Presentation Transcript

1. Equity Premium

   Yun Xu 11/14/2013

2. The Magnitude and Concept of the Equity Premium in 150 TextbooksPablo Fernandez

   Predicting the Equity Premium with Dividend Ratio AmitGoyal• Ivo Welch Pricewaterhouse Coopers Professor of Corporate Finance IESE Business School July 16, 2011 Goizueta Business School, Emory University • Yale School of Management, Yale University Management Science, Vol. 49, No. 5 (May, 2003), pp. 639-654 May 2003
3. Contents
4. Part I Introduction of Equity Premium
5. Four Concepts of Equity Premium The equity premium is one of the most important parameters in finance. The term equity premium is used to designate four different concepts: Historical equity premium (HEP): historical differential return of the stock market over treasuries. Expected equity premium (EEP): expected differential return of the stock market over treasuries. Required equity premium (REP): incremental return of a diversified portfolio (the market) over the risk-free rate required by an investor. It is used for calculating the required return to equity. Implied equity premium (IEP): the required equity premium that arises from assuming that the market price is correct.
6. Assumptions and recommendations of the 150 textbooks
7. Assumptions and recommendations of the 129 textbooks that assume REP=EEP
8. Review of the recommendations Figure 1 contains the evolution of the Required Equity Premium (REP) used or recommended by 150 books with average is 6.5%. Figure 2 shows that the 5-year moving average has declined from 8.4% in 1990 to 5.7% in 2008 and 2009.
9. Comments on the four concepts of the equity premium The HEP: easy to calculate and is equal for all investors, provided they use the same time frame, the same market index, the same risk-free instrument and the same average (arithmetic or geometric). Different stock index chosen will make HEP different:
10. Comments on the four concepts of the equity premium(cont’d) The EEP: Some authors try to find the Expected Equity Premium by conducting surveysbecause investors and professors do not share “homogeneous expectations,” do not hold the same portfolio of risky assets and may have different assessments of the expected equity premium.
11. Comments on the four concepts of the equity premium(cont’d) The REP: is the answer to such a question: what incremental return do investors require for investing in a diversified portfolio of shares over the risk-free rate. Different investors and companies use different REPs. The IEP: is the implicit REP used in the valuation of a stock that matches the current market value. The most widely used model to calculate the IEP is the dividend discount model. P0 = d1 / (Ke - g), which implies: IEP = d1/P0 + g - RF Where: P0: the current price per share Ke: the required rate of return D1: the dividend (equity cash flow) per share expected to be received at time 1 d1: the expected long term growth rate in dividends per share The estimates of the IEP depend on the particular assumption made for the expected growth. Even if market prices are correct for all investors, there is not an IEP common for all investors: there are many pairs (IEP, g) that accomplish equation.
12. Author’s conclusion & discussion The recommendations regarding the equity premium of 150 finance and valuation textbooks published between 1979 and 2009 range from 3% to 10%. Several books use different equity premia in different pages and most books do not distinguish among the four different concepts that the phrase equity premium designates: Historical equity premium, Expected equity premium, Required equity premium and Implied equity premium. There is not a generally accepted equity premium point estimate and that there is not either a common method to estimate it, even for the HEP. Which equity premium is used to value companies and investment projects by the author? for Europe, REPs between 3.8% and 4.3% for the U.S., given the yields of the T-Bonds, an additional 4% compensates the additional risk of a diversified portfolio.
13. Part II overview of the equity premium prediction
14. Abstract The use of aggregate dividend ratios to predict equity premium has a long tradition in finance. Dividend ratios: Dividend yield: D(t)/P(t-1) & Dividend-price ratio: D(t)/P(t) A typical regression specification: Where: D(t) = dividends paid by all stocks at the end of year t P(t) = total stock market capitalization at the end of year t Rm(t) = return on the stock market Rf(t) = return on a short-term risk –free treasury bill Do dividend ratio have the predictive ability of equity premium? The paper suggests a simple, recursive residuals (out-of-sample) graphical approach to evaluate the predictive power of popular equity premium and stock market time-series forecasting regressions.
15. Data(value-weighted CRSP index) Rm(t)is the log of the total return on the value-weighted stock market from year t-1 to t. EQP(t) subtracts the equivalent log return on a three-month treasury bill. DP(t)is the dividend-price ratio, i.e., the log of aggregate dividends D(t) divided by the aggregate stock market value P(t). DY(t),the dividend-yield ratio, divides by P(t- 1) instead. ΔD(t)is the change in log dividends from year t - 1 to t. All variables are in percentages. JqBris the Jarque-Bera test for normality. The critical level to reject normality is 5 .99 at the 95% level, 9.21 at the 99% level. ADF is the Augmented Dickey-Fuller test for the absence of a unit root. An A DF value of -3.5 rejects the presence of a unit root at the 1% level( -2.9% at the 5% level;-2 .6% at the 10% level).
16. Part III IN-SAMPLE FIT
17. In Sample Univariate Regression Explanation. All series are described in Table 1. This table presents the results of the following regression: EQP(t) =a + βx(t- 1) + ε (t). The first row of each regression is the coefficient, the second line it’s OLS t-statistic, and the third line it’s Newey - West adjusted t-statistic. Data frequency is annual; s.e.is the standard error of the regression residuals, and N is the number of observations. The sample period refers to the dependent variable, EQP(t) Interpretation: Panel A confirms the findings in Fama and French(1988, Table 3). Prior to the 1990s, the dividend yield (DY(t)) had significant forecasting power, the dividend-price ratio (DP(t)) had acceptable forecasting power. However, when the sample is extended into 2002, the in-sample predictive ability declines. The dividend-price ratio misses conventional statistical significance levels, while the dividend-yield ratio retains good statistical significance
18. Fama and French (1988)
19. Part IV Out-of-sample forecast & alternative specification
20. Out-of-Sample Forecast Even a sophisticated trader could not use the regression in Table 2 to predict equity premium. What can be used is only the prevailing data. Dividend-ratio coefficients show remarkably different patterns. The beta using dividend-price ratios has high s.e., but low variability. It crosses Zero in our sample. The beta using dividend yields is always positive, economically larger, but also continuously declining.
21. Other Illustrations of the changing dividend model coefficients By estimation subsamples By estimation only with prevailing data dividend yield underperformed the prevailing mean. dividend-price ratio sometimes outperformed the prevailing mean out-of-sample but statistically and economically insignificant and non-stability. Estimated coefficients vary widely across subperiods, casting some doubt on the stability on the specified model
22. Main Contribution—simple graphical diagnostic
23. Interpretation: Plotting the cumulative sum-squared error form the unconditional model minus the cumulative sum-squared error from the dividend-ratio model. A positive value indicates that the dividend ratio has outperformed the unconditional model. A positive slope indicates that the dividend ratio had lower forecasting error than the unconditional moving average equity premium in a given year Relative to the simple prevailing equity premium mean, the dividend yield shows poor predictive performance out-of-sample in the 1960s. Both the dividend yield and the dividend-price ratio show poor performance in the 1990s. Prior to the 1990s, both dividend ratios had only two very good years, 1973 and 1974.
24. Alternative Specifications Numerous variations: Reinvest the dividends, instead of summing them; Change in dividend ratio, because the dividend ratio is close to stationary; Use simple returns and yields, instead of log returns and yields; Predict on different horizons(monthly, quarterly, multiyearly); Reconcile definitions to match exactly those of Fama and French(1988) including using only NYSE firms, predicting stock returns rather than premia, and 30-year estimation window; Use different “fixed number of years” estimation windows;
25. Alternative Specifications (Cont’d) Use regression prediction standard error to normalize forecast errors; Try convex combination of the dividend-yield model prediction and the unconditional prediction; Forecast with Stambaugh(1999) correction for high serial correlation in the dividend yield; Use Earnings-price, earnings-payout ratios(Lamont 1998) or more complex measures based on analysts’ forecast(Lee et al. 1999); Try a similar experiment for forecasts of the equity premium using the risk-free rate. In sum, none of these variations impact the conclusion that out-of-sample performance has always been poor.
26. Part V Further research on dividend ratio
27. Instrumenting the changing dividend-yield process If theory is correct, changes in the dividend-yield autocorrelation and in the dividend yield’s ability to predict changes in dividend growth could themselves imply changes in the dividend-yield ability to predict the equity premium Rm(t) have low correlation (recently almost no correlation with DP(T-1)). (t) used to be strongly negative correlated with DP(t-1) but it is i.i.d. today. DP(t) had only mild autocorrelation in post-WW2 period, it is a random walk today. Reason: prices continued to be random walk with high variance, while dividends have remain stationary and low variance.
28. Campbell-Shiller instrumented dividend-ratio regressions Assume {DP(t)} follows a stationary process with mean = Then using Taylor expansion we can get Take covariance with DP(t) and divide by variance of DP(t) of equation (4) Define , k = -log)log(1/-1) The forecasting ability does not improve using Campbell and Shiller (1988) identities.
29. The source of poor predictive ability Puzzle: to WHAT dividend-price ratio really predicts? Rearrange the terms in Equation (4) and recurse forward, [Rm(t+1-i) - (t+1+i)] + constant It seems that dividend-price ratio must predict the next-period stock return, the next-period dividend growth rate, the next period dividend-price ratio. However, Table 6 shows: DP(t) is primarily forecasting itself over horizons up to about 5 years. It is a partial forecaster of itself over 5 to 10-year horizons, and does not forecast itself over 20-year horizons. DP(t) is primarily forecasting future market returns(and some dividend growth) over horizons greater than 10 years. It does not forecast market returns or dividend growths over horizons less than 5 years.
30. Decomposition of Dividend-Yield Components over different horizons
31. Part VI conclusions
32. Conclusions Conclusions & Suggestions Explanations The primary source of poor predictive ability is parameter instability. The dividend yield has failed to forecast one-year-ahead returns or dividend-growth rates, because it primarily forecast its own change. Instrumenting the model to account for the time-varying properties of the dividend yield and dividend growth process does not aid the dividend ratio in predicting the stock market levels. A figure that graphs comparative sum-squared model residuals out-of-sample(like Figure 3) can act as a powerful diagnostic for equity premium and stock price prediction. For simple dividend-yield models prediction equity premium, the diagnostic suggests that good in-sample performance is no guarantee of out-of-sample performance. The diagnostic further suggests that any remaining explanatory predictive ability of the dividend ratios in the post-war period prior to the 1990s was due to two years only, 1973 and 1974.
33. Part VII summary
34. Summary Good points Questions The first paper gives us a general range for the equity premium but does not show the reason for why professors use this number of equity premium. The second paper tells us the weak power of the dividend ratios to predict the equity premium with out-of-sample data or in a longer horizon but does not provide more thoughts on which ratio might be useful to predict the equity premium. Fernandez documents the range of advice on equity premium in the textbooks, which provides a reference that people can consider to apply in the practical investment decision or valuation. Goyal and Welch looked at statistical techniques for predicting the risk premium on the market, which reminds us that a market trader who just assumed that the equity premium was “like it has been” would typically have outperformed a trader who employed dividend-ratio forecasting regressions. The alternative specification section in the second paper especially gives a broader idea on researching or verifying models which could also be useful to practice.
35. Recommendations A Comprehensive Look at The Empirical Performance of Equity Premium PredictionAmitGoyal• Ivo Welch This paper comprehensively reexamine the performance of variables that have been suggested by the academic literature to be good predictors of the equity premium Numerous variables: Dividend ratio, Earnings Price Ratio, Dividend payout ratio, Stock variance, Cross-sectional premium, Book-to-market ratio, Investment-capital ratio, The consumption, wealth and income ratio, Inflation rates, aggregate net or equity issuing activity and various interest rates and spreads. Conclusion:NO models predict the equity premium well out-of-sample.(except 1973 and 1974)
36. Thank you!