Features of Financial Returns Modelling Price Volatility Forecasting Standard Deviations The Accuracy of Autocorrelation Estimates Testing the Random Walk Hypothesis Forecasting Trends in Prices Evidence Against the Efficiency of Futures Markets Valuing Options Appendix: A Computer Program for Modelling Financial Time Series.

Modelling Financial Time Series

We investigate lead-lag relationships among monthly country stock returns and identify a leading role for the United States: lagged U.S. returns significantly predict returns in numerous non-U.S. industrialized countries, while lagged non-U.S. returns display limited predictive ability with respect to U.S. returns. We estimate a news-diffusion model, and the results indicate that return shocks arising in the United States are only fully reflected in equity prices outside of the United States with a lag, consistent with a gradual information diffusion explanation of the predictive power of lagged U.S. returns.

International Stock Return Predictability: What Is the Role of the United States?

We survey the literature on stock return forecasting, highlighting the challenges faced by forecasters as well as strategies for improving return forecasts. We focus on U.S. equity premium forecastability and illustrate key issues via an empirical application based on updated data. Some studies argue that, despite extensive in-sample evidence of equity premium predictability, popular predictors from the literature fail to outperform the simple historical average benchmark forecast in out-of-sample tests. Recent studies, however, provide improved forecasting strategies that deliver statistically and economically significant out-of-sample gains relative to the historical average benchmark. These strategies – including economically motivated model restrictions, forecast combination, diffusion indices, and regime shifts – improve forecasting performance by addressing the substantial model uncertainty and parameter instability surrounding the data-generating process for stock returns. In addition to the U.S. equity premium, we succinctly survey out-of-sample evidence supporting U.S. cross-sectional and international stock return forecastability. The significant evidence of stock return forecastability worldwide has important implications for the development of both asset pricing models and investment management strategies.

Forecasting Stock Returns

This paper examines the volatility of common stocks of the Athens Stock Exchange at the market, industry and firm level. Over the period from 1988 to 2009 there has been a considerable increase in firm-level volatility relative to the market volatility, which implies that it takes increasingly more stocks to diversify away idiosyncratic risk. All volatility series move together and they are trended upwards. All three volatility measures show a countercyclical behaviour relative to GDP growth, and they all help to forecast GDP. Correlations among individual stocks have increased over the sample period, yet the explanatory power of the market model for a typical stock is still relatively low. All three volatility series rise during times of low returns. Factors that may be responsible for these findings are suggested.

Have individual stocks become more volatile : an empirical exploration of idiosyncratic risk

A Comprehensive Look at the Empirical Performance of Equity Premium Prediction

This paper investigates the relationship between stock market volatility and the business cycle in four major economies, namely the US, Canada, Japan and the UK. We employ both linear and nonlinear bivariate causality tests and we further conduct a multivariate analysis to explore possible spillover effects across countries. Our results suggest that there is a bidirectional causal relationship between stock market volatility and the business cycle within each country and additionally reveal that the recent financial crisis plays an important role in this context. Finally, we identify a significant impact of the US on the remaining markets.

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Stock market volatility and business cycle: Evidence from linear and nonlinear causality tests

Predicting the equity premium with dividend ratios: Reconciling the evidence

Information demand and stock return predictability

This paper evaluates the ability of dividend ratios to predict the equity premium. We conduct an out-of-sample comparative study and apply the Goyal and Welch (2003) methodology to equity premia derived from the UK FTSE All-Share and the S&P 500 indices. Preliminary in-sample univariate regressions reveal that in both markets the equity premium contains an element of predictability. However, out-of-sample the considered models outperform the historical moving average only in the UK context. This is confirmed by the graphical diagnostic which further indicates that dividend ratios are useful predictors of UK excess returns. Our paper provides a possible explanation of why dividend ratios might be more informative in the UK market and links these findings to a phenomenon that is not widely known in the predictability literature. Finally, Campbell and Shiller (1988b) identities are employed to account for the time-varying properties of the dividend ratio and dividend growth processes. It is shown that by instrumenting the models with the identities, forecasting ability can be further improved.

Predicting the Equity Premium with Dividend Ratios: Reconciling the Evidence

https://cronfa.swan.ac.uk/Record/cronfa21492/Download/0021492-01062015145247.pdf

Fotios I. Papadimitriou

Papers

Stock market volatility and business cycle: Evidence from linear and nonlinear causality tests

Predicting the equity premium with dividend ratios: Reconciling the evidence

Information demand and stock return predictability

Predicting the Equity Premium with Dividend Ratios: Reconciling the Evidence

UK imports, third country effect and the global financial crisis: Evidence from the asymmetric ARDL method