced in the empirical analysis. In addition we will show the results to (diversified) global value investing over the 1995-2012 period, providing an update to the study Going Global: Value Investing Without Boundaries by James Montier (2008).

On the difference between academic and Grahamite value

November 2012

In the academic literature a value stock is defined as a company with a low price-book, price-sales, price-earnings and/or price-cash flow ratio. A company with both of the following characteristics is considered to be a value stock, regardless of the company’s financial strength:
*price-book: 0.5,
*price-earnings: 8.

In our article The determinants of financial strength we provided the following advice for investors:

Hence we recommend always guaranteeing – either on a stock level or on a portfolio level – minimal safety margins regarding financial strength prior to taking a look at the two other risks, valuation risk and business risk. Based on the above discussed quantitative measures of financial strength value investors can work out investment strategies with an extremely low financial risk profile, guaranteeing not only an almost non-existent “permanent loss of capital” – as coined by Benjamin Graham – but also strong performance during downturns and significant long-term outperformance.

Consequently from a Grahamite point of view the aforementioned two characteristics are insufficient to consider a company to be a value stock. In order to define – within a Grahamite framework – a company as a value stock, this also depends on the financial strength of the company concerned. The following table illustrates this issue. The company in the first column can only be defined as a value stock from an academic point of view. The company in the last column can – considering the combination of low valuation and sufficient financial strength – be defined as a value stock from a Grahamite point of view.

Academic value:

*price-book: 0.5

*price-earnings: 8

*debt to equity: 300%

*equity to total assets: 20%

Grahamite value:

*price-book: 0.5

*price-earnings: 8

*debt to equity: 50%

*equity to total assets: 55%

The relevance of the aforementioned insights is emphasized by the actual returns of LSV Asset Management.* The Conservative Equity Value Fund started with a Net Asset Value of $10 in 2007. On April 30, 2012, this document shows a Net Asset Value of $7.30, significantly below the starting value. A closer look at the document shows that financials comprise 27.3% of the total stock portfolio. Financials suffered a major blow during the financial crisis, as shown by the KBW Bank index, and were only saved by the monetary largesse of the Federal Reserve. The fact that financials are part of the portfolio demonstrates that at LSV they implement academic value. Consequently, avoiding a “permanent loss of capital” cannot be guaranteed.

In a recent quarterly letter Jeremy Grantham accentuated the problem of career risk faced by asset managers:

For us agents, he [Keynes] might better have said “The market can stay irrational [and distorted by the government] longer than the client can stay patient.”

Some investors will definitely always quit value investing after a couple of years of under- or negative performance. “Human nature is not much affected by the passing years.” By guaranteeing objective, quantifiable minimal safety margins regarding financial strength agents can nevertheless hope to increase the clients’ confidence in the solidness of the stock portfolio in which they are invested.** This confidence can contribute to emotionally learning to tide over distressing periods (e.g. 2007-2009) and/or the inevitable periods of underperformance.

* LSV Asset Management was established by Lakonishok, Shleifer and Vishny. The three professors are well known for their seminal 1994 research paper.

** Quantifying the financial strength of a company does not require rocket science. Some simple ratios derived from the financial statements will do the job.

The New Finance: A new financial paradigm?

November 2012

Recently, as part of the Master of Science in Artificial Intelligence Programme (KU Leuven), we wrote the research paper An Assessment of The New Finance Paradigm Using Statistical and Artificial Intelligence Techniques (available by mail). In this contribution we give a brief summary of our objectives, findings and conclusions.

-Introduction

In the introductory chapter of the book The Inefficient Stock Market, Haugen (2002) distinguishes between three paradigms in financial-economics over the past century: The Old Finance, Modern Finance and The New Finance. The Old Finance was shaped by Benjamin Graham. It is a good academical custom for Haugen to define The Old Finance as a paradigm themed “the analyis of financial statements and the nature of financial claims”.

The close reader of Security Analysis (1934) and The Intelligent Investor (1949) realises that this is an extremely limited reflection of the views of The Old Finance. Insights hidden from view concern amongst other things:
* the factor of human nature in shaping stock market movements;
* the crucial distinction between investment and speculation;
* the distinction between bargain issues and growth stocks;
* the dangers related to growth and IPO investing;
* the margin-of-safety concept;
* … .

The above concepts and insights mean that the dissimilarity between The Old Finance and The New Finance mainly is restricted to using statistical and econometric techniques as “foundations” when implementing inductive ad hoc expected-return factor models. “Cast your net widely, and let statistics and econometrics guide your predictions” is the message (Haugen, 2010).

Consequently the use of a broad spectrum of statistical and more advanced artificial intelligence techniques is an excellent opportunity to submit the foundations of The New Finance to various empirical tests. We implement three traditional statistical techniques (ordinary-least-squares regression, ridge regression and robust regression using Huber penalty), two non-linear artificial intelligence techniques (a backpropagation feedforward neural network and a least-squares support vector machine with RBF kernel), and one ensemble method (stacked generalization).

-Objectives

In our research paper we take a product development perspective. We aim at the development of a user-friendly investment tool. Amongst other things this implies using a reduced set of factors (36 factors instead of the 71 factors in the original paper by Haugen and Baker (1996)) and making stock return forecasts on a quarterly instead of monthly basis.

-Findings

We summarize our main findings:

* the use of non-linear artificial intelligence techniques and ensemble methods doesn’t offer much value vis-à-vis traditional linear techniques such as ordinary-least-squares regression;

OLS regression and ridge regression generate a return that doesn’t significantly differ from the return generated by a neural network.

* the use of a dynamic investment model consisting of 36 fundamental and technical factors (“Complexity”) doesn’t generate significantly higher returns compared to a static two-factor model (“Simplicity”), confirming the evidence provided by Greenblatt (2006);

-
* the returns of our factor model are highly sensitive to the length of the history of payoffs that is used when making out-of-sample forecasts;

In the above graph we show the increase in $1 when we use the average estimated regression coefficients over the past two (2Q), four (4Q) and ten quarters (10Q) when predicting future quarterly stock returns.

* the fundamental profile of the established portfolios based on our ad hoc expected return factor model is highly volatile.

The above graph shows the debt-to-equity ratio of the quarterly portfolios. Debt to equity balances between 0.5 and 2 over the period considered.

-Conclusions

Future research should be conducted before considering The New Finance as a new paradigm in the financial-economic sciences.

-References

Graham, B. (1949). The Intelligent Investor. HarperCollins Publishers.

Graham, B. and D.L. Dodd. (1934). Security Analysis. The McGraw-Hill Companies.

Greenblatt, J. (2006). The Little Book that Beats the Market. Wiley.

Haugen, R.A. (2002). The Inefficient Stock Market (Second Edition). Pearson Education.

Haugen, R.A. (2010). The New Finance – Overreaction, Complexity, and Their Consequences (Fourth Edition). Pearson Education.

Haugen, R.A., and N.L. Baker. (1996). “Commonality in the determinants of expected stock returns.” Journal of Financial Economics, Vol. 41, 401-439.

Value and the rest

September 2012

This study was also published by Dr. Marc Faber as part of his monthly market commentary October 1, 2012.

In 2004 Chan and Lakonishok published Value and Growth Investing: Review and Update. In this study they document annual returns to value and growth investing over the period 1969-2001. They conclude that even after taking into account the hyperbolic surge (and crash afterwards) of growth stocks in the period 1997-2000 value investing still generates superior returns. Over the 1969-2001 period Chan and Lakonishok document a compound annual return of 16.4% for large cap US companies, where large caps are defined as stocks ranked in the top six deciles of market cap based on NYSE breakpoints. Over the same period the S&P500 generates a compound annual return of 11.4%.

In this contribution we extend the Chan and Lakonishok study:

* we document average annual returns to value and growth investing for large cap US companies over the 1970-2012 period;

* we show the returns to an investment strategy where the value decile is purged from companies with a weak financial position (referred to as value+, where a weak financial position is defined as companies with less than 30 percent common equity);

* we compare the returns to value and growth investing with other asset classes such as government bonds, gold and oil, both in nominal and real terms.

-Annual returns

TABLE I and TABLE II show average annual returns for the different investment strategies and asset classes over the 1970-2012 period. Both tables clarify that value+ realizes the highest average annual return. In nominal terms the average annual return to value+ is 16.9%; in real terms the return is 12.5%. Value+ realizes a smaller maximum drop on an annual basis compared to the other investment strategies and asset classes, with the exception of the 10-year Treasury.

TABLE I: AVERAGE ANNUAL RETURNS AND DOWNSIDE RISK (NOMINAL TERMS) OVER THE 1970-2012 PERIOD

Value

Value+

Growth

S&P500

10-year Treasury

Gold

Oil

16.4%

16.9%

11.9%

11.8%

8.4%

11.9%

11.8%

-28.0%

-23.7%

-38.7%

-31.9%

-11.1%

-25.2%

-46.4%

TABLE II: AVERAGE ANNUAL RETURNS AND DOWNSIDE RISK (REAL TERMS) OVER THE 1970-2012 PERIOD

Value

Value+

Growth

S&P500

10-year Treasury

Gold

Oil

12.1%

12.5%

7.6%

7.5%

4.0%

7.5%

7.5%

-26.6%

-22.3%

-45.8%

-30.4%

-13.7%

-34.8%

-48.1%

-
-Ten-year real total returns

In the following five charts we compare ten-year real total returns between value+ on the one hand and growth, S&P500, 10-year Treasury, gold and oil on the other over the 1980-2012 period. At the bottom of the chart we provide the most important results, more specifically:

* the number of times that each investment strategy or asset class realizes a positive ten-year real total return;

* the average ten-year real total return;

* the minimum ten-year real total return.

Value+ stands out as the best and most consistent investment strategy. We find that in all 33 ten-year periods value+ realizes a positive real total return with an average of 219% and a minimum of 65%. This finding also holds for value. All other investment strategies and asset classes are confronted with at least three ten-year periods of negative real total returns, implying a decrease in real wealth for investors. This is notably the case for gold and oil. Both asset classes suffered from a long period of negative ten-year total returns after the commodity boom in the late 1970s.

GRAPH I: VALUE+ VERSUS GROWTH – TEN-YEAR REAL TOTAL RETURNS

Number of times value+ realizes a positive real total return: 33 out of 33
Number of times growth realizes a positive real total return: 30 out of 33

Average real total return for value+: 219%
Average real total return for growth: 80%

Minimum real total return for value+: 65%
Minimum real total return for growth: -49%

GRAPH II: VALUE+ VERSUS S&P500 – TEN-YEAR REAL TOTAL RETURNS

Number of times value+ realizes a positive real total return: 33 out of 33
Number of times S&P500 realizes a positive real total return: 29 out of 33

Average real total return for value+: 219%
Average real total return for S&P500: 120%

Minimum real total return for value+: 65%
Minimum real total return for S&P500: -33%

GRAPH III: VALUE+ VERSUS 10-YEAR TREASURY – TEN-YEAR REAL TOTAL RETURNS

Number of times value+ realizes a positive real total return: 33 out of 33
Number of times 10-year Treasury realizes a positive real total return: 28 out of 33

Average real total return for value+: 219%
Average real total return for 10-year Treasury: 51%

Minimum real total return for value+: 65%
Minimum real total return for 10-year Treasury: -40%

GRAPH IV: VALUE+ VERSUS GOLD – TEN-YEAR REAL TOTAL RETURNS

Number of times value+ realizes a positive real total return: 33 out of 33
Number of times gold realizes a positive real total return: 15 out of 33

Average real total return for value+: 219%
Average real total return for gold: 67%

Minimum real total return for value+: 65%
Minimum real total return for gold: -60%

GRAPH V: VALUE+ VERSUS OIL – TEN-YEAR REAL TOTAL RETURNS

Number of times value+ realizes a positive real total return: 33 out of 33
Number of times oil realizes a positive real total return: 16 out of 33

Average real total return for value+: 219%
Average real total return for oil: 69%

Minimum real total return for value+: 65%
Minimum real total return for oil: -62%

-Total return

Finally we take a look at the total return of the various investment strategies and asset classes over the 1970-2012 period. The results are shown in GRAPH VI. We start with $1 invested at the end of May 1970. At the bottom of the graph again we show the most important figures. Value+ stands out with a total return in nominal terms of $393.35 after a 42-year period, implying a compound annual return of 15.29%. This figure is somewhat lower compared to the results by Chan and Lakonishok (2004).

GRAPH VI: TOTAL NOMINAL RETURN

Total return for value: $324.74
Total return for value+: $393.35
Total return for growth: $41.10
Total return for S&P500: $67.96
Total return for 10-year Treasury: $24.66
Total return for gold: $43.40
Total return for oil: $27.44

Compound annual return for value: 14.76%
Compound annual return for value+: 15.29%
Compound annual return for growth: 9.25%
Compound annual return for S&P500: 10.57%
Compound annual return for 10-year Treasury: 7.93%
Compound annual return for gold: 9.39%
Compound annual return for oil: 8.20%

-Conclusion

In this contribution we compared the returns to value+ investing with other investment strategies and asset classes over the 1970-2012 period. Value+ investing – as originally conceived by Benjamin Graham – proves to be the only investment strategy that realizes a positive real return over each ten-year period and consequently actually preserves the capital of investors in real terms. At the same time investors – thanks to the safe fundamental risk profile of value+ – don’t need to be worried about “a permanent loss of capital”.

-References

CPI and S&P500 data by Robert Shiller

10-year Treasury data by Aswath Damodaran

Gold and oil data by Inflation Data

Recommended readings in investing

July 2012

Recently students asked us for a list of some recommended literature regarding (value) investing. The question initially was an excellent opportunity to reorder our bookshelves in order to stow away in the attic the less consulted and/or less read books. After some reflection, concerning (value) investing books we bring up the following top 10:
1)    Graham, The Intelligent Investor, 1949.
2)    Montier, Value Investing, 2009.
3)    Montier, Behavioral Investing, 2007.
4)    Le Bon, The Crowd – A Study of the Popular Mind, 1896.
5)    Galbraith, The Great Crash 1929, 1954.
6)    Haugen, The New Finance – Overreaction, Complexity, and Their Consequences, 2010
7)    Haugen, The Inefficient Stock Market, 2002
8)    Lowe, The Rediscovered Benjamin Graham, 1999.
9)    Greenblatt, The Little Book that Beats the Market & The Big Secret for the Small Investor, 2006, 2010.
10)    Graham and Dodd, Security Analysis, 1934.

With regard to academic papers we propagate the following alphabetical list of 25 papers:
1)    Arnott et al., Clairvoyant Value and the Value Effect, The Journal of Portfolio Management, 2009.
2)    Baker and Haugen,  Low Risk Stocks Outperform within All Observable Markets of the World, Working Paper, 2012.
3)    Barber and Odean, Trading Is Hazardous to Your Wealth, The Journal of Finance, 2000.
4)    Bogle, The Mutual Fund Industry 60 Years Later – For Better or Worse, Financial Analysts Journal, 2005.
5)    Campbell et al., In Search of Distress Risk, The Journal of Finance, 2008.
6)    Chan et al., New Paradigm or Same Old Hype in Equity Investing, Financial Analysts Journal, 2000.
7)    Chan et al., The Level and Persistence of Growth Rates, The Journal of Finance, 2003.
8)    Cook et al., On the marketing of IPOs, Journal of Financial Economics, 2006.
9)    Davis, The Cross-Section of Realized Stock Returns, The Journal of Finance, 1994.
10)    Fama and French, Dissecting Anomalies, The Journal of Finance, 2008.
11)    Haugen and Baker, Case Closed, Working Paper, 2008.
12)    Hirshleifer, Investor Psychology and Asset Pricing, The Journal of Finance, 2001.
13)    Huang, The cross section of cashflow volatility and expected stock returns, Journal of Empirical Finance, 2009.
14)    Jegadeesh et al., Analyzing the Analysts – When Do Recommendations Add Value, The Journal of Finance, 2004.
15)    Lakonishok et al., Contrarian Investment, Extrapolation, and Risk, The Journal of Finance, 1994.
16)    Lee and Swaminathan, Price Momentum and Trading Volume, The Journal of Finance, 2000.
17)    Lovallo and Kahneman, Delusions of Success, Harvard Business Review, 2003.
18)    Muraven and Baumeister, Self-Regulation and Depletion of Limited Resources, Psychological Bulletin, 2000.
19)    Odean, Are Investors Reluctant to Realize Their Losses, The Journal of Finance, 1998.
20)    Piotroski, Value Investing, Journal of Accounting Research, 2000.
21)    La Porta, Expectations and the Cross-Section of Stock Returns, The Journal of Finance, 1996.
22)    Ritter, Economic growth and equity returns, Pacific-Basin Finance Journal, 2005.
23)    Ritter and Welch, A Review of IPO Activity, Pricing, and Allocations, The Journal of Finance, 2002.
24)    Skinner and Sloan, Earnings Surprises, Growth Expectations, and Stock Returns, Review of Accounting Studies, 2002.
25)    Van Dijk et al., Blessed are those who expect nothing, Journal of Economic Psychology, 2003.

In the past years numerous white papers and articles worth reading have been published:
1)    Grantham, My Sister’s Pension Assets and Agency Problems, GMO Quarterly Letter, 2012.
2)    Montier, The Seven Immutable Laws of Investing, GMO White Paper, 2011.
3)    Montier, The Flaws of Finance, GMO White Paper, 2012.
4)    Taleb, The pseudo-science hurting markets, Financial Times, 2007.
5)    Taleb and Triana, Bystanders to this financial crime were many, Financial Times, 2008.
6)    Taleb, History Written By the Losers, Lecturing Birds, 2009.

Safe Super Stocks versus risky Stupid Stocks

July 2012

In The determinants of financial strength we learned that companies with a (very) strong financial position realise higher stock returns compared with companies with a (very) weak financial position. We have referred to the studies by Opler and Titman (1994) and Campbell et al. (2008) among others. In this case also the study by Piotroski (2000) can be used. Piotroski shows that in a value portfolio the companies with the strongest financial and operational performances over the past year realise significantly higher stock returns.

In Blessed are those who expect nothing and Passed growth as a reliable guide to the future we have warned for an overoptimistic appraisal of future results, which is always doomed to produce too high valuations. Finally surrealistic valuations are punished with inferior stock returns.

These three contributions confirm the necessity to build in fundamental safety margins when establishing a stock portfolio, as initially expressed by Benjamin Graham in “the best book on investing ever written”:

In the old legend the wise men finally boiled down the history of mortal affairs into the single phrase, “This too will pass.” Confronted with a like challenge to distill the secret of sound investment into three words, we venture the motto, MARGIN OF SAFETY.

These two findings were combined in The Simplest Way to Select Bargain Stocks, the title of a similar interview with Benjamin Graham from 1976. In this interview Graham put forward a simplified method for stock selection containing two steps:

Step 1: remove all companies the common equity of which is smaller than 50 percent. This first step easily ensures that firms with a (very) weak financial position are eliminated.

Step 2: eliminate all companies with a price-to-earnings ratio larger than 10. This second step warrants a focus on cheap companies.

Studies show that over the period 1925-2011 this margin-of-safety method generates (extremely) attractive stock returns.

In this contribution we have an eye for the characteristics of a more advanced yet also robust investment strategy, to be precise the idea of establishing a stock portfolio consisting of Super Stocks. The distinction between Super Stocks and Stupid Stocks was introduced by Haugen (2002). Haugen, together with Baker (1996), document that the stock portfolios with the highest historical returns – so-called Super Stocks – are characterised by an extremely attractive fundamental risk profile. The reverse finding is applicable for the so-called Stupid Stocks; these stock portfolios with low historical returns are characterised by an extremely risky fundamental profile. Let’s have a look at these fundamental risk profiles. We will compare Super Stocks and Stupid Stocks on three dimensions: cheapness, financial strength and operational strength (Haugen and Baker, 1996).

Graph 1 indicates that Super Stocks are characterised by a higher dividend, cash-flow and earnings yield. Earnings yield is the inverse of the price-to-earnings ratio. Super Stocks have a positive earnings yield of 10 percent, implying a price-to-earnings ratio of 10.

GRAPH 1: CHEAPNESS

-

In Graph 2 and 3 the financial position and the change of it are displayed. It is obvious that Super Stocks have a stronger financial position; this is expressed in the lower ratio of total debt to stockholders’ equity and the higher income available for the payment of interest relative to total interest charges. Moreover Stupid Stocks are characterised by a deterioration in their financial position.

GRAPH 2: FINANCIAL POSITION

GRAPH 3: CHANGE IN FINANCIAL POSITION

-

In Graph 4 and 5 the operational position and the change of it are compared. Super Stocks are characterized by a positive return on equity and total assets. Investors in Stupid Stocks on the contrary are confronted with negative profit margins, negative ROE and ROA, and a downswing in both performance measures.

GRAHH 4: OPERATIONAL POSITION

GRAPH 5: CHANGE IN OPERATIONAL POSITION

-

Haugen (2002) explains how investors that dispose of the essential algorithms, can establish stock portfolios with a Super Stock profile.

In Haugen (2010) the author distinguishes between The Ancient Finance, Modern Finance and The New Finance. The Ancient Finance focused on Benjamin Graham’s investment theory. A comparison between The Ancient Finance and The New Finance shows that the investment foundations of both paradigms are considerably parallel. Like Graham, Haugen also assumes that stock returns can be explained by human behaviour; investors that systematically fall victim to the same mistakes over a sufficiently long time horizon, mistakes that can be exploited over a sufficiently long time horizon by focusing on stocks and/or stock portfolios with a safe fundamental profile.

Graham, 1949

Haugen, 2002; Haugen and Baker, 2008

The rules that survive apply mainly to human nature and human conduct. What this means is that, though business conditions may change, corporations and securities may change, and financial institutions and regulations may change, human nature remains essentially the same. Thus, the important and difficult part of sound investment, which hinges upon the investor’s own temperament and attitude, is not much affected by the passing years.

Expected stock returns are common across countries because human beings populate each market – human beings with an inaccurate concept of the true length of the short run. Human beings that tend to overweight the most recent information received. Human beings that are subject to agency problems that plague the entire investment profession everywhere. Human beings that tend to mimic, with time, the fads of the investment profession in the leader of the financial world – the United States. It is the commonalities in human behavior that create the commonality in the payoffs.

Confronted with a like challenge to distill the secret of sound investment into three words, we venture the motto, MARGIN OF SAFETY.

Undeniably, the highest expected return stocks are, collectively, highly attractive; the lowest expected return stocks are very scary.

No further questions.

-References

Campbell, J.Y., J. Hilscher, and J. Szilagyi. (2008). “In Search of Distress Risk.” The Journal of Finance, Vol. LXIII, No. 6., 2899-2939.

Graham, B. (1949). The Intelligent Investor. HarperCollins Publishers.

Haugen, R.A. (2002). The Inefficient Stock Market (Second Edition). Pearson Education.

Haugen, R.A. (2010). The New Finance – Overreaction, Complexity, and Their Consequences (Fourth Edition). Pearson Education.

Haugen, R.A., and N.L. Baker. (1996). “Commonality in the determinants of expected stock returns.” Journal of Financial Economics, Vol. 41, 401-439.

Haugen, R.A., and N.L. Baker. (2008). “Case Closed.” Working Paper, Quantitative Investments.

Opler, T.C., and S. Titman. (1994). “Financial Distress and Corporate Performance.” The Journal of Finance, Vol. XLIX, No. 3, 1015-1040.

Piotroski, J.D. (2000). “Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers.” Journal of Accounting Research, Vol. 38, 1-41.

The Simplest Way to Select Bargain Stocks

June 2012

-Introduction

In 1976 Benjamin Graham gave three interviews worth reading, one of them being The Simplest Way to Select Bargain Stocks. The interview was published in Medical Economics and all of the interviews can be downloaded here:

An Hour with Mr. Graham, FAJ (1976)

A Conversation with Benjamin Graham, FAJ (1976)

The Simplest Way to Select Bargain Stocks, Medical Economics (1976)

-The Simplest Way

In the interview with Medical Economics Benjamin Graham describes a simple quantitative method consisting of the following three steps:

Step 1: By making as large a list as possible of common stocks currently selling at no more than seven times their latest – not projected – 12-month earnings. Just look up the price-earnings ratios listed in the stock quotation columns of The Wall Street Journal or other major daily newspapers.

Step 2: You should select a portfolio of stocks that not only meet the P-E requirement but also are in companies with a satisfactory financial position. … An easy way to check on that is to look at the ratio of stockholders’ equity to total assets; if the ratio is at least 50 percent, the company’s financial condition can be considered sound.

This advice already could be found in The Intelligent Investor (1949):

An industrial company’s finances are not conservative unless the common stocks (at book value) represents at least half of the total capitalization, including all bank debt. For a railroad or public utility the figure should be 30 per cent.

Diversification is of course required.

Step 3: A portfolio of 30 would probably be an ideal minimum.

The results of this method were tested by Benjamin Graham over the period 1925-1975 with the following results:

My research shows that a portfolio put together using such an approach would have gained twice as much as the Dow Jones Industrial Average over the long run.

Otherwise said from a business economic point of view the method is based on combining a low valuation with a strong financial position, margin-of-safety plain and simple. Concerning the determinants of financial strength we refer to our April contribution.

-The Evidence

The study Analyzing Valuation Measures: A Performance Horse-Race over the past 40 Years was published a few months ago. In this study Wesley Gray and Jack Vogel test the performance of various valuation multiples over the period 1971-2010. One of the valuation multiples concerns the traditional price-to-earnings ratio. At the end of June companies are sorted based on the price-to-earnings ratio and divided in quintiles. Quintile 1 contains the growth stocks; quintile 5 contains the value stocks. Each portfolio is held for one year. Value stocks earn an average annual return of 15.99 percent for equally-weighted portfolios and 13.62 percent for value-weighted portfolios over the 1971-2010 period (TABLE I).

TABLE I

Average annual returns 1971-2010

Equally-weighted

Value-weighted

Q1 – Growth

10.44%

9.26%

Q2

12.40%

10.81%

Q3

13.74%

10.42%

Q4

14.60%

11.98%

Q5 – Value

15.99%

13.62%

It should be noted that the use of deciles or more concentrated portfolios undoubtedly results in higher average annual returns for value stocks. Nevertheless the findings are convincing and confirm those findings documented by Benjamin Graham over the period 1925-1975.

At the bottom of this article we provide the reader at the beginning of June with a list of fifty US companies having both a price-to-earnings ratio smaller than 10 and a common equity of at least 50 percent. A similar selection can be built using widely available professional stock screeners (e.g. screener.co).

-An Ode to Quant

Given the strong track-record of this quantitative method based on cheapness and financial strength (and other simplified quantitative value methods) over a period of more than 85 years the question should be raised why so much professional investors have not at all adopted a purely quantitative approach.

In the chapter Painting by Numbers: An Ode to Quant from the book Behavioural Investing James Montier formulates a number of answers. The principal reason happens to be overconfidence, the confidence or otherwise said the illusion that in the role of investors we can easily defeat simple quantitative models by making use of additional detailed information. Investors “adding their own two cents” should however have very strong a priori reasons why they will succeed in generating significantly higher returns.

A second reason is the loss of employment for analysts. Arranging a list according to the aforementioned three steps requires at the most one day of labour per year.

Montier considers the third reason in the sphere of marketing. It is much easier to persuade investors to invest based on attractive (growth) stories by focusing on “the intangible factors of value such as good-will, management and expected earning power” than based on a rational quantitative model. In lesser years many investors expect to receive an alleged (!) rational explanation for the negative returns and/or the underperformance. It is understood that based on this method it is hardly possible to give a significant explanation; poor years alternate with strong years. In this connection Benjamin Graham refers to the horrible stock market years 1973-1974. According to the study Value and Growth Investing: Review and Update by Chan and Lakonishok (2004) large-cap and small-cap value stocks realised returns of -40 percent and -35 percent respectively over this two-year period. A portfolio return of -40 percent implies that lots of stocks score a decrease of -50 percent, which is quite a disappointing experience for many investors.

In a well-defined bear market many sound common stocks sell temporarily at extraordinarily low prices. It is possible that the investor may then have a paper loss of fully 50 per cent on some of his holdings, without any convincing indication that the underlying values have been permanently affected. - Graham, 1949

In the light of such results investors in no time lose their confidence in a rational quantitative method; the loss years start to be such an influential factor for them that they completely lose sight of the track-record of value investing over the past decades. Instead of taking advantage of the opportunities offered by the market, investors resort to irrational panic reactions.

The investor who permits himself to be stampeded or unduly worried by unjustified market declines in his holdings is perversely transforming his basic advantage into a basic disadvantage. That man would be better off if his stocks had no market quotation at all, for he would then be spared the mental anguish caused him by other persons’ mistakes of judgment. - Graham, 1949

Over the period 1975-1976 large-cap and small-cap value stocks generated returns of 149 percent and 142 percent respectively, which is amply sufficient to outweigh the losses in the two previous years. Benjamin Graham correctly concludes with the following insight:

The investor needs the patience to apply these simple criteria consistently over a long enough stretch so that the statistical probabilities will operate in his favor. (Emphasis added)

-The Simplest Stock List (June 6, 2012)

Company

P/E

Equity

American Greetings

6,6

54%

Apache

6,8

53%

Applied Materials

7,0

64%

Atlas Pipeline Partners

5,5

64%

Autoliv

7,9

56%

AVX

7,6

88%

Buckeye Technologies

9,1

69%

CACI International

9,2

56%

Cash America International

9,3

54%

Ceradyne

7,2

75%

Chevron

7,1

58%

Cimarex Energy

8,2

58%

Comtech Telecommunications

9,9

67%

Convergys

4,8

62%

Corning

6,7

84%

Darling International

9,7

65%

Devry

5,8

75%

Diamond Offshore Drilling

8,4

62%

Entegris

8,4

87%

Forest Laboratories

9,5

80%

Gamestop

7,9

63%

Gardner Denver

9,6

54%

Gigoptix

4,0

71%

Graftech International

9,4

62%

Guess?

8,9

66%

Halliburton

9,4

56%

Intel

9,8

65%

International Rectifier

8,1

82%

Journal Communications

8,5

59%

KLA-Tencor

9,5

64%

Kulicke and Soffa Industries

5,8

65%

Lam Research

6,4

61%

LSB Industries

7,3

58%

Mantech International

6,3

62%

Marathon Oil

5,7

55%

Newpark Resources

5,9

56%

Occidental Petroleum

10,0

63%

Omnivision Technologies

6,4

73%

Orbital Sciences

9,5

57%

Patterson-UTI Energy

7,3

60%

Power-One

4,4

54%

Publix Super Markets

9,0

71%

Rofin-Sinar Technologies

9,0

74%

SanDisk

8,2

71%

Schnitzer Steel Industries

5,7

58%

Seaboard

7,0

69%

Unit

9,3

60%

Viropharma

9,4

67%

Vishay Intertechnology

6,9

54%

Western Digital

9,6

69%

Data from www.zignals.com.

-References

Chan, L.K.C., and J. Lakonishok. (2004). “Value and Growth Investing: Review and Update.” Financial Analyst Journal, 71-86.

Graham, B. (1949). The Intelligent Investor. HarperCollins Publishers.

Graham, B. and D.L. Dodd. (1934). Security Analysis. The McGraw-Hill Companies.

Gray, W.R. and J. Vogel. (2012). “Analyzing Valuation Measures: A Performance Horse-Race over the past 40 Years.” Working Paper, Drexel University.

Greenblatt, J. (2012). “Adding Your Two Cents May Cost You A Lot Over The Long-Term.” Magic Formula Investing Website.

Montier, J. (2007). Behavioural Investing. Wiley.

Past growth as a reliable guide to the future?

June 2012

Many shall be restored that now are fallen and many shall fall that now are in honor.
- Epigraph by Horace in Security Analysis (1934) by Graham & Dodd

-Introduction

In our May contribution we discussed the danger related to valuation risk, i.e. the danger of overpaying for the hope of growth (Montier, 2009). We documented that the expectations concerning long-term earnings growth rates of glamour stocks are overly optimistic and how this overoptimism results in inferior returns as well as (relatively) strong price drops following the publication of disappointing results. We concluded that (a) in their quest for successful growth stories investors should be careful before relying too heavily on long-term earnings growth forecasts made by financial analysts and (b) investors should avoid stocks with significantly above average valuation multiples. In this contribution we will add a new, third warning to the list: we warn to take care when using past earnings growth rates as a reliable precursor for future growth. It so happens that firms with high past earnings growth rates cannot be counted on to repeat their strong relative performance in the future; at the same time companies that over the past years have dangled round the growth group are not necessarily doomed to generate low growth. The findings warn against extrapolating past success into the future.

By custom we start with the vision of Benjamin Graham (1949) regarding the added value of past earnings trends in assessing future performance. In a second step we discuss the results of two research studies (Chan et al., 2003; Haugen, 2010) and elaborate on the important implications for growth and value investors respectively. We end with some conclusions.

-Old-School Value Investing

In chapter Group Studies of Earnings and Price Developments Benjamin Graham (1949) formulates an answer to the question “How permanent are trends?”:

Wall Street’s judgment has been influenced by past trends more than by any other single factor related to security values. The avowed object of people in the market is to anticipate future developments, and the past is held to have no significance except as it aids in such anticipation. Yet in practice it is almost the universal habit to base forecasts of future happenings on a projection of past trends. This is notoriously true of both the professional’s and the public’s view of market prospects. Nearly everyone is optimistic (or “bullish”) because the market has been enjoying a spirited advance and pessimistic (or “bearish”) after a decline. In the same way an industry or a company which has grown in the past is almost always expected to keep on progressing; those which have been on the downgrade are expected to get worse and worse.

The last attitude is expressed in categorical fashion on page 458 of Mead & Grodinsky’s book The Ebb and Flow of Investment Value, as follows: “Declining industries, therefore usually continue to decline until they reach the point where they pay nothing to the investor.”

Our own thinking during the past thirty years has been out of sympathy with this viewpoint. It is true that every established trend has a certain momentum, so that it is more likely to continue for at least a while longer than it is to reverse itself at the moment of observation. But this is far from saying that any trend may be relied upon to continue long enough to create a profit for those who get aboard. Rather extensive studies which we have made of the subject lead us to conclude that reversals of trend in every part of the financial picture occur so frequently as to make reliance on a trend a particularly dangerous matter. There must be strong independent reasons for investing money on the expectation of a continuance of past tendencies, and the investor must beware lest his weighing of future probabilities be unduly influenced by the trend line of the past. (Emphasis added)

The message is clear: past trends are not in the least a reliable guide to the future. The underlying reason has already been mentioned in our previous contribution. High growth rates and high profit margins attract rivals which results in increasing competitive pressures and downward pressure on growth and margins. On the other hand corporate bankruptcies and reorganisations will eliminate overcapacity and contribute to higher profit margins and growth rates.

-The Evidence

In Haugen (2010) the author refers to a study by Rayner and Little (1966). Rayner and Little look at British companies over the 1951-1961 period. Firms are ranked based on growth in earnings per share over the 1951-1956 period; the same procedure is repeated for the second half of the 1950s. The ranks in the two subperiods are subsequently plotted on a graph. The rank of a company in the first subperiod is plotted on the x-axis; the rank in the second subperiod is shown on the y-axis. If past growth rates serve as a reliable guide to the future we should find a pattern similar to the one in GRAPH I. Firms with the highest relative growth rates over the past years continue to bring this performance in the following years; firms that have underperformed in the past will continue to do so in the future.

GRAPH I: THE PAST AS A RELIABLE GUIDE TO THE FUTURE

-

If growth rates in the two subperiods are unrelated a pattern similar to the one in GRAPH II will emerge.

GRAPH II: PAST GROWTH NOT A RELIABLE PRECURSOR FOR FUTURE GROWTH

-

Rayner and Little find a pattern similar to GRAPH II. Using past earnings growth rates as a guide to the future is about as reliable as the fifty-fifty odds in flipping a coin. The study by Rayner and Little dates back from 1966. The evidence has been updated in “The Level and Persistence of Growth Rates” by Chan et al. (2003) for US companies. The study concerns the 1951-1998 period. The researchers verify whether firms that have demonstrated consistently high or low past growth rates have continued this pattern in the future. They proceed in the following way. At the end of each year Chan et al. select the firms that have realised superior past growth over the past three years. They subsequently check the number and percentage of companies that continue to deliver this strong relative performance in the following years. The results are shown in GRAPH III.

For year one in GRAPH III there are 259 firms that time and again realised an above-median growth in earnings over the past three years and that still exist after one year. 125 out of the 259 firms (which is 48.3 percent) succeed in realising an above-median growth in earnings for the fourth year in a row. If the possibilities of outperformance were simply a matter of chance, we would expect to find 130 companies (259*0.5) with above-median earnings growth for four consecutive years. Concerning the second year, 240 companies have realised an above-median growth in earnings over the past three years in a row and survive the upcoming two years. 57 firms out of the 240 – which is 23.7 percent – realise an above-median earnings growth during five consecutive years. By the laws of probability we would expect 60 firms (240*0.5^2) to be successful. As a consequence the number of companies achieving sustained high growth rates in earnings is not much different from what is expected by chance. Concerning year three to five in GRAPH III we also find that past and future performances are unrelated. Companies that realised the strongest past relative growth rates in earnings cannot be relied on to repeat this outperformance in the future.

GRAPH III: PERCENTAGE OF FIRMS WITH ABOVE-MEDIAN GROWTH EACH YEAR FOR THE PAST THREE YEARS AND ABOVE-MEDIAN GROWTH EACH YEAR IN THE FOLLOWING YEARS

-

Chan et al. also look at “the dogs”, i.e. companies with inferior past earnings growth rates. In GRAPH IV they select companies with below-median growth in each of the three past years and evaluate their relative performance in the five subsequent years. When we look at the third year of the following graph we find that 28 out of the 184 companies with below-median growth in earnings over the past three years – which is 15.3 percent – realise a growth in earnings above (!) the median during each of the three post-formation years. If the possibilities of outperformance were simply a matter of chance, we would expect to find 23 companies (184*0.5^3) with above-median earnings growth in each of the three post-formation years. Otherwise said the dogs from the past are not doomed to bring permanently low growth.

GRAPH IV: PERCENTAGE OF FIRMS WITH BELOW-MEDIAN GROWTH EACH YEAR FOR THE PAST THREE YEARS AND ABOVE-MEDIAN GROWTH EACH YEAR IN THE FOLLOWING YEARS

-

The findings by Chan et al. (2003) confirm the early evidence documented by Rayner and Little (1966). The reliability of past relative performance when predicting future relative performance is as reliable as the fifty-fifty odds in flipping a coin.

What are the consequences of these findings for growth and value/contrarian investors respectively? For growth investors two warnings can be stated. First high past relative earnings growth rates should not be considered to be representative for the future. Secondly one should try to avoid that the substantial growth from the past results in willingness to paying significantly above average valuation multiples. The following simplified example illustrates that the extrapolation of past earnings growth rates, which results in overoptimistic future earnings forecasts, in combination with the willingness to paying an overly liberal multiplier, results in an extremely overoptimistic assessment of intrinsic value and consequently in a significant risk of substantial long-term losses.

In the study by Chan et al. 10 percent of the companies realise an average annual earnings growth rate higher than 21.3 percent over a five-year period. Based on the evidence presented above we assume that half of these companies will generate above-median earnings growth rates in the next five years, the other half will generate below-median earnings growth rates. Let’s assume that these companies, on average, succeed in realising an average annual growth rate in earnings of 9.8 percent over the next five years (9.8 percent is the median annual growth rate in earnings for all companies over the 1951 to 1998 period). At the moment the 90th percentile of the price-to-earnings ratio for US stocks is 50. We assume that this valuation multiple is representative for the 10 percent companies with the highest average annual growth rates in earnings over the past five years. Chan et al. provide evidence that investors actually are willing to pay higher valuations for stocks having achieved several consecutive years of strong growth, believing these companies will continue their stellar performance.

We now decide to invest $100 in the group of stocks with the 10 percent highest earnings growth rates over the past five years. At a price-to-earnings ratio of 50, we obtain average earnings per share of $2. If growth investors naïvely assume that these companies will succeed in repeating the past growth rate of 21.3 percent over the next five years, they will project earnings after five years of $5.25. Applying the same liberal multiplier of 50 the growth investor obtains an estimated intrinsic value of his stock portfolio of $262. Given the evidence presented above there’s not much of a chance that the firms once again will succeed in realising an average annual growth rate of 21.3 percent; when considering a more conservative and realistic average annual earnings growth rate of 9.8 percent, the estimated earnings within five years amount to $3.19. At a multiplier of 50 this would produce an estimated intrinsic value of $160. The growth investor is however misled to believe that investors would be prepared to pay a multiplier of 50 for a group of average companies. The median price-to-earnings ratio for US companies at the time of writing is 16.42. Applying this more conservative multiplier to the estimated earnings of $3.19 after five years we obtain an intrinsic value of only $52.3, representing a loss of approximately 48% compared to the initially invested capital!

This simplified example demonstrates the dangers related to extrapolating past growth rates to the future and at the same time rewarding high growth companies with high valuation multiples, a dangerous confluence of two factors that Benjamin Graham (1949) has warned us against:

What seems to happen, rather, is that the price remains high until the earnings actually show a definite falling off – which invariably seems to take the followers of the issue by surprise. Then we have the market decline usually associated with a disappointing development – a decline perhaps intensified by the fact that the price level of the growth stock had been dangerously high.

Overoptimism in future earnings growth rates in combination with a significantly above average multiplier turns out to be the perfect receipt for guaranteeing a permanent loss of capital over the long term.

It is understood that the aforementioned example can be reversed and implemented from the perspective of a value or contrarian investor. Let’s put the focus on the companies with the 10 percent lowest average growth rates over the past five years. In the study by Chan et al. companies at the 10th percentile realised an annualised average earnings growth rate over the past five years of -6.4 percent. If the market handles these stocks as if their future would be a reflection of their past lacklustre growth, their stock prices could be reprimanded too heavily, offering lucrative opportunities for contrarian investors. In The Intelligent Investor (1949) Benjamin Graham remarks:

Our final category of opportunities for enterprising investment lies in the field of undervalued or bargain issues. These are the direct antitheses of growth stocks. If the latter may often sell to high because they are too popular, many not non-growth stocks often sell too low because they are too unpopular? We believe the answer to this question is definitely yes. A sound analogy may be drawn between a depressed general market and a stock that is individually unpopular. Just as declines of the whole market tend to go too far because public sentiment is generally pessimistic, so the price of many single issues may fall unduly low because their future is considered to be relatively unpromising. In both cases unfavorable circumstances are present – as actual developments, or perhaps only as prospects – and in both cases the response may be excessive and thus create a genuine opportunity for the intelligent and courageous investor. In the depths of a depressed or bear market the average person can see no ray of light ahead and can think only in terms of worse to come. So too, when an individual company or industry begins to lose ground in the economy, Wall Street is quick to assume that its future is entirely hopeless and it should be avoided at any price. The two types of reasoning are similar, and equally fallacious. (Emphasis added)

At the moment the 10th percentile of the price-to-earnings ratio for US stocks is 7.7. Applying the same methodology as before, an investment of $100, at an average annual growth rate in earnings of only 7.6 percent (< 9.8 percent) and a multiplier of 11.52 (25th percentile at the time of writing), would turn $100 into $216 over a five-year period.

Based on the aforementioned statements readers might have noticed the substantial dispersion of the price-to-earnings ratio for US stocks. The 10th percentile is 7.7; the 90th percentile is 50. The numbers closely correspond with those of Chan et al. from 1999 (7.4 for the 10th percentile, 53.9 for the 90th percentile). This large gap implies that the market expects companies in the top ten percent will realise a significantly higher growth over the upcoming years. Based on the evidence presented chances are small that these stocks will come up to the expectations. As long as this “relative pricing structure” stays in place, contrarian and patient value investors will be rewarded nicely for picking up the dogs of the past years at low valuations (guaranteeing of course the presence of sufficient financial strength, we refer to our April contribution).

-Conclusions

Once again the findings from Haugen (2010) and Chan et al. (2003) confirm some important insights from Benjamin Graham (1949) concerning the chances of successful implementation of, and the risks attached to a growth stock program, and they are comprehensively summarised in the following notice:

All in all, our evidence on the limited predictability of earnings growth suggests that investors should be wary of stocks that trade at very high multiples. Very few firms are able to live up to the high hopes for consistent growth that are built into such valuations. - Chan et al., 2003

At the same time the findings offer support for the courageous value investor. All too often investors once and for all write off the dogs of yesterday. Stocks that have been penalised for their low relative performance over the past years and that dispose of a strong financial position (guaranteeing that the companies survive a shake-out in the industry or a major reorganisation) can be picked up at low valuations providing patient investors with both a significant margin of safety and attractive long-term investment returns.

In the world of securities, courage becomes the supreme virtue after adequate knowledge and a tested judgment are at hand. – Graham, 1949

-Final note

Chan et al. provide evidence that investors actually are willing to pay higher valuations for stocks having achieved several consecutive years of strong growth, believing these companies will continue their stellar performance. Companies are sorted annually based on the average annual growth in earnings over a period of ten years and divided in deciles. Chan et al. subsequently calculate the median book-to-market (BM) at the start and end of this ten-year period for the ten decile portfolios. The results are shown in TABLE I. The median annual growth rates for the portfolios are shown in the first row. Looking at book-to-market, stocks with weak financial performance over the past ten years (decile one) were punished with significantly lower valuations; the book-to-market ratio increases from 0.653 to 1.048. The opposite evolution can be found with companies having the strongest growth rates over the past ten years (decile ten); these stocks are reasonably rewarded with the median book-to-market decrease from 0.817 to 0.622.

 TABLE I

 

D1

D2

D3

D4

D5

D6

D7

D8

D9

D10

Growth rate

-10.8

-3.4

-0.3

2.1

3.9

5.6

7.4

9.4

12.4

19.3

Beginning BM

0.653

0.699

0.696

0.699

0.726

0.707

0.723

0.706

0.742

0.817

Ending BM

1.048

0.860

0.796

0.761

0.748

0.734

0.725

0.673

0.647

0.622

-

-Summer months

In July we will discuss the concepts of Super Stocks versus Stupid Stocks as introduced by former professor Robert Haugen. In August we will provide the reader with an illustration of the value added of descriptive historical evidence. Taking a look at many finance programs let students and professionals believe that any knowledge of financial history is completely irrelevant. Nevertheless time and again the finance industry finds itself astonished when reoccurring financial crises are brought on by EXACTLY the same causes. ALL of them boil down to two causes: COMPLEXITY and LEVERAGE.

-References

Chan, L.K.C., J. Karceski, and J. Lakonishok. (2003). “The Level and Persistence of Growth Rates.” The Journal of Finance, Vol. LVIII, No. 2, 643-684.

Graham, B. (1949). The Intelligent Investor. HarperCollins Publishers.

Haugen, R.A. (2010). The New Finance – Overreaction, Complexity, and Their Consequences (Fourth Edition). Pearson Education.

Montier, J. (2009). Value Investing. Wiley.

Rayner, A.C. and I.M.D. Little. (1966). Higgledy Riggledy Growth Again. Basil Blackwell.

Blessed are those who expect nothing

May 2012

-Introduction

In our April contribution we have emphasised the importance of imposing quantitative measures of financial strength when either selecting individual stocks or building stock portfolios. Empirical studies point to a strongly negative relationship between financial risk and returns; distressed companies yield low (excess) stock returns. We concluded that the use of simple measures of financial strength can prevent that your stock portfolio encounters a permanent loss of capital.

Financial risk is one of the three components of the trinity of risk, as set forth by James Montier in Value Investing: Tools and Techniques for Intelligent Investing. The two other risks are valuation risk and business risk. In this contribution we discuss and illustrate the danger related to valuation risk, i.e. the danger of overpaying for the hope of growth. We start with a discussion of the practice of growth investing as set forth by Benjamin Graham in The Intelligent Investor (1949). In a second step we discuss some of the most important related findings documented in the academic literature, and we end with some conclusions.

-Old-School Value Investing

In The Intelligent Investor (1949) the reader gets an extensive discussion of investing in growth stocks in nearly all possible aspects. A growth company first is defined as a company that over the past years has realised above-average growth rates and which is expected to continue this trend. It is understood that identifying companies that have realised a strong growth, is quite simple.

From the selection the growth investor needs to select the firms with the greatest chance to prolong the growth pattern. Benjamin Graham however doesn’t believe in investors’ talent to identify these stocks ex ante. It should be noted that in the current accounting literature researchers do have another opinion. In Financial Statement Analysis and Security Valuation (2009) – one of the foremost books in the domain of financial statement analysis – it is believed that success in the field of equity investing requires the adoption of a forecast-oriented approach. It is however not realized that the exercise of special foresight cannot be learned out of books, i.e. by studying advanced valuation technologies and corresponding financial statement analyses. Based on Benjamin Graham’s insights, an extensive study of the related accounting literature as well as on our personal empirical work we decided to ban the forecast-oriented approach once and for all.

If the growth investor should succeed in selecting the companies with the highest future growth (which is quite unlikely), then another problem shows up: stocks with a strong business track record usually quote at high valuation multiples. Over the previous years the bright prospects have become evident to the great majority of investors such that these prospects almost always are overly discounted in current stock prices. Investors however fail to realise that high growth rates are not tenable; strong growth rates attract competitors so that finally sales growth will decrease and profit margins will become pressured. High valuations combined with results that fall short of high growth expectations, invariably result in major losses for the majority of growth investors. Otherwise said growth investors pay the price for immediate or short-term excitement. In the case of growth investing, excitement comes first, disappointment will appear later; in the case of value investing the reverse is often true, an observation also made by John Maynard Keynes in The General Theory. “Austrians” will definitely recognise the element of time preference coming into play here.

What is the maximum valuation that an investor should be allowed to pay for a growth company? Benjamin Graham pushes forward a maximum cyclically-adjusted price-earnings ratio of twenty. James Montier mentions a maximum normalized price-earnings ratio of sixteen.

Based on the above discussion we summarise Benjamin Graham’s insights regarding growth investing as follows:
(a) companies with strong future growth rates are not identifiable ex ante;
(b) investors are on average too optimistic about the future prospects of glamour stocks;
(c) investors are as a consequence systematically negatively surprised by the results of growth companies;
(d) investors underestimate the law of reversion to the mean in future growth rates.

In what follows we focus on items (b) and (c). The other two items will be discussed in a subsequent contribution.

-The Evidence

There are various studies worth mentioning the findings of which indicate that investors are way too optimistic regarding the future growth rates of glamour stocks and systematically are surprised in a negative way at the publications of their earnings. Here among other things we think about – in chronological order – Dreman and Berry (1995), La Porta (1996), Frankel and Lee (1998), Chan et al. (2000, 2003), Skinner and Sloan (2002), Arnott et al., (2009) and Haugen (2010). The contributions made by Chan et al. (2000), Arnott et al. (2009) and Haugen (2010) will be discussed at another occasion. Let’s have a look at the most crucial findings and conclusions of the other empirical studies.

Overly optimistic about the prospects of growth stocks

Two of the aforementioned studies (Frankel and Lee, 1998; Chan et al., 2003) test analysts’ long-term growth expectations against the actually realised figures. In their study, Frankel and Lee (1998) investigate the quality of IBES long-term earnings growth forecasts. Stocks are sorted based on their expected future growth rate over the next five years and subsequently divided in quintiles. Frankel and Lee compare the actually reported ROE in year three (Realised in TABLE I) with the ROE that was forecast ex ante (Forecast in TABLE I). The results show that analysts are, on average, overly optimistic. Furthermore analysts tend to be more over-optimistic for firms with the highest expected long-term growth forecasts (Q5 in TABLE I). For quintile five analysts expect a ROE in year three of 30.6 percent; the actually realised ROE is only 12.2 percent. Similar results are documented in the study by Chan et al. (2003). Over the 1982-1998 period the median of the distribution of IBES long-term growth forecasts is 14.5 percent; the median realised five-year growth rate is 9 percent (which is 5.5 percent less). For the firms with the highest expected growth rate in net income analysts project a median future growth rate of 22.4 percent (Q5 in TABLE I); the appropriate firms realise a median five-year growth rate of only 9.5 percent. Chan et al. attribute this overoptimism to cognitive biases and to the close ties between brokerage and investment banking business.

TABLE I
THE FOLLY OF FORECASTING

Frankel and Lee (1998)

Q1

Q2

Q3

Q4

Q5

Forecast

4.6

10.5

13.5

16.9

30.6

Realised

4.2

4.5

8.3

6.3

12.2

Chan et al. (2003)

Q1

Q2

Q3

Q4

Q5

Forecast

6.0

10.2

12.3

15.1

22.4

Realised

2.0

6.5

6.5

8.0

9.5

High expectations, low stock returns

In The Intelligent Investor (1949) Benjamin Graham claims that the future prospects of glamour companies are on average overly discounted in their current stock prices. La Porta (1996) shows that companies with higher long-term earnings forecasts tend to earn indeed low subsequent returns. The results are shown in TABLE II. Companies are sorted based on expected long-term earnings growth and subsequently divided in deciles. Companies with the lowest expectations reside in decile one (D1 in TABLE II); companies with the highest expectations penetrate decile ten (D10 in TABLE II). The earnings of companies in decile one are expected to grow at 2.3 percent per year over the next five years; for decile ten analysts expect a growth rate of 26.1 percent. The results in the table show that growth investors don’t have to wait too long before disappointment sets in. In the year after portfolio formation the average raw return of low expectation stocks is 20.9 percentage points higher than the return of high expectation stocks (29.5 percent versus 8.6 percent) during the sample period. On a size-adjusted basis low expectation stocks earn an 8.8 percent return, while high expectation stocks decline by 11.3 percent in size-adjusted terms.

TABLE II
BLESSED ARE THOSE WHO EXPECT NOTHING  

 

D1

D2

D3

D4

D5

D6

D7

D8

D9

D10

Forecast

2.3

4.2

5.7

7.1

8.6

10.2

11.8

13.7

16.1

26.1

Return

29.5

28.0

25.6

22.1

21.7

21.6

17.8

17.0

15.6

8.6

Size-adjusted return

8.8

7.5

4.8

1.7

1.3

0.7

-2.7

-3.8

-4.8

-11.3


Unpleasantly surprised growth investors

Following Dreman and Berry (1995) Skinner and Sloan (2002) examine how the stock price of value and growth firms reacts on average upon the publication of quarterly results. Here – besides the value/growth dimension – a distinction is made between firms whose publications are in accordance with, below or above expectations. Skinner and Sloan document that with the publication of negative earnings surprises growth investors are confronted with an asymmetrically large negative price response. The results are shown in TABLE III. In the first column stocks are sorted based on book-to-market and divided in quintiles; value stocks reside in quintile one, growth stocks reside in quintile five. Each quintile is subsequently divided into three categories based on the sign of the earnings surprise. – [0] (+) concern the companies whose results are below / [in accordance with] / (above) expectations. The mean quarterly abnormal stock returns for the zero and positive surprise portfolios show no systematic trend as a function of book-to-market. The negative surprise portfolios tell a different story. The mean quarterly abnormal returns decline monotonically across the book-to-market portfolios from a high of -3.6% for the value portfolio to a low of -7.3% for the growth portfolio. These findings indicate that the lower historical returns to growth stocks appear when these firms report negative earnings surprises.

TABLE III
GROWTH STOCKS HIT BY EARNINGS TORPEDOES

 

-

0

+

Q1 – Value stocks

-3.6

1.1

5.4

Q2

-3.9

2.0

4.9

Q3

-4.9

1.7

5.3

Q4

-5.8

1.5

5.7

Q5 – Growth stocks

-7.3

1.7

6.3

Skinner and Sloan document furthermore that the asymmetric price response to negative earnings surprises is responsible for 80 percent (!) of the long-term return differential between growth stocks and value stocks. Consequently investors are advised to head the conclusion formulated in the title of their paper: “Don’t Let an Earnings Torpedo Sink Your Portfolio.”

Let’s rap up the discussion of the aforementioned empirical findings:
(a) analysts – and by extension most investors – are overly optimistic about the prospects of glamour stocks;
(b) companies with high expected growth rates produce low stock returns;
(c) growth stocks are hit doubly hard in case of negative surprises.

-Conclusions

In this contribution we verified two claims made by Benjamin Graham (1949) concerning growth investing.

Claim one

The chief obstacle to success lies in the stubborn fact that if the favorable prospects of a concern are clearly apparent they are almost always reflected already – and often overdiscounted – in the current price of the stock. Buying such an issue is like betting on a top-heavy favorite in a horse race. The chances may be on your side, but the real odds are against you. - Graham, 1949

Claim two

What seems to happen, rather, is that the price remains high until the earnings actually show a definite falling off – which invariably seems to take the followers of the issue by surprise. Then we have the market decline usually associated with a disappointing development – a decline perhaps intensified by the fact that the price level of the growth stock had been dangerously high. - Graham, 1949

The presented empirical evidence indicates that most investors have failed to follow Graham’s sound investment advice. Via Frankel and Lee (1998) and Chan et al. (2003) we find that long-term growth estimates of analysts are overly optimistic. La Porta (1996) shows that companies with the highest expected long-term earnings growth rates earn the lowest stock returns. These results indicate that, on average, caution should be exercised before relying too heavily on long-term earnings growth forecasts made by financial analysts as estimates of expected growth rates in valuation studies. Secondly, confirming the second claim, Skinner and Sloan (2002) indicate that growth stocks are hit doubly hard when confronted with disappointing earnings. We conclude that preferably investors avoid stocks with significantly above average valuation multiples no matter how attractive, exciting, exotic, fantastic, sexy, revolutionary, etc. the growth story of your favourite glamour company looks.

-Next month

After reading the above argumentation and corresponding empirical evidence most investors might be convinced that – particularly concerning glamour companies – expected growth rates have been overestimated in the past, and consequently it is advisable to assume a more conservative position in the future. Nevertheless some investors (the majority, I guess) might still believe that they belong to the exclusive club of chosen investors who – by means of focusing on future growth – are able to distinguish between the successful and less successful glamour stocks. Apart from the barely successful analysts’ forecasts investors can use other sources of information in order to track down successful growth stories. We think about the extrapolation of the past trend in growth rates (whether or not supported by sophisticated statistical techniques), quantitative information available in the financial statements and/or qualitative information regarding for instance management and promising technologies.

-References

Arnott, R.D., F. Li, and K.F. Sherrerd. (2009). “Clairvoyant Value II: The Growth/Value Cycle.” The Journal of Portfolio Management, Vol. 35, No. 4.

Chan, L.K.C., J. Karceski, and J. Lakonishok. (2000). “New Paradigm or Same Old Hype in Equity Investing?” Financial Analysts Journal, 23-36.

Chan, L.K.C., J. Karceski, and J. Lakonishok. (2003). “The Level and Persistence of Growth Rates.” The Journal of Finance, Vol. LVIII, No. 2, 643-684.

Dreman, D.N., and M.A. Berry. (1995). “Overreaction, Underreaction, and the Low-P/E Effect.” Financial Analysts Journal, 21-30.

Frankel, R., and C.M.C. Lee. (1998). “Accounting valuation, market expectation, and cross-sectional stock returns.” Journal of Accounting and Economics 25, 283-319.

Graham, B. (1949). The Intelligent Investor. HarperCollins Publishers.

Haugen, R.A. (2010). The New Finance – Overreaction, Complexity, and Their Consequences (Fourth Edition). Pearson Education.

La Porta, R. (1996). “Expectations and the Cross-Section of Stock Returns.” The Journal of Finance, Vol. LI, No. 5, 1715-1742.

Montier, J. (2009). Value Investing. Wiley.

Penman, S. (2009). Financial Statement Analysis and Security Valuation. McGraw-Hill.

Skinner, D.J., and R.G. Sloan. (2002). “Earnings Surprises, Growth Expectations, and Stock Returns or Don’t Let an Earnings Torpedo Sink Your Portfolio.” Review of Accounting Studies, 7, 289-312.

van Dijk, W.W., M. Zeelenberg, and J. van der Pligt. (2003). “Blessed are those who expect nothing: Lowering expectations as a way of avoiding disappointment.” Journal of Economic Psychology, 24, 505-516.

The determinants of financial strength

April 2012

-Introduction

In the chapter Clear and Present Danger: The Trinity of Risk from the book Value Investing: Tools and Techniques for Intelligent Investing by James Montier, he subdivides the fundamental risk of a stock in three components: (a) valuation risk, (b) business/earnings risk and (c) balance sheet/financial risk. When assessing balance sheet/financial risk, Montier makes use of Altman’s Z-score (1968).

Altman’s Z-score consists of five accounting signals:
* liquidity criterium: working capital / total assets;
* solvency criterium: retained earnings / total assets;
* solvency criterium: market value of equity / book value of total liabilities;
* operating efficiency criterium: earnings before interest and taxes / total assets;
* operating efficiency criterium: sales / total assets.

In The Intelligent Investor (1949) Benjamin Graham considered an industrial company’s finances as not conservative unless common equity represented at least half of the total assets.

In this contribution we give an overview of quantitative financial statement measures that can be used by investors in order to significantly increase the financial strength of their stock portfolio. To that end we discuss two more recent research studies that investigate the relationship between financial strength and stock returns. We conclude that the majority of Altman’s variables still are relevant.

-The determinants of distress risk

In December 2008 the study “In Search of Distress Risk” by Campbell, Hilscher and Szilagyi was published in The Journal of Finance. In the first step of their analysis Campbell et al. use a combination of accounting data and market data to develop an empirical measure of financial distress. The accounting data concern the ratio of net income to the market value of assets (NI/MTA), the ratio of total liabilities to the market value of assets (TL/MTA), the ratio of a company’s cash and short-term assets to the market value of assets (CASH/MTA) and the market-to-book ratio (MB). As an alternative the denominator in previous ratios, i.e. the market value of assets, can be replaced by the book value of total assets and then we get NI/TA, TL/TA en CASH/TA respectively. Campbell et al. however show that scaling by the market value of total assets has added value. The market data concern the stock return of each company over the past month as compared to the S&P500 (EXRET), the standard deviation of each firm’s daily stock return over the past three months (SIGMA) and the ratio of the market capitalization to the market capitalization of the S&P500.

TABLE I shows the descriptive statistics of the aforementioned accounting variables for companies one month prior to their bankruptcy.

TABLE I 

 

NI/TA

NI/MTA

TL/TA

TL/MTA

CASH/MTA

MB

Mean

-0.054

-0.040

0.796

0.763

0.044

2.430

Median

-0.054

-0.047

0.872

0.861

0.021

1.018

Std. Dev.

0.043

0.030

0.174

0.210

0.062

2.509

TABLE II shows the same descriptive statistics for all companies in the sample.

TABLE II

 

NI/TA

NI/MTA

TL/TA

TL/MTA

CASH/MTA

MB

Mean

-0.001

0.000

0.506

0.445

0.084

2.041

Median

0.007

0.006

0.511

0.427

0.045

1.557

Std. Dev.

0.034

0.023

0.252

0.280

0.097

2.579

From a fundamental point of view companies close to bankruptcy are loss-making (average NI/MTA at -4.0 percent), are characterised by a very high debt burden (average TL/MTA at 76.3 percent) and have a weak liquidity position (average CASH/MTA at 4.4 percent). No surprises here.

The aforementioned accounting and market variables are used to predict the probability of bankruptcy within the next twelve months. Companies are subsequently sorted based on predicted bankruptcy probability and divided in percentiles and deciles. Average excess returns are reported in TABLE III; the returns are strongly and monotonically declining in bankruptcy risk (GRAPH I). The lowest-risk 5% of stocks (indicated by 0005) realize an average excess return of 3.3 percent per year; companies with the one-percent highest bankruptcy risk (indicated by 9900) realize a market-adjusted annual return of -16.14 percent.

TABLE III 

 

0005

0510

1020

2040

4060

6080

8090

9095

9599

9900

Mean excess return

3.30

1.48

0.97

0.93

0.58

-0.23

-4.41

-7.97

-6.80

-16.14

The above descriptive statistics can be used by investors to avoid companies with particular weak fundamentals. In TABLE I we notice that the average leverage of close to bankrupt companies is very high relative to their assets; average leverage – as measured by TL/TA – is 79.6 percent. The standard deviation is 17.4 percent. Investors can for example remove all companies that are within two standard deviations of the mean; this implies screening out all stocks with TL/TA higher than 44.8 percent. Similar rules can be applied for the other accounting variables.

GRAPH I: LOW BANKRUPTCY PROBABILITY, HIGH EXCESS RETURN-

-

-The role of financial strength in times of industry distress

In the study “Financial Distress and Corporate Performance” Opler and Titman (1994) investigate the performance of stocks in distressed industries. Within industries the researchers distinguish between companies having low and high financial leverage. Financial leverage is measured as the book value of debt divided by the book value of assets. They find that companies with the highest financial leverage realize significantly lower stock returns. They document furthermore that companies with high financial leverage are hit extra hard when they are part of an industry in distress. These companies experience a decline in market valuation over a two-year period that in absolute terms is 11.9 percent higher compared to companies in the same distressed industry with low financial leverage. Based on the documented findings Opler and Titman conclude that there is a positive relationship between financial strength and stock returns in industry downturns. Consequently the findings of this study are important for investors who want to limit the downside risk of their stock portfolio in times of industry-specific and/or economic-wide distress. The message is clear: avoid companies with high (industry-adjusted) financial leverage.

-Conclusion

In The Intelligent Investor (1949) Benjamin Graham notices that investors often lose track of the financial risk profile of their portfolio at the height of economic booms. During a sustained bull market, when it is easy to make money by following the crowd, investors gradually lose interest in the quality of the securities they are buying and become more and more involved in the exciting game of beating the stock market.

Hence we recommend always guaranteeing – either on a stock level or on a portfolio level – minimal safety margins regarding financial strength prior to taking a look at the two other risks, valuation risk and business risk. Based on the above discussed quantitative measures of financial strength value investors can work out investment strategies with an extremely low financial risk profile, guaranteeing not only an almost non-existent “permanent loss of capital” – as coined by Benjamin Graham – but also strong performance during downturns and significant long-term outperformance.

-References

Altman, E.I. (1968). “Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy.” The Journal of Finance, Vol. XXIII, No. 4, 589-609.

Campbell, J.Y., J. Hilscher, and J. Szilagyi. (2008). “In Search of Distress Risk.” The Journal of Finance, Vol. LXIII, No. 6., 2899-2939.

Montier, J. (2009). Value Investing. Wiley.

Opler, T.C., and S. Titman. (1994). “Financial Distress and Corporate Performance.” The Journal of Finance, Vol. XLIX, No. 3, 1015-1040.

The New Finance

March 2012

-Introduction

The New Finance was mainly developed by former professor Robert Haugen and is set forth in the publications mentioned below. There’s no doubt that his publications are one of the most principal sources of inspiration for investors within the academic literature. Many parts are definitely thought-provoking. In Chapter 12 of The New Finance for example he reflects upon the epistemological foundations of the finance area. “Austrians” will immediately notice some similarities with the more profound epistemological insights by Ludwig von Mises. Many of his writings offer exciting opportunities for further reflections and future research.

-The real determinants of expected stock returns

In 1996 Robert Haugen and Nardin Baker published the first version of their expected return ad hoc factor model in The Journal of Financial Economics. Based on five categories of variables – among which are (fundamental) risk factors, measures of cheapness, measures of profitability and technical criteria – they try to predict future returns of individual stocks as accurately as possible.

GRAPH I: ESTIMATING THE PAYOFF TO EARNINGS-TO-PRICE

-

-Inductive approach

The modus operandi of The New Finance is illustrated by means of GRAPH I. For a specific period – e.g. a month – the relationship between for example the earnings-to-price ratio and the realised return for each stock is estimated using linear regression. The estimated relationship can be used to predict the payoffs for each stock over the next period. Instead of using only one factor – i.e. the earnings-to-price ratio – investors can simultaneously estimate expected stock returns using numerous factors. The method is called an expected return factor model. In the original version of the model Haugen and Baker introduce seventy-one factors. Based on the empirical results of this inductive approach Haugen and Baker arrive at some very interesting characteristics of extremely profitable and extremely unprofitable stock portfolios.

-Test

During the months to come we will cast a critical look at our self-developed inductive quantitative model; methodology, portfolio returns and portfolio characteristics systematically will be documented on our blog. Stay tuned.

-Literature

As part of The New Finance we refer to the following books and articles:

Haugen, R.A., and N.L. Baker. (1996). “Commonality in the determinants of expected stock returns.” Journal of Financial Economics, Vol. 41, 401-439.

Haugen, R.A. (2002). The Inefficient Stock Market (Second Edition). Pearson Education.

Hanna, J.D., and M.J. Ready. (2005). “Profitable predictability in the cross section of stock returns.” Journal of Financial Economics, Vol. 78, 463-505.

Haugen, R.A., and N.L. Baker. (2008). “Case Closed.” Working Paper, Quantitative Investments.

Haugen, R.A. (2010). The New Finance – Overreaction, Complexity, and Their Consequences (Fourth Edition). Pearson Education.

Greenblatt, J. (2006). The Little Book that Beats the Market. Wiley.

Old-school value: Psychology

March 2012

-Introduction

All too often one departs from the assumption that the cricital success factor when managing a stock portfolio, is to have a thorough command of complex mathematical formulae. In our opinion Benjamin Graham was right when he wrote in The Analysts Journal (1958):

In 44 years of Wall Street experience and study, I have never seen dependable calculations made about common stock values, or related investment policies, that went beyond simple arithmetic or the most elementary algebra. Whenever calculus is brought in, or higher algebra, you could take it as a warning signal that the operator was trying to substitute theory for experience, and usually also to give speculation the deceptive guise of investment.

Successful intelligent investing primarily requires an exceptionally mental or psychological attitude. This insight – the importance of which cannot be overstated – has substantial implications regarding the way in which investment processes are structuralised and returns of value funds are assessed.

Intelligent investment is more a matter of mental approach than it is of technique. A sound mental approach toward stock fluctuations is the touchstone of all successful investment under present-day conditions. - Graham, 1949

-Obsession with short-term results and/or benchmarks

In his monthly market commentary of March 1, 2012, investor and Austrian economist dr. Marc Faber discusses in detail the historical results of value investing by means of the book What Works on Wall Street by James O’Shaugnessy. Faber concludes that value strategies on the long term realise significantly higher returns compared to growth strategies. Yet he immediately wonders why the majority of professional and individual investors fails to equal the results of very simple quantitative value strategies. According to him the answer is due to a lack of discipline and patience.

In his new book The Big Secret for the Small Investor, value investor Joel Greenblatt states an excellent anecdote illustrative for the lack of discipline and patience. Greenblatt indicates that the best mutual fund over the 2000-2009 period has realised an average annual return of +18%. Yet the average investor in this fund realised an average annual return of … -11%. How can this substantial difference be explained? Simple. Every time the fund underperformed, people left, every time the market went down, people left, every time the fund outperformed the market, new investors scrambled to get in just after the outperformance. With these decisions the average investor ended up losing 11 percent per year. Otherwise said investors have always bought on high levels and sold on low levels. The returns realised and common sense indicate that this modus operandi is pretty unsuccessful.

The focus of a value investor should be on fundamental safety margins rather than short-term price movements and/or comparisons to arbitrary benchmarks.

As in all other activities which emphasize price movements first and underlying values second, the work of many intelligent minds constantly engaged in this field tends to be self-neutralizing and self-defeating over the years. - Graham, 1949

-Three recommendations for developing the right mental approach

We state three recommendations for value investors. They are:
* focus on objective fundamental safety margins;
* do not focus on short-term fluctuations and avoid using benchmarks;
* use an investment horizon of at least (!) five years.

An additional fourth recommendation could be included, more specifically:
* increase your position in value stocks and/or value funds after strong market corrections (15% to 20%), based on an outlined financial plan with an investment horizon of at least (!) five years.

-Literature

As part of Old-School Value Investing: Psychology we advance the following books and articles:

Faber, M. (2012). March Monthly Market Commentary.

Graham, B. (1949). The Intelligent Investor. HarperCollins Publishers.

Graham, B. and D.L. Dodd. (1934). Security Analysis. The McGraw-Hill Companies.

Greenblatt, J. (2011). The Big Secret for the Small Investor. Wiley.

Montier, J. (2007). Behavioural Investing. Wiley.

Montier, J. (2009). Value Investing. Wiley.

Old-school value: Technique

March 2012

-Introduction

The past years we have paid attention to the study of the empirical relationship between business fundamentals – as reflected in the historical financial statements – and stock returns. This research to a great extent confirmed the investment canon developed by Benjamin Graham in Security Analysis (1934) and The Intelligent Investor (1949). The basic principles of intelligent investing that he set forth there have remained virtually intact and unassailable.

-Investment canon of Benjamin Graham

The most important issue in the investment philosophy of Benjamin Graham – from a technical point of view – is to build in fundamental safety margins for every company that is included in a value portfolio.

Confronted with a like challenge to distill the secret of sound investment into three words, we venture the motto, MARGIN OF SAFETY. This is the thread that runs through all the preceding discussion of investment policy – often explicitly, sometimes in a less direct fashion. - Graham, 1949

Safety margins are built in by focusing on stocks that are cheap relative to fundamentals – assets, normalized earnings, dividends, etc. – and that possess a strong financial position, a strong dividend track-record, etc.

The security analyst develops and applies standards of safety by which he can conclude whether a given bond or preferred stock may be termed sound enough to justify purchase for investment. These standards relate primarily to past average earnings, but they are concerned also with capital structure, working capital, asset values, and other matters. - Graham, 1949

Forecasts about the companies’ future results are not a component of the safety margins’ definition; forecasts are considered to be purely speculative.

In the prewar period it was the well-considered view that when prime emphasis was laid upon what was expected of the future, instead of what had been accomplished in the past, a speculative attitude was thereby taken. Speculation, in its etymology, meant looking forward; investment was allied to “vested interests,” – to property rights and values taking root in the past. The future was uncertain, therefore speculative; the past was known, therefore the source of safety. - Graham & Dodd, 1934

The focus on tangible fundamentals implies an inherently critical attitude vis-à-vis growth stocks and promising companies.

-Literature

As part of Old-School Value Investing: Technique we advance the following books:

Graham, B. (1949). The Intelligent Investor. HarperCollins Publishers.

Graham, B. and D.L. Dodd. (1934). Security Analysis. The McGraw-Hill Companies.

Greenblatt, J. (2006). The Little Book that Beats the Market. Wiley.

Montier, J. (2007). Behavioural Investing. Wiley.

Montier, J. (2009). Value Investing. Wiley.