The Gilt-Equity Yield Ratio and the Predictability of UK and US Equity Returns

A number of financial variables have been shown to be effective in explaining the time-series of aggregate equity returns in both the UK and the US. These include, inter alia , the equity dividend yield, the spread between the yields on long and short government bonds, and the lagged equity return. Recently, however, the ratio between the long government bond yield and the equity dividend yield – the gilt-equity yield ratio – has emerged as a variable that has considerable explanatory power for UK equity returns. This paper compares the predictive ability of the gilt-equity yield ratio with these other variables for UK and US equity returns, providing evidence on both in-sample and out-of-sample performance. For UK monthly returns, it is shown that while the dividend yield has substantial in-sample explanatory power, this is not matched by out-of sample forecast accuracy. The gilt-equity yield ratio, in contrast, performs well both in-sample and out-of-sample. Although the predictability of US monthly equity returns is much lower than for the UK, a similar result emerges, with the gilt-equity yield ratio dominating the other variables in terms of both in-sample explanatory power and out-of-sample forecast performance. The gilt-equity yield ratio is also shown to have substantial predictive ability for long horizon returns.     

The Gilt-Equity Yield Ratio and the Predictability of UK and US Equity Returns

A number of financial variables have been shown to be effective in explaining the time-series of aggregate equity returns in both the UK and the US. These include, inter alia , the equity dividend yield, the spread between the yields on long and short government bonds, and the lagged equity return. Recently, however, the ratio between the long government bond yield and the equity dividend yield – the gilt-equity yield ratio – has emerged as a variable that has considerable explanatory power for UK equity returns. This paper compares the predictive ability of the gilt-equity yield ratio with these other variables for UK and US equity returns, providing evidence on both in-sample and out-of-sample performance. For UK monthly returns, it is shown that while the dividend yield has substantial in-sample explanatory power, this is not matched by out-of sample forecast accuracy. The gilt-equity yield ratio, in contrast, performs well both in-sample and out-of-sample. Although the predictability of US monthly equity returns is much lower than for the UK, a similar result emerges, with the gilt-equity yield ratio dominating the other variables in terms of both in-sample explanatory power and out-of-sample forecast performance. The gilt-equity yield ratio is also shown to have substantial predictive ability for long horizon returns.     

Equity premium prediction and the state of the economy

We detect cyclical variation in the predictive information of economic fundamentals, which can be used to substantially improve and simplify out-of-sample equity premium prediction. Economic fundamentals based on stock-specific information (notably the dividend yield) deliver better predictions in expansions. Economic fundamentals based on aggregate information (notably the short rate) deliver better predictions in recessions. Accordingly, a simple forecast combination of one predictor that generates cyclical forecasts and one predictor that generates countercyclical forecasts can deliver statistically significant and economically valuable equity premium predictions in both expansions and recessions. A prominent two-predictor forecast combination that performs well is the dividend yield and the short rate. Strategies designed for ex-ante timing of the business cycle can provide additional economic gains in equity premium prediction.     

Stock and bond joint pricing,consumption surplus,and inflation news

In this paper, Bekaert et al.’s (2010) model is modified by allowing consumption growth to depend on dividend yield rather than dividend growth. With a simplified inflation dynamic, the general equilibrium model is characterized by a system of linear and affine stochastic equations. From these equations, a closed-form solution jointly pricing equity and bonds is derived. The generalized method of moments is used to demonstrate that our model’s calibrated moments broadly match the first and second moments of stocks, bonds, and other macroeconomic variables in the US. Our estimated equity premium is 6.0%, which closely matches its actual value of 5.6%. The predicted risk aversion is countercyclical. Moreover, an out-of-sample test indicates the significant improvement of predictive power on the price–dividend ratio over Campbell and Cochrane’s (1999) model. Our model can further capture the dramatic increase in the price–dividend ratio after the 1990s.     

The UK Equity Premium: 1901–2004

Abstract:  This paper examines the UK equity premium over more than a century using dividend growth to estimate expectations of capital gains employing the approach of Fama and French (2002) . Over recent decades estimated equity premia implied by dividend growth have been much lower than that produced by average stock returns for the UK market as a whole; a finding corroborated by all economic sub-sectors. The empirical analysis suggests this is primarily due to a declining discount rate, during the latter part of the 20th century, which would rationally stimulate unanticipated equity price rises during this period. Thus, I conclude that historical stock returns over recent decades have been above investors' expectations.     

Dividend premium: Are dividend-paying stocks worth more?

This paper reports that the relation between dividend payout and firm value is positive. Panel data regressions suggest that the dividend premium for firms' equity is 17.4% and the dividend premium for firms' assets is 7.1%. The tests using propensity score matching methodology report a lower – but still positive and statistically significant – dividend premium: 12.5% for equity and 6.1% for assets. Thus, stock prices of dividend payers are greater by 12.5% or 17.4% on average (depending on methodology) compared to those of nonpayers. We find that policy-related economic uncertainty and the proportion of firms paying dividends explain more than half of the variation in dividend premium for assets.     

Re-examination of the historical equity risk premium in Australia

In light of the ongoing debate over the value of the equity risk premium, its increasing use in the regulatory setting, and the impact of dividend imputation on the premium, this paper presents a timely new look at the historical equity risk premium in Australia, and provides an improved understanding of the historical record. We document concerns about data quality that become increasingly important the further back in time one looks. In particular, there are sufficient question marks over the quality of data prior to 1958 to warrant any estimates based thereon to be treated with caution. Accordingly, we present a new set of estimates of the historical equity risk premium corresponding to periods of increasing data quality but of decreasing sample size. Relative to bonds (bills), the equity premium has averaged 6.3 per cent (6.8 per cent) per annum over 1958–2005, which is a period of relatively good data quality. Together with other results in the paper, the findings reveal a historical estimate that is substantially less than widely cited historical studies would otherwise indicate. We reconcile prior evidence through documenting a dividend adjustment that has typically been overlooked. We also provide estimates that incorporate an adjustment for imputation credits.     

Income Insurance and the Equilibrium Term Structure of Equity

Output, wages, and dividends feature term structures of variance ratios that are respectively flat, increasing, and decreasing. Income insurance from shareholders to workers explains these term structures. Risk‐sharing smooths wages but only concerns transitory risk and hence enhances short‐run dividend risk. As a result, actual labor‐share variation largely forecasts the risk, premium, and slope of dividend strips. A simple general equilibrium model in which labor rigidity affects dividend dynamics and the price of short‐run risk reconciles standard asset pricing facts with the term structures of the equity premium, volatility, and macroeconomic variables, which are at odds in leading models.     

Out-of-sample equity premium predictability and sample split–invariant inference

For a comprehensive set of 21 equity premium predictors we find extreme variation in out-of-sample predictability results depending on the choice of the sample split date. To resolve this issue we propose reporting in graphical form the out-of-sample predictability criteria for every possible sample split, and two out-of-sample tests that are invariant to the sample split choice. We provide Monte Carlo evidence that our bootstrap-based inference is valid. The in-sample, and the sample split invariant out-of-sample mean and maximum tests that we propose, are in broad agreement. Finally we demonstrate how one can construct sample split invariant out-of-sample predictability tests that simultaneously control for data mining across many variables.     

The expected value premium

Fama and French [2002. The equity premium. Journal of Finance 57, 637–659] estimate the equity premium using dividend growth rates to measure expected rates of capital gain. We apply their method to study the value premium. From 1945 to 2005, the expected value premium is on average 6.1% per annum, consisting of an expected dividend growth component of 4.4% and an expected dividend price ratio component of 1.7%. Unlike the equity premium, the value premium has been largely stable over the last half century.     

Do return prediction models add economic value?

We compare statistical and economic measures of forecasting performance across a large set of stock return prediction models with time-varying mean and volatility. We find that it is very common for models to produce higher out-of-sample mean squared forecast errors than a model assuming a constant equity premium, yet simultaneously add economic value when their forecasts are used to guide portfolio decisions. While there is generally a positive correlation between a return prediction model’s out-of-sample statistical performance and its ability to add economic value, the relation tends to be weak and only explains a small part of the cross-sectional variation in different models’ economic value.     

Four centuries of return predictability

We combine annual stock market data for the most important equity markets of the last four centuries: the Netherlands and UK (1629–1812), UK (1813–1870), and US (1871–2015). We show that dividend yields are stationary and consistently forecast returns. The documented predictability holds for annual and multi-annual horizons and works both in- and out-of-sample, providing strong evidence that expected returns in stock markets are time-varying. In part, this variation is related to the business cycle, with expected returns increasing in recessions. We also find that, except for the period after 1945, dividend yields predict dividend growth rates.     

Do jumps contribute to the dynamics of the equity premium?

This paper investigates whether risks associated with time-varying arrival of jumps and their effect on the dynamics of higher moments of returns are priced in the conditional mean of daily market excess returns. We find that jumps and jump dynamics are significantly related to the market equity premium. The results from our time-series approach reinforce the importance of the skewness premium found in cross-sectional studies using lower-frequency data; and offer a potential resolution to sometimes conflicting results on the intertemporal risk-return relationship. We use a general utility specification, consistent with our pricing kernel, to evaluate the relative value of alternative risk premium models in an out-of-sample portfolio performance application.     

Long‐Run Risk and Its Implications for the Equity Premium Puzzle: New Evidence from a Multivariate Framework

This paper investigates the empirical evidence of long‐run risk and its implications for the equity premium puzzle. We find that the long‐run risk model is generally weakly identified and that standard inferences tend to underestimate the uncertainty of long‐run risk. We extend the LM‐type test of Ma and Nelson (2010) that remains valid under weak identification to the bivariate VARMA‐GARCH model of consumption and dividend growth. The results cast doubt on the validity of long‐run risk as an explanation for the equity premium puzzle. We also evaluate the approach of Bansal, Kiku, and Yaron (2007a), which extracts long‐run risk by regressing consumption growth and its volatility on predictive variables. The results using the Bonferroni Q‐test of Campbell and Yogo (2006) suggest that consumption and dividend growth are generally unpredictable by the price‐dividend ratio and risk‐free rate. This casts doubt on the validity of the BKY approach.     

Risk,uncertainty, and asset prices

We identify the relative importance of changes in the conditional variance of fundamentals (which we call “uncertainty”) and changes in risk aversion in the determination of the term structure, equity prices, and risk premiums. Theoretically, we introduce persistent time-varying uncertainty about the fundamentals in an external habit model. The model matches the dynamics of dividend and consumption growth, including their volatility dynamics and many salient asset market phenomena. While the variation in price–dividend ratios and the equity risk premium is primarily driven by risk aversion, uncertainty plays a large role in the term structure and is the driver of countercyclical volatility of asset returns.     

Machine learning and asset allocation

Investors have access to a large array of structured and unstructured data. We consider how these data can be incorporated into financial decisions through the lens of the canonical asset allocation decision. We characterize investor preference for simplicity in models of the data used in the asset allocation decision. The simplicity parameters then guide asset allocation along with the usual risk aversion parameter. We use three distinct and diverse macroeconomic data sets to implement the model to forecast equity returns (the equity risk premium). The data sets we use are (a) price‐dividend ratios, (b) an array of macroeconomic series, and (c) text data from the Federal Reserve's Federal Open Market Committee (FOMC) meetings.     

A century of equity premium predictability and the consumption–wealth ratio: An international perspective

This paper re-examines the predictive ability of the consumption–wealth ratio (cay) on the equity premium using hand-collected annual data spanning one century for four major economies. In addition to statistical tests of out-of-sample forecast accuracy, we measure the economic value of the predictive information in cay in a stylized asset allocation strategy. We find that cay does not contain predictive power prior to World War II, when a structural break occurs for all countries. In the postwar period, while statistical tests provide mixed evidence, economic criteria uncover substantial predictive power in cay, further enhanced when allowing for economically meaningful restrictions.     

Forecasting stock returns with large dimensional factor models

We study equity premium out-of-sample predictability by extracting the information contained in a high number of macroeconomic predictors via large dimensional factor models. We compare the well-known factor model with a static representation of the common components with the Generalized Dynamic Factor Model, which accounts for time series dependence in the common components. Using statistical and economic evaluation criteria, we empirically show that the Generalized Dynamic Factor Model helps predicting the equity premium. Exploiting the link between business cycle and return predictability, we find accurate predictions also by combining rolling and recursive forecasts in real-time.     

Rare disaster risk and the expected equity risk premium

Consistent with the predictions of rare disaster models, we find that a proxy for the time‐varying probability of rare disasters helps to explain fluctuations in expectations of the equity risk premium. Our proxy for disaster risk is a recently developed measure of global political instability, and the expected market risk premium is from Value Line analysts' expected stock returns. Consistent with long‐run risk models, uncertainty about expected GDP growth and expected consumption growth is also significantly positively related to the expected market risk premium. We obtain similar results when we use the earnings–price ratio and the dividend–price ratio as proxies for the expected market risk premium.     

DEFAULT RISK PREMIA IN THE NEAR-CASH INVESTMENT MARKET: THE CASE OF AUCTION RATE PREFERRED STOCK VERSUS COMMERCIAL PAPER

Auction rate preferred stock (ARPS) is often regarded as an alternative to other near-cash instruments such as commercial paper while the dividend exclusion for ARPS offers tax advantages to corporate purchasers. The mean default risk premium for ARPS, relative to commercial paper, is estimated at 83 basis points during stable financial markets. This default premium appears to surge during unstable equity markets, having jumped by 192 basis points in November 1987. Lower-rated ARPS shows even larger changes, with yields 40–50 basis points above yields on high-rated ARPS, adjusted for the normal risk premium differential. The perceived risk change of ARPS underscores how quickly market participants re-evaluate default risk, and even the importance of the priority order among debt and equity claimants. Findings suggest ARPS and commercial paper are not an acceptable substitute for commercial paper during times of unsettled equity markets.