Predicting Stock Market Returns by Combining Forecasts
AbstractThe predictability of stock market returns has been a challenge to market practitioners and financial economists. This is also important to central banks responsible for monitoring financial market stability. A number of variables have been found as predictors of future stock market returns with impressive in-sample results. Nonetheless, the predictive power of these variables has often performed poorly for out-of-sample forecasts. This study utilises a new method known as "Aggregate Forecasting Through Exponential Re-weighting (AFTER)" to combine forecasts from different models and achieve better out-of-sample forecast performance from these variables. Empirical results suggest that, for longer forecast horizons, combining forecasts based on AFTER provides better out-of-sample predictions than the historical average return and also forecasts from models based on commonly used model selection criteria.
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Bibliographic InfoPaper provided by Hong Kong Monetary Authority in its series Working Papers with number 0801.
Length: 30 pages
Date of creation: Mar 2008
Date of revision:
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More information through EDIRC
Forecasting; Model combination; Model uncertainty;
Find related papers by JEL classification:
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-05-31 (All new papers)
- NEP-ECM-2008-05-31 (Econometrics)
- NEP-FMK-2008-05-31 (Financial Markets)
- NEP-FOR-2008-05-31 (Forecasting)
- NEP-RMG-2008-05-31 (Risk Management)
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