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The Predictive Ability of the Bond-Stock Earnings Yield Differential Model

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The Predictive Ability of the Bond-Stock Earnings Yield Differential Model The Predictive Ability of the Bond-Stock Earnings Yield Differential Model KLAUS BERGE,GIORGIO CONSIGLI, AND WILLIAM T. ZIEMBA FORMAT ANY IN KLAUS BERGE he Federal Reserve (Fed) model prices and stock indices has been studied by is a financial controller provides a framework for discussing Campbell [1987, 1990, 1993]; Campbell and for Allianz SE in Munich, stock market over- and undervalu- Shiller [1988]; Campbell and Yogo [2006]; Germany. [email protected] ation. It was introduced by market Fama and French [1988a, 1989]; Goetzmann Tpractitioners after Alan Greenspan’s speech on and Ibbotson [2006]; Jacobs and Levy [1988]; GIORGIO CONSIGLI the market’s irrational exuberance in ARTICLELakonishok, Schleifer, and Vishny [1994]; Polk, is an associate professor in November 1996 as an attempt to understand Thompson, and Vuolteenaho [2006], and the Department of Mathe- and predict variations in the equity risk pre- Ziemba and Schwartz [1991, 2000]. matics, Statistics, and Com- mium (ERP). The model relates the yield on The Fed model has been successful in puter Science at the THIS University of Bergamo stocks (measured by the ratio of earnings to predicting market turns, but in spite of its in Bergamo, Italy. stock prices) to the yield on nominal Treasury empirical success and simplicity, the model has [email protected] bonds. The theory behind the Fed model is been criticized. First, it does not consider the that an optimal asset allocation between stocks role played by time-varying risk premiums in WILLIAM T. Z IEMBA and bonds is related to their relative yields and the portfolio selection process, yet it does con- is Alumni Professor of Financial Modeling and when the bond yield is too high, a market sider a risk-free government interest rate as the Stochastic Optimization, adjustment is needed resulting in a shift out of discount factor of future earnings. More seri- Emeritus at the University stocks into bonds. If the adjustment is large, it ously, the inflation illusion (the possible impact of British Columbia in causes an equityREPRODUCE market correction (a decline of inflation expectations on the stock market) Vancouver, BC, Canada., of 10% within one year); hence, there is a as suggested by Modigliani and Cohn [1979] and Visiting Professor at the short-term negative ERP. The model predicted is not taken into consideration. Second, the Mathematical Institute, TO Oxford University and the the 1987 U.S., 1990 Japan, 2000 U.S., and model assumes the comparability of an earn- ICMA Centre, University 2002 U.S. corrections. ings-to-price ratio (EP), a real quantity, to a of Reading. A similar valuation model using the 30- nominal, bond-induced interest rate (Campbell [email protected] year long bond rate and the equity yield dif- and Vuolteenaho [2004]). Asness [2000, 2003], ference as the underlying measure of relative and Ritter and Warr [2002] discussed these ILLEGALequity market valuation was suggested by issues. Consigli, MacLean, Zhao and Ziemba Ziemba and Schwartz [1991] (see also Ziemba [2006] propose a stochastic model of equity IS [2003], and Koivu, Pennanen, and Ziemba returns based on an extension of the Fed model [2005]). The partial predictability of stock inclusive of a risk premium in which market IT returns has been analyzed and confirmed by corrections are endogenously generated by the Fama and French [1988b], and Poterba and bond–stock yield difference. The model Summers [1988]. The ability of financial and accommodates both cases of prolonged yield accounting variables to predict individual stock deviations leading to a long series of small SPRING 2008 THE JOURNAL OF PORTFOLIO MANAGEMENT 63 Copyright © 2008 declines in the equity market and the case, which is pecu- The bond–stock earnings yield differential, liar to recent speculative bubbles, of a series of corrections BSEYD(t) = r(t) – y(t), is related to the (random) valua- over limited time periods. The inclusion of the yield dif- tion measure and the equity yield, ferential as a key driver of the market correction process is tested and the model is validated with market data. St() BSEYD() t The next, or second, section discusses the bond–stock −=1 (4a) pt%() yt() valuation model and shows its original application to the October 1987 correction. Hence, the ERP is not con- stant and thus is partially predictable. The third section BSEYD( t)= BSYR () t − 1 y () t (4b) discusses overvaluation and possible forthcoming correc- tions. The fourth section discusses empirical evidence from the U.S., U.K., Japan, Germany, and Canada. The fifth The differential reflects the difference between the section analyzes endogenous instability, risk premiums, current market value and its theoretical value. A more and the nominal-versus-real variable issue. The last section theoretically sound motivation for the predictive ability concludes. of the BSEYD is the basic Gordon formula, where EP is the forward earnings yield (which Schwartz and Ziemba [2000] show is the best predictor of at least individual VALUATION MODEL, EQUITY YIELD, Japanese stock prices), AND 10-YEAR INTEREST RATE EP – nominal yield = equity risk premium – real The Fed model in its original 1996 form states the growth – inflation, so the BSEYD can be used as a proxy dependence of a fair stock price level, p~(t), at time t to for the unobservable right-side economic variables. the expected earnings, E(t), and the 10-year Treasury For a given equity yield, the BSEYD and the BSYR rate, r(t). Earnings expectations are fully incorporated in can be used to identify zones of under- and overvaluation prices and discounted at the current 10-year risk-free and to forecast possible forthcoming market adjustments. rate for t = 1, 2, …, Under the Fed model assumptions, we expect the market, even with prolonged deviations, to fluctuate around its Et() theoretical value and, thus from time to time, the BSYR pt%()= (1) rt() should converge to one and the BSEYD to zero. Alter- natively, a market risk premium should be accounted for and future earnings accordingly discounted by an interest Earnings per share, y(t), are computed by equity rate above the prevailing risk-free rate (10-year maturity investors as the expected earnings for a given unit invest- rates in the canonical Fed model assumption). ment in the stock market with equity shares, S(t), A classic example of the use of this model is the stock market correction in October 1987 illustrated in Et() Exhibit 1. It is from this application that Ziemba’s Yamaichi yt()= (2) St() Research Institute study group in 1988 formulated the BSEYD measure described in Ziemba and Schwartz [1991], and Ziemba [2003]. The danger zone was entered Et() then St()= Yt() . There is a direct relationship between in May 1987 and the correction occurred in October, the equity yield in Equation (2) and the risk-free rate in four months later. During June,July, and August, investors Equation (1). The ratio of the current market value to kept rebalancing their portfolios from the bond to the the theoretical value is the bond–stock yield ratio, BSYR(t), equity market (MSCI TRI + 13.87% over the quarter). The equity market then fell –31.80% in the following Et() quarter (September to November 1987) with the majority of the decline occurring in October. In order to validate St() yt() rt() = = = BSYR() t the approach, Berge and Ziemba [2006] used eight dif- pt%() Et() yyt() ferent strategies to test the predictive ability of the BSEYD rt() (3) or, equivalently, the BSYR (see Exhibit 2). The strategies 64 THE PREDICTIVE ABILITY OF THE BOND–STOCK EARNINGS YIELD DIFFERENTIAL MODEL SPRING 2008 Copyright © 2008 E XHIBIT 1 These 60 or 120 observations, respectively, inclu- Behavior of BSEYD in U.S. Around October 1987 ding the value of the current month, define the threshold Stock Market Correction levels for the end of that month. As time evolves, the most recent monthly value is added and the oldest value is omitted. Moving intervals diminish the impact of changes in the regulatory framework of the economy on EP ratios over time, since high past values of the BSEYD are eventually excluded. For the historical values of the BSEYD, two different distributional concepts are used to define the predetermined exit and entry threshold levels: normal and historical. In the case of normality, the mean and standard deviation of the historical range of BSEYDs are 1 t BSEYDtd, = ∑ BSEYD j (5) d jtd=− +1 and t 1 2 s = ()BSEYD− BSEYDtd, (6) BSEYDtd, ∑ j d −1 jtd=− +1 respectively, where d is the length of the interval consid- ered. The exit threshold level is Source: Berge and Ziemba [2006]. Out, ND TLtd,,αα=+ BSEYDtd, z. sBSEYD (7) are defined over either 5- or 10-year time-data intervals, 11td, under normal or historical return distribution assump- tions, and different fractile levels on such distributions for and the entry threshold level is exiting and entering the equity market. The threshold In, ND TL=+ BSEYDtd, z. s (8) levels were specified for the BSEYD measure. td,,αα22BSEYDtd, E XHIBIT 2 Strategies Used to Evaluate the Robustness (Predictive Ability) of BSEYD-based Strategies Source: Berge and Ziemba [2006]. SPRING 2008 THE JOURNAL OF PORTFOLIO MANAGEMENT 65 Copyright © 2008 α α equivalents, the yield on 3-month T-bills is used. Data where Zα1 and Zα2 are the 1- and 2-fractiles, respec- tively, of the standard normal probability distribution. The for 3-month T-bills are from Global Financial Data (GFD) α α and Thomson Financial Datastream. second concept calculates the 1- and 2 fractiles of the historical distribution. The α-fractile of d observations is Data on 10-year government bond yields come from various sources.
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