Predicting the Equity Premium With Dividend Ratios

Our paper reexamines the forecasting regressions which predict annual aggregate stock market returns net of the risk-free rate with lagged aggregate dividend-yield ratios and dividend-price ratios. Prior to 1990, the conditional dividend yield could reliably outperform the historical equity premium mean in predicting future equity premia *in-sample*. But our paper shows that the dividend ratios could not outperform the prevailing unconditional mean *out-of-sample*, plus any residual power was directly related to only two years, 1974 and 1975. As of 2000, even this in-sample predictive ability has disappeared. Our paper also documents changes in the time-series processes of the dividends themselves and shows that an increasing persistence of dividend-price ratio is largely responsible for weak stock return predictability.

Stock Returns and Equity Premium Evidence Using Dividend Price Ratios and Dividend Yields in Malaysia

The empirical findings of Goyal and Welch (2003) and Cochrane (2006) suggested that dividend yields and dividend ratios are robust predictors of annual stock returns and annual equity premia. However, Goyal and Welch (2003) asserted that many researchers considered dividend yields to be a good predictor for the equity premium before the 1990s but not after the 1990s. We apply these models to the Malaysian market. Our general findings suggest that the in-sample performances of the KLCI Malaysian datasets present similar results to those predicted by Goyal and Welch (2003, 2006). Meanwhile, the Mincer-Zarnowitz (1969) regression forecast tests for out of sample performances illustrate poor predictability of stock returns and equity premiums using both dividend price ratios and dividend yields. Cochrane (2006) suggested that if stock returns and dividend growth are not predictable, then price growth must be forecastable to bring the dividend yields back to equilibrium after any shock given that the dividend yields are stationary. We find that the growth of dividends is predictable using data deflated by changes in the consumer price index. Thus, the overall results suggest that both dividend price ratio and dividend yield models have significant effects though the dividend yield model is a superior predictor of stock returns and equity premiums in the Malaysian context.Dividend yields, Dividend price ratios, Stock returns, Equity premium, Asian financial crisis 1997

Market timing with aggregate and idiosyncratic stock volatilities

Guo and Savickas [2005] show that aggregate stock market volatility and average idiosyncratic stock volatility jointly forecast stock returns. In this paper, we quantify the economic significance of their results from the perspective of a portfolio manager. That is, we evaluate the performance, e.g., the Sharpe ratio and Jensen's alpha, of a mean-variance manager who tries to time the market based on those two variables. We find that, over the period 1968-2004, the associated market-timing strategy outperforms the buy-and-hold strategy, and the difference is statistically and economically significant.Stock exchanges

Stock return predictability and stationarity of dividend yield

This paper first investigates the stationarity of dividend yield and then analyzes the predictive ability of the adjusted dividend yield which removes structural changes and high persistence characteristics. Empirical results have found that the dividend yield follows a mean-reverting process in each regime, and the convergence speed depends on the mean and variance. Moreover, the dividend yield is also global stationary. Finally, the adjusted dividend yield can predict future stock returns, and its predictive ability is time-invariant.mean reversion, regime switching, stationarity, stock return predictability

Stock return predictability: the role of inflation and threshold dynamics

This paper argues that the nature of stock return predictability varies with the level of inflation. We contend that the nature of relations between economic variables and returns differs according to the level of inflation, due to different economic risk implications. An increase in low level inflation may signal improving economic conditions and lower expected returns, while the opposite is true with an equal rise in high level inflation. Linear estimation provides contradictory coefficient values, which we argue arises from mixing coefficient values across regimes. We test for and estimate threshold models with inflation and the term structure as the threshold variable. These models reveal a change in either the sign or magnitude of the parameter values across the regimes such that the relation between stock returns and economic variables is not constant. Measures of in-sample fit and a forecast exercise support the threshold models. They produce a higher adjustedR2, lower MAE and RMSE and higher trading related measures. These results help explain the lack of consistent empirical evidence in favour of stock return predictability and should be of interest to those engaged in stock market modelling as well as trading and portfolio management

Are there bubbles in the art market? The detection of bubbles when fair value is unobservable

The purpose of this paper is to look for bubbles in the Art Market using a structure based on steady state results for TAR models and appropriate definitions of bubbles recently put forward by Knight, Satchell and Srivastava (2011). The usual method for investigating bubbles is to measure prices as deviations from fair value. We assess whether it is meaningful to define a fair value of art and conclude that it is very challenging empirically to implement any definition. We then treat fair value as zero in one instance and unobservable in the other case and in both cases provide evidence of bubbles in the art market

Predicting the UK Equity Premium with Dividend Ratios: An Out-Of-Sample Recursive Residuals Graphical Approach

The purpose of this paper is to evaluate the ability of dividend ratios to predict the UK equity premium. Specifically, we apply the Goyal and Welch (2003) methodology to equity premia derived from the UK FTSE All-Share index. This approach provides a powerful graphical diagnostic for predictive ability. Preliminary in-sample univariate regressions reveal that the UK equity premium contains an element of predictability. Moreover, out-of-sample the considered models outperform the historical moving average. In contrast to similar work on the US, the graphical diagnostic then indicates that dividend ratios are useful predictors of excess returns. Finally, Campbell and Shiller (1988) identities are employed to account for the time-varying properties of the dividend yield and dividend growth processes. It is shown that by instrumenting the models with the identities, forecasting ability can be improved.

Recursive Portfolio Selection with Decision Trees

A great proportion of stock dynamics can be explained using publicly available information. The relationship between dynamics and public information may be of nonlinear character. In this paper we offer an approach to stock picking by employing so-called decision trees and applying them to XETRA DAX stocks. Using a set of fundamental and technical variables, stocks are classified into three groups according to the proposed position: long, short or neutral. More precisely, by assessing the current state of a company, which is represented by fundamental variables and current market situation, well reflected by technical variables, it is possible to suggest if the current market value of a company is underestimated, overestimated or the stock is fairly priced. The performance of the model over the observed period suggests that XETRA DAX stock returns can adequately be predicted by publicly available economic data. Another conclusion of this study is that the implied volatility variable, when included into the training sample, boosts the predictive power of the model significantly.CART, decision trees in finance, nonlinear decision rules, asset management, portfolio optimisation

Can the information content of share repurchases improve the accuracy of equity premium predictions?

We adjust the dividend–price ratio for share repurchases and investigate whether predictive power can be improved when constructing forecasts of the UK and French equity premia. Regulations in the two largest European stock markets allow us to employ actual repurchase data in our predictive regressions. Hence, we are able to overcome problems associated with markets characterised by less stringent disclosure requirements, where investors might have to rely on proxies for measuring repurchase activity. We find that predictability does not improve either in a statistical or in an economically significant sense once actual share repurchases are considered. Furthermore, we employ a proxy measure of repurchases which can be easily constructed in international markets and demonstrate that its predictive content is not in line with that of the actual repurchase data