Geography, Local Sentiment, and Market Anomalies
49 Pages Posted: 20 Nov 2018
Date Written: November 13, 2018
This study shows that market anomalies are stronger for stocks headquartered in states with a history of cross-sectional return predictability. Using a combined measure of mispricing based on 11 prominent anomaly strategies, I find that the level of mispricing for a firm's geographic peers predicts how mispriced the firm itself will be in the future. I find similar results when I consider industrial peers instead, but the effect of neither group is absorbed by the other. States in which firm mispricing is more prevalent are those experiencing relatively higher levels of local investor sentiment and better local macroeconomic conditions. Finally, evidence indicates that the predictability of mispricing based on geography and industry is concentrated on stocks with high levels of analyst forecasting errors.
Keywords: Anomalies, Local Predictability, Mispricing, Sentiment, Industry
JEL Classification: G12, G14
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