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Consumption-Based Asset Pricing After 25 Years Douglas T. Breeden*

Consumption-Based Asset Pricing After 25 Years Douglas T. Breeden*. *Dean and William W. Priest Professor of Finance, Duke University, Fuqua School of Business Reference notes, tables and graphs for June 20, 2005 Western Finance Association Talk. Perspective and Goal of the Paper.

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Consumption-Based Asset Pricing After 25 Years Douglas T. Breeden*

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  1. Consumption-Based Asset Pricing After 25 YearsDouglas T. Breeden* *Dean and William W. Priest Professor of Finance, Duke University, Fuqua School of Business Reference notes, tables and graphs for June 20, 2005 Western Finance Association Talk

  2. Perspective and Goal of the Paper • Rip Van Winkle (Austin Powers?) academic career: Intertemporal consumption, portfolio theory and asset pricing research 1976-1989. Left Duke 1992 to build Smith Breeden, did applied research on mortgages and corporate bonds. Returned to academia in 2000. Dean at Duke 2001-present, with usual IQ drop of Dean. • Paper will be a follow-up look at the numbers for some major results of consumption-based asset pricing that I began working on 25 years ago. There are many areas for future research that we’ll see.

  3. Preceding Work on Intertemporal Asset Pricing and the Term Structure • Markowitz (1952), Sharpe (1964), Lintner (1965) and Mossin (1966) developed diversification and the market-based CAPM. • Samuelson (1969), Merton (1969, 1971, 1973), Hakannson (1970), Fama (1970), Pye (1972) and Long (1975) pioneered intertemporal investments. • Hirshleifer (1970 book), Cox, Ingersoll and Ross (1985) and Garman (1976) on term structure.

  4. First Decade of Selected Research on Consumption-Based Asset Pricing • Rubinstein (1976 BJEMS), Breeden-Litzenberger (1978 JB), Lucas (1978 Ec), Breeden (1979 JFE) • Hall (1978), Breeden (1980), Stulz (1981), Grossman-Shiller (1982) , Marsh-Rosenfeld (1982), Mankiw-Shapiro (1986), Mehra-Prescott (1985), Wheatley (1986), Hansen-Singleton (1982, 1983), Ferson (1983), Breeden (1984),Gibbons-Ferson. • Chen, Roll and Ross (1986), Grossman, Melino, Shiller (1987), Campbell-Shiller (1988), Breeden, Gibbons and Litzenberger(1989) • Term Structure: Garman (1976), Cox, Ingersoll, Ross (1985), Breeden (1986), Harvey (1988, 1989, 1991), Dunn-Singleton (1986), Sundaresan (1989)

  5. Second Decade of Selected Research on Consumption-Based Asset Pricing • Constantinides (1990), Abel (1990), Epstein-Zin(1991), Hansen-Jagannathan (1992), Cochrane(1991,1994,1996), Campbell (1991) • Campbell-Shiller(1990), Shanken (1990), Fama (1991), Kandel-Stambaugh(1991),Ferson-Constantinides (1991), Mankiw-Zeldes (1991), Fama-French (1992), Brennan-Schwartz-Lagnado(1997) • Heaton (1995), Elton-Gruber-Blake (1995), He-Modest (1995), Constantinides-Duffie (1996), Jagannathan-Wang (1996), Campbell-Cochrane (1999), Campbell-Viceira (1999), Ferson-Harvey(1999)

  6. Third Decade of Selected Research on Consumption-Based Asset Pricing • Campbell (2000), Heaton-Lucas (2000), Lettau-Ludwigson (2001a,b), Santos-Veronesi (2001),Brav-Constantinides-Geczy (2002), Wachter (2002), Barberis-Huang-Santos (2003) • Verdelhan (2003), Lustig-Verdelhan(2004), Piazzesi-Schneider-Tuzel (2003),Bansal-Yaron(2005), Bansal-Dittmar,Lundbad(2005),Bansal-Dittmar-Kiku (2004) • Jagannathan and Wang (2004), Parker-Julliard (2005), Campbell-Vuolteenaho (2004),Hansen-Heaton-Li(2005) • In total, 179 articles with “consumption, asset pricing” in the abstract, far more than mentioned here. Apologies.

  7. Consumption Based Asset PricingOutline of Paper 1. Consumption and marginal utility. 2. Consumption risks of corporate profits & cash flows. Capital budgeting. 3. Consumption betas vs. market betas for industries. 4. Term structure slope and consumption growth. 5. Risk and return and the “Maximum Correlation Portfolio” for consumption. 6. Consumption deviations from wealth and the investment and income opportunity sets. 7. Volatility of family consumption and the “Equity Premium Puzzle.”

  8. Consumption and Marginal Utility

  9. Consumption and Marginal Utility • Some likely statistical indicators of times when the marginal utility of $1 is quite high, are the following: 1. Unemployment rate is increasing. 2. Job growth is less rapid than normal. 3. Businesses are failing more often, risky bonds’ yield spreads are high. 4. Banks are charging off more loans.

  10. United States Unemployment Rate EOQ, 1960-Q4 2004

  11. U.S. Real Consumption Growth Last Four Quarters Percent, 1960-2004 Q4

  12. Unemployment Changes (6mo) and Consumption Growth 1959-2004

  13. Unemployment Changes (6mo) and Real S&P 500 Returns: 1959-2004

  14. Unemployment Rate vs. Consumption and Stock Prices 1959-2004 (6 month changes)

  15. Employment Growth vs. Consumption and Stock Prices 1959-2004 (6 month changes)

  16. Conclusion on Marginal Utility • Consumption’s percentage changes likely represent more correctly changes in the marginal utility of $1 to individuals than do changes in real stock prices. • This is no failing of stock prices, for as the present value of future dividends, they should reflect future profit growth and changing risks and risk aversion.

  17. II. Consumption and Market Risks of Corporate Cash Flows

  18. Remember the Discounted Cash Flow Approach to Valuation? • We teach our students to value an asset by discounting expected cash flows at their proper risk-adjusted discount rates. • Breeden-Litzenberger (Oct 1978, J. Business) derived risk-adjusted discount rates in a multiperiod economy with power utility, jointly lognormal cash flows. Correct discount rates were derived as the Consumption-based CAPM.

  19. Consumption and Market Risks: Earnings, Cash Flows vs. Stock Prices • Major problem applying CCAPM to stock prices is imprecision of consumption beta estimates vs. very precise market betas. • Breeden paper presented at the French Finance Ass’n at U. Paris Dauphine on “Capital Budgeting with Consumption” June 1989 showed opposite results for earnings risks. Updated slides follow. Consumption risks are more precisely estimated for earnings than are market risks, making CCAPM use natural for capital budgeting. Just in textbooks, e.g., Elton-Gruber.

  20. NIPA U.S Real BT Earnings Growth vs Total Consumption:Annual Data: 1930-2003 (Excl. 1939-1947)

  21. NIPA U.S Real BT Earnings Growth vs NDS Consumption:Annual Data: 1930-2003 (Excl. 1939-1947)

  22. NIPA U.S Real BT Earnings Growth vs S&P 500 Real Return:Annual Data: 1930-2003 (Excl. 1939-1947)

  23. NIPA U.S Real BT Earnings Growth vs Total Consumption: Postwar Annual Data: 1948-2003

  24. NIPA U.S Real BT Earnings Growth vs S&P 500 Real Return:Postwar Annual Data: 1948-2003

  25. NIPA Profits and Cash Flows: Average RSQ vs. SP500 and Consumption

  26. Conclusion on Cash Flow Risks • As we teach our students and in practice, it is both more correct and more intuitive to measure cash flow risks in terms of sensitivity to fluctuations in aggregate real consumption, rather than in terms of their relationship to stock market fluctuations. • Of course, if P/E multiples were constant, stock prices would be proportionate to earnings, and 1% higher earnings would give 1% higher stock prices. However, in reality, stocks’ price/earnings multiples fluctuate also with interest rates, economic risk and with growth prospects.

  27. III. Relative Consumption Betas For Industries Are Different From Their Market Betas

  28. Market Betas vs. Consumption Betas: Estimation Procedure • Stock market betas are estimated from industry returns data from Professor Kenneth French’s website, using quarterly data from 1948-2004. • Consumption betas are from NIPA “coarse industries” quarterly profit data, using 2-quarter percentage changes in real profits. Actual calculation is of changes in real profits/employee compensation vs. real consumption growth, divided by average profits/employee compensation.

  29. Risks by Industry 1948-2004: Part 1Market Betas vs. Consumption Betas

  30. Risks By Industry 1948-2004: Part 2Market Betas vs. Consumption Betas

  31. Market Betas vs. Relative Consumption Betas for Selected IndustriesSemiannual data 1948-2004. Stock returns on stocks, Profits on Consumption.

  32. IV. The Term Structure of Interest Rates as a Predictor of Economic Growth

  33. Theory: Slope of the Term Structure Optimally Related to Changes in Real Economic Growth • Breeden’s (1986, JFE) article on “Consumption, Production, Inflation and Interest Rates: A Synthesis”, generalized Garman (1976), Rubinstein (1976), Fisher (1907) and Hirshleifer (1970) and derived and illustrated optimal relations of the term structure with expected consumption growth and its volatility. • Higher expected consumption growth is consistent with higher real rates. Higher volatility is consistent with lower real rates. With forecasted declines in expected growth, the term structure should have a negative slope. A positive slope should presage an expected strengthening in economic growth.

  34. Tests and Uses of the Term Structure Slope to Forecast Changes in Economic Growth • Harvey (JFE 1988, 1989,1991,1993) tested Breeden’s equilibrium model and found it to be quite powerful, forecasting economic growth better than most professional economists and working in many countries. • Reflecting this research, in 1996, the slope of the term structure was added as a variable in the Index for Leading Economic Indicators. • Dotsey (1998) of the Federal Reserve Bank of Richmond found a negative term structure slope gave 18 true quarterly signals and only 2 false signals of recession in quarterly growth during the 1955-1995 period.

  35. US Yield Curve Inverts Before Last Six US Recessions(5-year US Treasury bond - 3-month US Treasury bill)Source: Campbell R. Harvey, Professor, Duke University Annual GDP growth or Yield Curve % Real annual GDP growth Yield curve slope Recession Correct Recession Correct Yield curve accurate in recent forecast Recession Correct 2 Recessions Correct Data though 1/12/03

  36. Slope of the Term Structure Predicts Real Consumption Growth 1959-2004

  37. Forecasts of Growth from Term SpreadQuarterly Data, 1953 : 1978

  38. Forecasts of Growth from Term SpreadQuarterly Data, 1979 : 2004

  39. Global Term Structure Slopes: 10 Year-3 Month Ends of Years 1989-2003

  40. V. Consumption Risk and Returns and the Maximum Correlation Portfolio

  41. Maximum Correlation Portfolio ElementsS&P 500, Baa-Treasury Bonds, Term Spread • Breeden, Gibbons and Litzenberger (JF, 1989) proved that the CCAPM also holds with regard to betas measured against the maximum correlation portfolio for consumption. • Three broad traded markets are for (1) stocks, (2) Government bonds and (3) corporate bonds. Consumption relates to each of these through effects of wealth, the term structure, and relation of credit risk to the economic cycle, respectively.

  42. Maximum Correlation PortfolioSemiannual Data (Dec-Jun) 1960-2004

  43. “Consumption Risk and the Cross-Section of Expected Returns”,Parker-Julliard (JPE, 2005) Consumption betas measured by contemporaneous covariances of assets’ returns and consumption growth, fail to explain the dispersion in risk premiums across assets. Parker-Julliard measure ultimate consumption risk as covariation of return with current and future consumption growth. Ultimate consumption betas, therefore, measure the exposure of asset returns to long-run risks in consumption.

  44. Consumption Risk and Expected ReturnsParker-Julliard (JPE, 2005) continued Parker-Julliard argue that ultimate consumption risk measures are much more robust to measurement errors in consumption, as well as slow and costly adjustments of consumption to returns. Using post-war quarterly data on 25 Fama-French portfolios sorted by Book Equity/Market Equity and Size, they show ultimate consumption risk measures are able to explain from 44% to 73% of the variation in expected returns.

  45. VI. Consumption Deviations from Wealth as a Predictor of Income and Investment Opportunities

  46. Consumption Deviations from Wealth Predict Income and Investment Opportunities • Breeden (1984, JET) showed with relative risk aversion >1, investors’ consumption levels are positively related to income and investment opportunities. (If RRA<1, reverse hedging occurs.) • In June 1989, at the French Finance Association in Paris and in 1991 at Harvard, Breeden paper on “Capital Budgeting with Consumption”, argued that as consumption optimally is a function of wealth, income and investment opportunities, consumption fluctuations orthogonalized for wealth effects should be indicators of the income and investment opportunity set. Test results presented then are updated as follows:

  47. Consumption Growth Predicted by Stock ReturnsQuarterly Data, 1949 – 2003

  48. Consumption Growth Deviations and the Income and Investment Opportunity Set • The lagged values of the residuals from the above regressions are examined for predictive ability with regard to income, wages and corporate profits. • Specifically, we regress the growth rate of each variable on its own lag and the lagged consumption residuals.

  49. Consumption Deviations Predict Real Personal Income Growth: 1989 Results • Results in 1989 Breeden paper (Quarterly 1950-1988): • Personal Income Growth (t)= = .0054+ .36 PI(t-1) + .31(PCETotal Residual) (t=4.84) (t=3.44) RSQ=.27 = .0054 +.35 PI(t-1) + .47 (PCE NDS Residual) (t=4.67) (t=3.52) RSQ=.27

  50. Consumption Deviations Predict Real Personal Income Growth: 2004 Results • Updating tests quarterly from 1949-2003: • Personal Income Growth (t)= = -.125 PI(t-1) + .33(PCETotal Residual) (t=-1.38) (t=3.89) Adj RSQ=.06 = -.133 PI(t-1) + .56 (PCE NDS Residual) (t=-1.52) (t=4.90) Adj RSQ=.05

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