Predicting Stock Returns (eBook)

David G. McMillan is a Professor of Finance at the University of Stirling, UK. His research interests are in empirical financial economics, and include forecasting asset returns and volatility, modelling the linkages between asset prices and macroeconomic variables and examining the behaviour of financial and investor ratios. David has published widely on these topics in internationally respected peer-reviewed journals such as the Journal of Banking and Finance and the Oxford Bulletin of Economics and Statistics. He is a senior editor for the Cogent Economics and Finance and Cogent Business and Management journals and sits of the editorial board of several internationally respected journals, including the European Journal of Finance and the Journal of Asset Management.

Predicting Stock Returns 2
Contents 6
List of Figures 7
List of Tables 8
1 Introduction 11
Abstract 11
References 16
2 Where Does Returns and Cash-Flow Predictability Occur? Evidence from Stock Prices, Earnings, Dividends and Cointegration 18
Abstract 18
2.1Introduction 19
2.2Methodology 21
2.3Data and Empirical Results 23
Data 23
Cointegration and State-Space Models 23
Returns and Cash-Flow Predictability 27
2.4Summary and Conclusion 32
References 34
3 Forecasting Stock Returns—Historical Mean Vs. Dividend Yield: Rolling Regressions and Time-Variation 36
Abstract 36
3.1Introduction 37
3.2Empirical Methodology 39
3.3Data and Empirical Results 43
Discussion and Further Results 55
3.4Summary and Conclusion 62
References 63
4 Returns and Dividend Growth Switching Predictability 66
Abstract 66
4.1Introduction 67
4.2Methodology 68
4.3Data and Results 69
4.4Summary and Conclusion 82
References 83
5 Which Variables Predict and Forecast Stock Market Returns? 85
Abstract 85
5.1Introduction 86
5.2Background 88
5.3Data 90
5.4Empirical Results 91
5.5Forecasting 101
5.6Summary and Conclusion 104
Appendix—Data Series 106
References 108
6 Forecast and Market Timing Power of the Model and the Role of Inflation 110
Abstract 110
6.1Introduction 111
6.2Data and Linear Forecasting 114
Data and Empirical Methodology 114
In-Sample Predictive and Out-of-Sample Forecast Results 118
6.3Probit Model and Market Timing 125
6.4The Role of Inflation and Threshold Regression 128
6.5Summary and Conclusions 133
References 134
7 Summary and Conclusion 137
Abstract 137
Index 140