Stock market return predictability: A combination forecast perspective |
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| Affiliation: | 1. School of Economics and Management, Beijing University of Chemical of Technology, Beijing, China;2. School of Economics and Management, Beijing Jiaotong University, Beijing, China;1. School of International Economics and Trade, Nanjing University of Finance and Economics, Nanjing, China;2. Rotman Commerce, University of Toronto, Toronto, Canada;3. SHU-UTS SILC Business School, Shanghai University, 99 Shangda Road, Shanghai, China;1. Central Bank of Turkey, Ümraniye, İstanbul, Turkey;2. Department of Business Administration, Middle East Technical University, 06800 Ankara, Turkey;1. Department of Electrical and Electronics Engineering, University of West Attica, Ancient Olive Grove Campus, 12241 Egaleo, Greece;2. Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, Metaxa and Vasileos Pavlou, Penteli, GR-15236 Athens, Greece |
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| Abstract: | Based on traditional macroeconomic variables, this paper mainly investigates the predictability of these variables for stock market return. The empirical results show the mean combination forecast model can achieve superior out-of-sample performance than the other forecasting models for forecasting the stock market returns. In addition, the performances of the mean combination forecast model are also robust during different forecasting windows, different market conditions, and multi-step-ahead forecasts. Importantly, the mean combination forecast consistently generates higher CER gains than other models considering different investors' risk aversion coefficients and trading costs. This paper tries to provide more evidence of combination forecast model to predict stock market returns. |
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