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predictive variance. We show theoretically how this adjustment factor affects both average and volatility of excess returns. We … related to excess volatility as predicted by the model. Further confirming the model's implications, we also show how stock …
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We apply state-of-the-art financial machine learning to assess the return-predictive value of more than 45,000 earnings announcements on a majority of S&P1500 constituents. To represent the diverse information content of earnings announcements, we generate predictor variables based on various...
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An analysis of about 300000 earnings forecasts, created by 18000 individual forecasters for earnings of over 300 S&P listed firms, shows that these forecasts are predictable to a large extent using a statistical model that includes publicly available information. When we focus on the...
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