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frequency information into one model. We consider subsample averaging, bootstrap averaging, forecast averaging methods for the … the averaging methods (subsample averaging, bootstrap averaging, forecast averaging), which serve as different ways of …
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Stock returns predictability has been a long-standing topic in the literature on financial economics. Developments in prediction technology have facilitated the wide use of machine learning techniques, which motivates our study of whether stock returns predictability can be improved using...
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-forecasting ability managers. Our findings support the signaling theory of dividend changes and indicate that management forecasting …
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construct a proxy of the adjustment factor using the sequence of dispersion of analysts earnings forecast. We provide empirical …
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not observed at the time that the forecast is made--but can nonetheless improve forecasting accuracy by reducing parameter … of forecasting excess bond and equity returns. We find substantial improvements in out-of-sample forecast accuracy for …
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