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The Impact of Size Bias on Empirical Research on Stock Market Anomalies: US and International Evidence
Journal Contribution - Journal Article Conference Contribution
Using an international Thomson Reuters Datastream database, where size bias is minimized, we show that some specification decisions, and especially those related to size bias, may have a significant impact on asset pricing test results. We use the FF model as test case. We also show that size bias affects the optimal factor portfolio specifications. More specifically, using standard asset pricing models we encounter pricing errors for the ten percent smallest stocks. We, therefore, extend the standard 4-factor model (Carhart, 1997) by two additional risk factors (one size- and one book-to-market factor). This 6-factor model is tested both on US and international data (with 39 countries both developed and emerging) and isable to price the entire size spectrum. We discuss the possible economic explanations of these risk premia for the smallest stocks. The fact that pricing errors are resolved by adding factors rather than characteristics, rules out data problems and information asymmetries as an explanation. Thin trading bias in the beta is also rejected as the source of abnormal returns. Liquidity remains a serious possible candidate, as is the hypothesis of additional downside risk for the smallest firms.
Journal: PROCEEDINGS of the IABE - 2012 Venice - Summer Conference
Pages: 190 - 203