Gmo the value vs growth dilemma

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  • 1. Value versus growth: Some statistical evidence Bruce Greenwald & Tano Santos Columbia Business School Columbia University
  • 2. Introduction • We focus in this course on the fundamental value of the investment at the expense of any other consideration. • In particular: Value investing is about levels and the comparison between value and the market price. • Specifically, we can classify the approaches to investing along the following dimensions.
  • 3. Approaches to investing 3 Approaches to investment Efficient Markets •Diversification •Asset Allocation •Cost minimization
  • 4. Approaches to investing 4 Approaches to investment Efficient MarketsShort term •Diversification •Asset Allocation •Cost minimization Fundamental Value Changes •Current Price vs. forecast change •Micro •Macro Technical •Value strategies •Momentum •Price/Volume patterns
  • 5. Approaches to investing 5 Approaches to investment Efficient MarketsShort termLong term Fundamental Value Levels •Diversification •Asset Allocation •Cost minimization •Mkt. price vs. value Fundamental Value Changes •Current Price vs. forecast change •Micro •Macro Technical •Value strategies •Momentum •Price/Volume patterns
  • 6. Introduction • The essential value investing principles are: 1. Identification of the firms whose value is reliably calculable by you (circle of competence.) 2. Among these firms, invest in those whose market price (equity plus debt) is below your calculated value by an appropriate margin of safety (1/3 to 1/2). • Thus, value investing emphasizes specialization and it focuses on specific names and emphasizes prudence to guarantee the protection of principal. • Understanding the principles above is the purpose of this course. 6
  • 7. Introduction • Today though we ask the following question: - Are there superior returns associated with investing in companies which are “cheap” relative to some measure of fundamentals? • For instance, if we classify firms according to their book-to-market, do firms which have high book-to- market (BE/ME) yield on average higher returns than do firms with low BE/ME? • To preview the answer: - Value (high BE/ME) stocks command higher average returns though they are not riskier. 7
  • 8. Outline • In what follows we divide the presentation in two parts: 1. The cross section of stock returns: a) Value strategies b) Momentum c) Long term reversal d) Industry 2. The market portfolio • Throughout it is important to remember that none of this is what we refer to as value investing, which is the application of simple principles to the analysis of individual names. 8
  • 9. Outline • In what follows we divide the presentation in two parts: 1. The cross section of stock returns: a) Value strategies b) Momentum c) Long term reversal d) Industry 2. The market portfolio • Throughout it is important to remember that none of this is what we refer to as value investing, which is the application of simple principles to the analysis of individual names. 9 Not today
  • 10. THE CROSS SECTION 10
  • 11. The value premium • To assess whether value stocks, stocks with high book-to-market, systematically yield high returns than growth stocks we proceed as follows: - We take all publicly traded stocks and sort them according to BE/ME into ten portfolios - Then we construct a “value strategy” by going long the portfolio of stocks with high book-to-market which we fund by shorting a portfolio of stocks with low book-to-market. - The resulting portfolio is called the “High-Minus-Low” portfolio, or HML. - We then compute the monthly returns of this HML portfolio since 1927. 11
  • 12. Value sorts 12 Stock 1 Stock 2 Stock 3 Stock 4 Stock 5 Stock 6 Stock 7 Stock 8 Stock 9 Stock 10 June of year t
  • 13. Value sorts 13 Stock 1 Stock 2 Stock 3 Stock 4 Stock 5 Stock 6 Stock 7 Stock 8 Stock 9 Stock 10 June of year t Low book-to-market High book-to-market
  • 14. Value sorts 14 Stock 1 Stock 2 Stock 3 Stock 4 Stock 5 Stock 6 Stock 7 Stock 8 Stock 9 Stock 10 Stock 1 Stock 2 Stock 3 Stock 4 Stock 5 Stock 6 Stock 7 Stock 8 Stock 9 Stock 10 Growth portfolio Value portfolio June of year t
  • 15. Value sorts 15 Stock 1 Stock 2 Stock 3 Stock 4 Stock 5 Stock 6 Stock 7 Stock 8 Stock 9 Stock 10 Stock 1 Stock 2 Stock 3 Stock 4 Stock 5 Stock 6 Stock 7 Stock 8 Stock 9 Stock 10 Growth portfolio Value portfolio Stock 3 Stock 2 Stock 7 Stock 9 Stock 8 Stock 1 Stock 10 Stock 4 Stock 6 Stock 5 Stock 3 Stock 2 Stock 7 Stock 9 Stock 8 Stock 1 Stock 10 Stock 4 Stock 6 Stock 5 Growth portfolio Value portfolio June of year t June of year t+1
  • 16. Value versus growth: 1927-2008 16 -60 -40 -20 0 20 40 60 1927 1929 1931 1933 1935 1937 1939 1941 1943 1945 1947 1949 1951 1953 1955 1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 Mkt-RF Annual market returns in excess of the one year treasury bill. 1927-2008. Source: Ken French database
  • 17. Value versus growth: 1927-2008 17 -60 -40 -20 0 20 40 60 1927 1929 1931 1933 1935 1937 1939 1941 1943 1945 1947 1949 1951 1953 1955 1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 Mkt-RF Great Depression – I (1929) Great Depression – II (1937) Oil shock – I (1973) Oil shock – II (1981) End of tech. bubble (2000) Great Recession - (2008) Annual market returns in excess of the one year treasury bill. 1927-2008. Source: Ken French database
  • 18. Value versus growth: 1927-2008 18 -60 -40 -20 0 20 40 60 1927 1929 1931 1933 1935 1937 1939 1941 1943 1945 1947 1949 1951 1953 1955 1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 Mkt-RF HML Great Depression – I (1929) Great Depression – II (1937) Oil shock – I (1973) Oil shock – II (1981) End of tech. bubble (2000) Great Recession - (2008) Annual market returns in excess of the one year treasury bill rate and the annual returns on a zero investment portfolio that is long value stocks and short growth. 1927-2008. Source: Ken French database
  • 19. Value versus growth: 1927-2008 Growth Port. 2 Port. 3 Port. 4 Port. 5 Port. 6 Port. 7 Port. 8 Port. 9 Value Avge. BE/ME .20 .37 .49 .61 .72 .84 .97 1.14 1.40 2.21 Avge. excess return (ann. %) 3.84 5.45 5.71 5.67 5.52 6.60 7.35 8.17 9.36 10.96 Average book-to-market, and excess returns for ten book-to-market sorted portfolios of all stocks in Compustat; annualized; value weighted; 1963-01 to 2009-09; the portfolios are resorted at the end of June and BE/ME is book equity at the last fiscal year end of the prior calendar year divided by ME at the end of December of the prior year. • So what are the returns of those ten sorted portfolios?
  • 20. Value versus growth: 1927-2008 • So in conclusion the value portfolio, the portfolio of stocks with high book to market, earns, on average a bit over 7% excess return over the growth portfolio. • The evidence so far has exclusively focused on the US. • But, what about the international evidence? • Unfortunately, the available data does not extend back as far as it does in the US, but the overall picture is identical: 20
  • 21. Value vs. growth: international evidence Market Value Growth Japan 1.00 1.53 .64 UK 1.21 1.61 1.16 Germany 1.47 1.63 1.36 France 1.34 1.71 1.23 Spain 1.13 1.17 .99 Australia 1.33 1.65 1.15 Canada 1.13 1.15 .98 21 Monthly returns 1975-01 to 2007-12 (except for Canada where the sample starts in 1977-01) in percentages Source: Ken French
  • 22. The value premium: Is it risk? • To reiterate: Value, the strategy of buying high BE/ME stocks, yields superior returns to one that focuses on growth or glamour stocks. • Why? Two possible answers: 1. Risk - The higher average return of value portfolios simply reflects a compensation for risk. 2. Mispricing - The higher average return of value portfolios reflect a systematic undervaluation of value stocks relative to growth • Let’s try to shed some light on this issue. 22
  • 23. The value premium: Is it risk? • If the CAPM is a proper representation of risk then it must be the case that value stocks have higher betas than growth stocks. • Do they? Does the value portfolio have a higher beta than the growth portfolio? To answer this: - Estimate βs by running a time series regression of the excess returns of each of the ten portfolios on the market excess return (the market model). - Calculate the fitted CAPM average excess return for each of the ten portfolios and compare them to the actual average excess return in sample. 23
  • 24. The value premium: Is it risk? 3 4 5 6 7 8 9 10 11 3 4 5 6 7 8 9 10 11 CAPMfittedexcessreturns Average excess returns Average excess returns of ten book-to-market sorted portfolios against CAPM fitted excess returns. 1963-1 – 2009-09. Source: Ken French database.
  • 25. The value premium: Is it risk? 3 4 5 6 7 8 9 10 11 3 4 5 6 7 8 9 10 11 CAPMfittedexcessreturns Average excess returns This is where the dots should be if the CAPM betas captured risk Average excess returns of ten book-to-market sorted portfolios against CAPM fitted excess returns. 1963-1 – 2009-09. Source: Ken French database.
  • 26. Is it risk? The CAPM and the value premium 3 4 5 6 7 8 9 10 11 3 4 5 6 7 8 9 10 11 CAPMfittedexcessreturns Average excess returns Average excess returns of ten book-to-market sorted portfolios against CAPM fitted excess returns. 1963-1 – 2009-09. Source: Ken French database. Extreme Growth Extreme Value
  • 27. The value premium: Is it risk? 3 4 5 6 7 8 9 10 11 3 4 5 6 7 8 9 10 11 CAPMfittedexcessreturns Average excess returns Average excess returns of ten book-to-market sorted portfolios against CAPM fitted excess returns. 1963-1 – 2009-09. Source: Ken French database. Extreme growth yields less than what is predicted by the CAPM Extreme value yields more than what is predicted by the CAPM
  • 28. The value premium: Is it risk? Growth Port. 2 Port. 3 Port. 4 Port. 5 Port. 6 Port. 7 Port. 8 Port. 9 Value Avge. BE/ME .20 .37 .49 .61 .72 .84 .97 1.14 1.40 2.21 Avge. excess return (ann. %) 3.84 5.45 5.71 5.67 5.52 6.60 7.35 8.17 9.36 10.96 CAPM βs 1.07 1.01 .98 .99 .91 .92 .86 .89 .92 1.05 CAPM fitted excess returns 5.49 5.17 5.02 5.07 4.66 4.71 4.40 4.56 4.71 5.38 Average book-to-market, excess returns, CAPM betas and CAPM fitted excess returns for ten book-to-market sorted portfolios of all stocks in Compustat; annualized; value weighted; 1963-01 to 2009-09; the portfolios are resorted at the end of June and BE/ME is book equity at the last fiscal year end of the prior calendar year divided by ME at the end of December of the prior year.
  • 29. The value premium: Is it risk? • The conclusion is striking: Value stocks have 7% (annual) higher average returns than growth stocks but the betas cannot explain any of it: - Technically: Whereas average excess returns are an increasing function of BE/ME betas have a flat relation with returns. - That is, the CAPM cannot explain the superior returns of value strategies. • But the CAPM may not be the right description of risk - Are value stocks risky in that they do specially bad in bad times relative to growth and thus the higher premium? 29
  • 30. Value versus growth: 1927-2008 30 -60 -40 -20 0 20 40 60 1927 1929 1931 1933 1935 1937 1939 1941 1943 1945 1947 1949 1951 1953 1955 1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 Mkt-RF HML Great Depression – I (1929) Great Depression – II (1937) Oil shock – I (1973) Oil shock – II (1981) End of tech. bubble (2000) Great Recession - (2008) Annual market returns in excess of the one year treasury bill rate and the annual returns on a zero investment portfolio that is long value stocks and short growth. 1927-2008. Source: Ken French database
  • 31. The value premium: Is it risk? -40 -30 -20 -10 0 10 20 30 40 192607 192610 192701 192704 192707 192710 192801 192804 192807 192810 192901 192904 192907 192910 193001 193004 193007 193010 193101 193104 193107 193110 193201 193204 193207 193210 193301 193304 193307 193310 193401 193404 193407 193410 193501 193504 193507 193510 193601 193604 193607 193610 193701 193704 193707 193710 193801 193804 193807 193810 193901 193904 193907 193910 Mkt-RF Monthly market returns in excess of the one month treasury bill – 1926-07 – 1939-12. Source: Ken French database.
  • 32. The value premium: Is it risk? -40 -30 -20 -10 0 10 20 30 40 192607 192610 192701 192704 192707 192710 192801 192804 192807 192810 192901 192904 192907 192910 193001 193004 193007 193010 193101 193104 193107 193110 193201 193204 193207 193210 193301 193304 193307 193310 193401 193404 193407 193410 193501 193504 193507 193510 193601 193604 193607 193610 193701 193704 193707 193710 193801 193804 193807 193810 193901 193904 193907 193910 Mkt-RF Monthly market returns in excess of the one month treasury bill – 1926-07 – 1939-12. Source: Ken French database. 1929-10 1931-09 1932-05 1938-03
  • 33. The value premium: Is it risk? -40 -30 -20 -10 0 10 20 30 40 192607 192610 192701 192704 192707 192710 192801 192804 192807 192810 192901 192904 192907 192910 193001 193004 193007 193010 193101 193104 193107 193110 193201 193204 193207 193210 193301 193304 193307 193310 193401 193404 193407 193410 193501 193504 193507 193510 193601 193604 193607 193610 193701 193704 193707 193710 193801 193804 193807 193810 193901 193904 193907 193910 Mkt-RF Value-Growth Monthly market returns in excess of the one month treasury bill and the monthly returns on a zero investment portfolio that is long value stocks and short growth. 1926-07 – 1939- 12. Source: Ken French database 1929-10 1931-09 1932-05 1938-03
  • 34. The value premium: Is it risk? -20 -15 -10 -5 0 5 10 15 200301 200303 200305 200307 200309 200311 200401 200403 200405 200407 200409 200411 200501 200503 200505 200507 200509 200511 200601 200603 200605 200607 200609 200611 200701 200703 200705 200707 200709 200711 200801 200803 200805 200807 200809 200811 200901 200903 200905 200907 200909 Mkt-RF Monthly market returns in excess of the one month treasury bill – 2003-01 –2009-10. Source: Ken French database. 2008-10 2008-09
  • 35. The value premium: Is it risk? -20 -15 -10 -5 0 5 10 15 200301 200303 200305 200307 200309 200311 200401 200403 200405 200407 200409 200411 200501 200503 200505 200507 200509 200511 200601 200603 200605 200607 200609 200611 200701 200703 200705 200707 200709 200711 200801 200803 200805 200807 200809 200811 200901 200903 200905 200907 200909 Mkt-RF Value-Growth 2008-10 2008-09 Monthly market returns in excess of the one month treasury bill and the monthly returns on a zero investment portfolio that is long value stocks and short growth. 2003-01 –2009-10. Source: Ken French database 2008-09
  • 36. The value premium: Is it risk? -30 -20 -10 0 10 20 30 40 50 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 Mkt-RF Annual market returns in excess of the one year treasury bill. 1993-2006. Source: Ken French database
  • 37. The value premium: Is it risk? -30 -20 -10 0 10 20 30 40 50 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 Mkt-RF Value-Growth Annual market returns in excess of the one year treasury bill rate and the annual returns on a zero investment portfolio that is long value stocks and short growth. 1993-2006. Source: Ken French database
  • 38. The value premium: Is it risk? 38 -30 -20 -10 0 10 20 30 40 50 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Growth Value Annual market returns of a value weighted portfolio of the top (value) and bottom (growth) 20% of stocks sorted by BE/ME . 1993-2006. Source: Ken French database
  • 39. The value premium: Is it risk? • Thus it looks that value stocks do relatively better than growth stocks in bad (market) times (though not always!): - The Great Depression first shock of 1929 - The oil shocks of 1970s and early 1980s - The end of the technology bubble. • And worse than growth during the tech bubble. • If value stocks were riskier than growth they should be doing worse in bad times, as measured by the market, but they don’t seem to, at least in some significant episodes. 39
  • 40. The value premium: Is it risk? • Before we turn to a potential behavioral explanation it is worth going deeper into the issue of whether value was always less risky than growth (according to the CAPM!) • For this we run the following exercise we estimate betas using a trailing five year window with data starting in 1926-07 all the way up to 2009-09. • As before we use the market model and we estimate betas by running time series regressions of excess returns for the BE/ME portfolios on market excess returns. 40
  • 41. The value premium: Is it risk? 41 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 193007 193112 193305 193410 193603 193708 193901 194006 194111 194304 194409 194602 194707 194812 195005 195110 195303 195408 195601 195706 195811 196004 196109 196302 196407 196512 196705 196810 197003 197108 197301 197406 197511 197704 197809 198002 198107 198212 198405 198510 198703 198808 199001 199106 199211 199404 199509 199702 199807 199912 200105 200210 200403 200508 200701 200806 Growth Monthly time series of market betas for the value and growth portfolios, defined as the top and bottom decile,respectively,of the book-to-market sorted portfolios for the sample 1926-07 to 2009-09.The betas are estimated using a rolling five year window. The monthly returns are from Ken French’s data base.
  • 42. The value premium: Is it risk? 42 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 193007 193112 193305 193410 193603 193708 193901 194006 194111 194304 194409 194602 194707 194812 195005 195110 195303 195408 195601 195706 195811 196004 196109 196302 196407 196512 196705 196810 197003 197108 197301 197406 197511 197704 197809 198002 198107 198212 198405 198510 198703 198808 199001 199106 199211 199404 199509 199702 199807 199912 200105 200210 200403 200508 200701 200806 Growth Value Monthly time series of market betas for the value and growth portfolios, defined as the top and bottom decile,respectively,of the book-to-market sorted portfolios for the sample 1926-07 to 2009-09.The betas are estimated using a rolling five year window. The monthly returns are from Ken French’s data base.
  • 43. The value premium: A behavioral view • As we just saw, a “risk story” faces challenges in addressing the value premium. • One of the biggest divide in finance academic circles: - Rational: The value premium is a compensation for risk; we just simply don’t observe the proper measure of risk (and the CAPM βs do not describe risk). - Behavioral: The value premium is a reflection of systematic underpricing of value stocks by investors. • We study next the behavioral story. 43
  • 44. The value premium: A behavioral view • Lakonishok, Shleifer and Vishny (JF, 1994) argue that the value premium arises because: - Value portfolios are comprised of stocks that have “underperformed” recently according to some metrics such as returns and earnings and - that investors extrapolate this past performance into the future and thus expect equally dismal results. - As a result they stay away from these distressed stocks which fall in price relative to fundamentals, such as a book, and thus the higher returns when performance surprises on the positive side. 44
  • 45. The value premium: A behavioral view • This logic is an example of the representative heuristic (Tversky and Kahneman, 1974), the tendency of individuals to identify the an uncertain event or a sample by the degree to which is similar to the parent population. • To quote Benjamin Graham: “[Strong past returns] created a natural satisfaction on Wall Street with such fine achievements, and a quite illogical and dangerous conviction that equally marvelous results could be expected for common stocks in the future. Few people seem to have been bothered by the thought that the very extent of the rise might indicate that it had been overdone.” The Intelligent Investor, Revised Ed 1984, pp. 67-69.45
  • 46. The value premium: A behavioral view • LSV offer some striking evidence of their thesis. • Take the same extreme value and growth portfolios that we constructed above and calculate some measure of past and future performance for these portfolios: - Earnings - Sales - Cash flows 46
  • 47. The value premium: A behavioral view Growth Value AEG(-5,0) .309 -.274 AEG(0,5) .050 .436 AEG(2,5) .070 .215 ACG(-5,0) .217 -.013 ACG(0,5) .127 .070 ACG(2,5) .086 .111 ASG(-5,0) .091 .030 ASG(0,5) .062 .020 ASG(2,5) .059 .023 47 AEG(i,j) is the geometric average growth rate of earnings for the portfolio from year i to year j. ACG(i,j) and ASG(i,j) are defined analagously for cash-flow and sales respectively. Source: J. Lakonishok,A. Shleifer and R.Vishny. Journal of Finance, Dec. 1994,TableV.
  • 48. The value premium: A behavioral view Growth Value AEG(-5,0) .309 -.274 AEG(0,5) .050 .436 AEG(2,5) .070 .215 ACG(-5,0) .217 -.013 ACG(0,5) .127 .070 ACG(2,5) .086 .111 ASG(-5,0) .091 .030 ASG(0,5) .062 .020 ASG(2,5) .059 .023 48 AEG(i,j) is the geometric average growth rate of earnings for the portfolio from year i to year j. ACG(i,j) and ASG(i,j) are defined analagously for cash-flow and sales respectively. Source: J. Lakonishok,A. Shleifer and R.Vishny. Journal of Finance, Dec. 1994,TableV.
  • 49. The value premium: A behavioral view • Thus it seems that past earnings growth fostered pessimism on these stocks which led to low prices and realized low returns • These stocks thus get classified as value. • After that, these same stocks surprise on the upside and thus the larger return after being classified as value. • This behavioral story fits with a particular psychological bias which is that of extrapolation 49
  • 50. Momentum • Value strategies are perhaps the most famous of sorts, but the strategy to uncover sources of average excess returns are always the same: - Sort stocks along your favorite characteristic. - Form portfolios, say decile portfolios, and track their returns over a particular period. - Reform the portfolios at a frequency of your choice (in the case of book-to-market sorted portfolios the standard rule is to resort portfolios after one year.) - Compute average excess returns across these portfolios and test whether whatever cross sectional dispersion in average returns can be explained by some measure of risk. 50
  • 51. Momentum • Momentum portfolios are those where the sort is driven by past returns: - Each month, say, we place stocks in portfolios according to their performance in the last year. - We then compute the returns of the so formed portfolios for the following month. • The idea behind momentum is easy enough to explain - Stocks that did well in the recent past are going to keep doing well, whereas those that did poorly are going to underperform. 51
  • 52. Momentum Low 2 3 4 5 6 7 8 9 High Avge. Returns (%) monthly 0.33 0.70 0.71 0.85 0.85 0.92 1.00 1.12 1.19 1.52 52 Monthly returns, in percentages, of ten portfolios sorted on realized returns over the previous year. Thus the returns in month t, corresponds to the portfolio formed at the end of month t-1, based on realized returns from t-1 to t-13. 1927-01 to 2009-09. Source: Ken French data base •Notice thus the portfolio of past winners outperforms the portfolio of past losers by more than a percentage point a month!
  • 53. Momentum • Momentum has deep implications for the value investor. - Value investors focus on “cheap and ugly” stocks. - If these have become such over the last year, it means that one can expect them to remain so and to keep underperforming in the short run. • Finally, notice that it is difficult to conceive of a risk based story that can account for the dispersion in average returns across momentum sorted portfolios as the frequency is much higher than that at which macroeconomic news occur. 53
  • 54. Momentum 54 -60 -40 -20 0 20 40 60 80 1927 1929 1931 1933 1935 1937 1939 1941 1943 1945 1947 1949 1951 1953 1955 1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 Mom Mkt-Rf Annual returns for the momentum factor and market excess return; 1927-2009; Source: Ken French data base. The construction of the Momentum Factor is due to Ken French. It is based on “six value-weight portfolios formed on size and prior (2-12) returns to construct Mom. The portfolios, which are formed monthly, are the intersections of 2 portfolios formed on size (market equity, ME) and 3 portfolios formed on prior (2-12) return. The monthly size breakpoint is the median NYSE market equity. The monthly prior (2-12) return breakpoints are the 30th and 70th NYSE percentiles. Mom is the average return on the two high prior return portfolios minus the average return on the two low prior return portfolios: Mom = 1/2 (Small High + Big High) - 1/2(Small Low + Big Low).
  • 55. Momentum • There are many possible explanations for momentum: - Conservatism bias: Investors underreact to new information, effectively underweighting new data, and this gives rise to momentum profits. - There is also evidence that, at least in the past, mutual fund managers tended to buy past winners and sell past losers creating the conditions for the momentum effect to arise. - There are explanations also based on self-attribution bias. For instance, negative news about stocks are attributed to “bad luck” rather than poor skills and thus mangers don’t liquidate their position delaying the full incorporations of news in prices. 55
  • 56. Long term reversals • Momentum is the observation that stocks that have done well in the recent past (last year) do well in the near future (generally, 3 months to a year) whereas stocks that have done poorly keep underperforming. • Momentum can lead to overvaluation but if this is the case we should observe some long term reversal. Is this the case? - The answer is yes: When we sort stocks based on the performance between one and five years there is substantial evidence that bad performers tend to perform better whereas the opposite is true for winners. 56
  • 57. Long term reversals • To check this we now sort stocks on a monthly basis based on their performance between one and five year into ten portfolios. Then we compute their monthly returns: 57 Low 2 3 4 5 6 7 8 9 High Avge. Monthly returns (%) 1.47 1.26 1.24 1.04 1.10 0.99 1.02 1.02 0.87 0.87 Average monthly returns, in percentages, of ten portfolios sorted at the end of month t-1 based on returns between months t-13 and month t-60. 1931-01 to 2009-09. The stocks are all stocks In NYSE, Nasdaq and AMEX. Source: Ken French data base
  • 58. Long term reversals 58 -50 -30 -10 10 30 50 70 90 1931 1933 1935 1937 1939 1941 1943 1945 1947 1949 1951 1953 1955 1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 Long Term Reversal Factor Mkt-Rf Annual returns of the long term reversal factor versus the market excess return over the one year treasury bill rate. 1931 to 2008. Source: Ken French data base, which should be consulted for the construction of the factor
  • 59. THE MARKET 59
  • 60. Some thoughts on the market • Value investors are reluctant to give advice regarding the timing of Mr. Market, being aware of its intemperate, capricious and childish ways! • Still, one should not make the mistake of ignoring the vagaries of the market. • It is important to try to make sense of its gyrations. • Next we try to cover briefly where we are and some general lessons for the value investor regarding the market outlook. 60
  • 61. Some thoughts on the market 61 0 200 400 600 800 1000 1200 1400 1600 1800 2000 1870 1890 1910 1930 1950 1970 1990 2010 RealS&P500StockPriceIndex Year Price Real S&P Stock Price Index and Composite Earnings. Monthly 1871-01 to 2010-01 (Jan. 13) Source: Robert Shiller
  • 62. Some thoughts on the market 62 0 50 100 150 200 250 300 350 400 450 0 200 400 600 800 1000 1200 1400 1600 1800 2000 1870 1890 1910 1930 1950 1970 1990 2010 RealS&PCompositeEarnings RealS&P500StockPriceIndex Year Price Earnings Real S&P Stock Price Index and Composite Earnings. Monthly 1871-01 to 2010-01 (Jan. 13) Source: Robert Shiller
  • 63. Some thoughts on the market 63 0 5 10 15 20 25 30 35 40 45 1881.01 1883.05 1885.09 1888.01 1890.05 1892.09 1895.01 1897.05 1899.09 1902.01 1904.05 1906.09 1909.01 1911.05 1913.09 1916.01 1918.05 1920.09 1923.01 1925.05 1927.09 1930.01 1932.05 1934.09 1937.01 1939.05 1941.09 1944.01 1946.05 1948.09 1951.01 1953.05 1955.09 1958.01 1960.05 1962.09 1965.01 1967.05 1969.09 1972.01 1974.05 1976.09 1979.01 1981.05 1983.09 1986.01 1988.05 1990.09 1993.01 1995.05 1997.09 2000.01 2002.05 2004.09 2007.01 2009.05 Price to (10 year smoothed) earnings ratio of S&P Index – 1881-01 to 2010-01. Source: Robert Shiller
  • 64. Some thoughts on the market • More recently, the market has rallied dramatically since its low in March 2009. • This has been very painful for many investors (value or not) who have remained skeptical about the sources and sustainability of the recovery. - In particular, the recovery seems to be fueled by a world wide expansion of the monetary base. • Before we turn to this rally let’s consider one previous rally in times that were economically challenging as well. 64
  • 65. Some thoughts on the market 65 • S&P composite 12/28-04/30 • One dollar invested in the index at the peak, in Sept. 1929, becomes only 71cents in November 1929 • One dollar (re)invested at the (local) bottom of November 1929 becomes $1.52 in April 1930. • The plot is the price and one has to account for dividends, which are also reinvested. • What happened afterwards? 20.00 22.00 24.00 26.00 28.00 30.00 32.00 1928.12 1929.01 1929.02 1929.03 1929.04 1929.05 1929.06 1929.07 1929.08 1929.09 1929.1 1929.11 1929.12 1930.01 1930.02 1930.03 1930.04 S&P composite price. Monthly. 12/28-04/30. Source: Robert Shiller -30% +50%
  • 66. Some thoughts on the market 66 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00 1929.01 1929.07 1930.01 1930.07 1931.01 1931.07 1932.01 1932.07 1933.01 1933.07 1934.01 1934.07 1935.01 1935.07 1936.01 1936.07 1937.01 1937.07 1938.01 1938.07 1939.01 1939.07 1940.01 1940.07 1941.01 1941.07 1942.01 1942.07 1943.01 1943.07 1944.01 1944.07 1945.01 1945.07 1946.01 1946.07 1947.01 1947.07 1948.01 1948.07 1949.01 1949.07 1950.01 1950.07 1951.01 1951.07 1952.01 1952.07 1953.01 1953.07 1954.01 1954.07 1955.01 1955.07 S&P composite price. Monthly. 1/29-12/55. Source: Robert Shiller
  • 67. Some thoughts on the market 67 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00 1929.01 1929.07 1930.01 1930.07 1931.01 1931.07 1932.01 1932.07 1933.01 1933.07 1934.01 1934.07 1935.01 1935.07 1936.01 1936.07 1937.01 1937.07 1938.01 1938.07 1939.01 1939.07 1940.01 1940.07 1941.01 1941.07 1942.01 1942.07 1943.01 1943.07 1944.01 1944.07 1945.01 1945.07 1946.01 1946.07 1947.01 1947.07 1948.01 1948.07 1949.01 1949.07 1950.01 1950.07 1951.01 1951.07 1952.01 1952.07 1953.01 1953.07 1954.01 1954.07 1955.01 1955.07 S&P composite price. Monthly. 1/29-12/55. Source: Robert Shiller This is the episode in the previous plot
  • 68. Some thoughts on the market 68 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00 1929.01 1929.07 1930.01 1930.07 1931.01 1931.07 1932.01 1932.07 1933.01 1933.07 1934.01 1934.07 1935.01 1935.07 1936.01 1936.07 1937.01 1937.07 1938.01 1938.07 1939.01 1939.07 1940.01 1940.07 1941.01 1941.07 1942.01 1942.07 1943.01 1943.07 1944.01 1944.07 1945.01 1945.07 1946.01 1946.07 1947.01 1947.07 1948.01 1948.07 1949.01 1949.07 1950.01 1950.07 1951.01 1951.07 1952.01 1952.07 1953.01 1953.07 1954.01 1954.07 1955.01 1955.07 S&P composite price. Monthly. 1/29-12/55. Source: Robert Shiller August 1929: 31.30 September 1954: 31.45
  • 69. Some thoughts on the market • What fueled the impressive rally between November 1929 and April 1930? • Nothing: Economic news were dismal and in fact the economy was in for a massive downturn. • No wonder the market resumed its downfall afterwards. • It took 25 years to cross the level of August 1929 again. 69 -15.0 -10.0 -5.0 0.0 5.0 10.0 15.0 20.0 1930-01-01 1931-01-01 1932-01-01 1933-01-01 1934-01-01 1935-01-01 1936-01-01 1937-01-01 1938-01-01 1939-01-01 1940-01-01 1941-01-01 1942-01-01 1943-01-01 1944-01-01 1945-01-01 Real GNP growth –percent change from a year ago– 1930 to 1945. Source: St. Louis Fed
  • 70. Some thoughts on the market 70 700 800 900 1000 1100 1200 1300 1400 1500 1600 2007.01 2007.03 2007.05 2007.07 2007.09 2007.11 2008.01 2008.03 2008.05 2008.07 2008.09 2008.11 2009.01 2009.03 2009.05 2009.07 2009.09 2009.11 2010.01 20.00 22.00 24.00 26.00 28.00 30.00 32.00 1928.12 1929.01 1929.02 1929.03 1929.04 1929.05 1929.06 1929.07 1929.08 1929.09 1929.1 1929.11 1929.12 1930.01 1930.02 1930.03 1930.04 S&P 500 index during two big market corrections: 2007-01 to 2010-01 & 1928-12 to 1930-04. Source: Robert Shiller
  • 71. Some thoughts on the market 71 700 800 900 1000 1100 1200 1300 1400 1500 1600 2007.01 2007.03 2007.05 2007.07 2007.09 2007.11 2008.01 2008.03 2008.05 2008.07 2008.09 2008.11 2009.01 2009.03 2009.05 2009.07 2009.09 2009.11 2010.01 • The market has rallied dramatically since the trough in March 2009. What is different? - Some of it real: No Great Depression – II - Main difference: Policy response - Fiscal - Monetary: • Low rates and promises of low rates • Money base expansion
  • 72. Some thoughts on the market 72 0 200 400 600 800 1000 1200 1400 1600 1800 0 200000 400000 600000 800000 1000000 1200000 1400000 1600000 1800000 2007-01-03 2007-01-24 2007-02-14 2007-03-07 2007-03-28 2007-04-18 2007-05-09 2007-05-30 2007-06-20 2007-07-11 2007-08-01 2007-08-22 2007-09-12 2007-10-03 2007-10-24 2007-11-14 2007-12-05 2007-12-26 2008-01-16 2008-02-06 2008-02-27 2008-03-19 2008-04-09 2008-04-30 2008-05-21 2008-06-11 2008-07-02 2008-07-23 2008-08-13 2008-09-03 2008-09-24 2008-10-15 2008-11-05 2008-11-26 2008-12-17 2009-01-07 2009-01-28 2009-02-18 2009-03-11 2009-04-01 2009-04-22 2009-05-13 2009-06-03 2009-06-24 2009-07-15 2009-08-05 2009-08-26 2009-09-16 Securities held outright S&P500 Securities (Treasuries, MBS, and Agency Debt) held by the Federal Reserve (in millions) vs. the S&P500; weekly; 2007-01-03 to 2009-09-16
  • 73. Some thoughts on the market • Whether the recovery justifies the prices is difficult to say but there are reasons to question the recent rally. • In the words of Jeremy Grantham: - “Riding a bubble is a guilty pleasure totally denied to value managers who typically pay a high price to the God of Investment Discipline …” - “Risk taking has come roaring back. Value, it must be admitted, is seldom a powerful force in the short term. The Fed’s weapons of low rates, plenty of money and the promise of future help if necessary seems stronger than value over a few quarters. And the forces of herding and momentum are also helping to push prices up, with the market apparently quite unrepentant of recent crimes and willing to be silly again. ” Jeremy Grantham, Just Deserts and Markets Being Silly Again, GMO Quarterly Letter, October 2009 73