Vikas Mehrotra
Alberta School of Business, University of Alberta
Organised by
Indian Statistical Institute (ISI), Delhi Center
Abstract:
Favoured explanations for the large and persistent turn-of-the-year effect in stock returns are tax-loss selling and institutional investor window-dressing. A new dataset of pre-CRSP NYSE daily stock-level total returns reveals a statistically significant 2.2 percent turn-of-the-year market return between 1874 and 1917, a period preceding income taxes and modern institutional investors in the U.S. The turn-of- he-year return is higher for small, growth and extreme winner and loser stocks. Our evidence implies that taxes cannot be the sole explanation for the turn-of-the-year effect. Either some form of window-dressing predates modern institutional investors, or other explanations for the anomaly must be sought.
Date: November 13, 2019
Time: 03:30 P.M.
Venue:
Seminar 2
Indian Statistical Institute Delhi Centre,
7, S. J. S. Sansanwal Marg,
New Delhi-110016 (INDIA)
Location:
View Larger Map
Alberta School of Business, University of Alberta
Organised by
Indian Statistical Institute (ISI), Delhi Center
Abstract:
Favoured explanations for the large and persistent turn-of-the-year effect in stock returns are tax-loss selling and institutional investor window-dressing. A new dataset of pre-CRSP NYSE daily stock-level total returns reveals a statistically significant 2.2 percent turn-of-the-year market return between 1874 and 1917, a period preceding income taxes and modern institutional investors in the U.S. The turn-of- he-year return is higher for small, growth and extreme winner and loser stocks. Our evidence implies that taxes cannot be the sole explanation for the turn-of-the-year effect. Either some form of window-dressing predates modern institutional investors, or other explanations for the anomaly must be sought.
Date: November 13, 2019
Time: 03:30 P.M.
Venue:
Seminar 2
Indian Statistical Institute Delhi Centre,
7, S. J. S. Sansanwal Marg,
New Delhi-110016 (INDIA)
Location:
View Larger Map
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