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Asian Review of Financial Research, Vol., No..
pp.43~86
pp.43~86
Short-term idiosyncratic momentum in cross-sectional stock returns : Empirical evidence
Cheoljun EOM School of Business, Pusan National University, Busan 46241, Rep. of Korea
This study uncovers short-term idiosyncratic momentum (SIMOM) in cross-sectional stock returns. SIMOM utilizes the daily residuals estimated by the pricing models for the previous month. This differs from idiosyncratic volatility (IVOL) and short-term reversals (SREV) in the same previous month. SIMOM exhibits persistently significant positive performance until the next eight months and has unique information that cannot be explained by known factor premiums or firm-specific variables. Institutional and foreign investors who focus on public market information tend to underreact to high SIMOM stocks, leading to over-selling trading. . Individual investors who prioritize firm-specific information seem to use high SIMOM stocks as a profitable strategy. There is a strong negative relationship, exceeding 95%, between the performance of SIMOM and IVOL in terms of their predictive power for expected returns; that is, the existence of a significant positive SIMOM implies the existence of a significant negative IVOL, and vice versa. Therefore, this finding is expected to lead to further studies that verify SIMOM and provide new insights into the IVOL puzzle and individual investors¡¯ trading behavior.
Cheoljun EOM
This study uncovers short-term idiosyncratic momentum (SIMOM) in cross-sectional stock returns. SIMOM utilizes the daily residuals estimated by the pricing models for the previous month. This differs from idiosyncratic volatility (IVOL) and short-term reversals (SREV) in the same previous month. SIMOM exhibits persistently significant positive performance until the next eight months and has unique information that cannot be explained by known factor premiums or firm-specific variables. Institutional and foreign investors who focus on public market information tend to underreact to high SIMOM stocks, leading to over-selling trading. . Individual investors who prioritize firm-specific information seem to use high SIMOM stocks as a profitable strategy. There is a strong negative relationship, exceeding 95%, between the performance of SIMOM and IVOL in terms of their predictive power for expected returns; that is, the existence of a significant positive SIMOM implies the existence of a significant negative IVOL, and vice versa. Therefore, this finding is expected to lead to further studies that verify SIMOM and provide new insights into the IVOL puzzle and individual investors¡¯ trading behavior.
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