MEASURING EFFECTS ON STOCK RETURNS OF SENTIMENT INDEXES CREATED FROM STOCK MESSAGE BOARDS

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Abstract

Various techniques and sources of information exist to aid investors in predicting future stock returns. However, no effective proxy for retail investors, such as stock message board users, has been established. This study provides guidelines for creating an effective proxy. The heart of such proxies is sentiment indexes, and in the past the indexes have had low predictive power. Introducing four methodological improvements for applying text classifiers and two probability measurements, we contrast eight widely applied text classifiers to stock message board data. Based on the classifier results and incorporating our new methods, the new sentiment index proves to be a significant “same-day positive but next-day negative” directional indicator.

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