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Research examining the usefulness of non-linear models for stock market returns has almost reached an impasse. While there is general recognition of the superior ability of non-linear models to describe the data, there is less certainty about their ability to forecast the data. As such simple...
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Model selection, i.e., the choice of an asset pricing model to the exclusion of competing models, is an inherently misguided strategy when the true model is unavailable to the researcher. This paper illustrates the advantages of a model pooling approach in characterizing the cross section of...
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microstructure noise and to obtain consistent estimates of the integrated volatility (IV) as a measure of ex-post daily volatility …. Even bias-corrected and consistent (modified) realized volatility (RV) estimates of the integrated volatility can contain … residual microstructure noise and other measurement errors. Such noise is called “realized volatility error”. As such …
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This paper explores the implications of a dividend yield model for predicting aggregate Japanese stock returns using long time-series data from 1949 to 2009. In addition to one-period return tests, we conduct statistical tests based on dividend growth forecasts and long-horizon return forecasts...
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Researchers and practitioners face many choices when estimating an asset's sensitivities toward risk factors, i.e., betas. Using the entire U.S. stock universe and a sample period of more than 50 years, we find that a historical estimator based on daily return data with an exponential weighting...
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The stock expected returns are positively related to operation performances and negatively related to investment and financing activities, we check the three indicators with significant predictive power in the cross-section of stock returns, across large, medium and small cap stock groups: Net...
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