SSRN Author: Mark J. KamstraMark J. Kamstra SSRN Content
http://www.ssrn.com/author=77748
http://www.ssrn.com/rss/en-usSat, 16 Dec 2017 09:24:42 GMTeditor@ssrn.com (Editor)Sat, 16 Dec 2017 09:24:42 GMTwebmaster@ssrn.com (WebMaster)SSRN RSS Generator 1.0REVISION: Momentum, Reversals, and other Puzzles in Fama-MacBeth Cross-Sectional RegressionsThe existence of reversals and momentum in equity returns has challenged proponents of efficient markets for over 30 years. Although explanations for momentum profits based on cross-sectional mean return dispersion have been proposed, evidence of time-series autocorrelation from Fama-MacBeth cross-sectional regressions persists without any good risk/return explanation. In this paper I show that common implementations of the Fama-MacBeth procedure will yield upward biased estimates of time-series autocorrelation coefficients. Even in absence of autocorrelation, the bias is strictly positive, leading to apparent momentum when there is, in fact, none. This biased implementation of the Fama-MacBeth procedure has found its way into a great many other studies and may, similarly, lead to apparent effects when there are none. I outline conditions under which this bias occurs and prove the existence of bias under these conditions. I also provide a Monte Carlo simulation showing the magnitude ...
http://www.ssrn.com/abstract=2947340
http://www.ssrn.com/1651880.htmlThu, 14 Dec 2017 16:56:26 GMTREVISION: Momentum, Reversals, and other Puzzles in Fama-MacBeth Cross-Sectional RegressionsThe existence of reversals and momentum in equity returns has challenged proponents of efficient markets for over 30 years. Although explanations for momentum profits based on cross-sectional mean return dispersion have been proposed, evidence of time-series autocorrelation from Fama-MacBeth cross-sectional regressions persists without any good risk/return explanation. In this paper I show that common implementations of the Fama-MacBeth procedure will yield upward biased estimates of time-series autocorrelation coefficients. Even in absence of autocorrelation, the bias is strictly positive, leading to apparent momentum when there is, in fact, none. This biased implementation of the Fama-MacBeth procedure has found its way into a great many other studies and may, similarly, lead to apparent effects when there are none. I outline conditions under which this bias occurs and prove the existence of bias under these conditions. I also provide a Monte Carlo simulation showing the magnitude ...
http://www.ssrn.com/abstract=2947340
http://www.ssrn.com/1616159.htmlThu, 10 Aug 2017 07:42:32 GMTREVISION: Momentum, Reversals, and other Puzzles in Fama-MacBeth Cross-Sectional RegressionsThe existence of reversals and momentum in equity returns has challenged proponents of efficient markets for over 30 years. Although explanations for momentum profits based on cross-sectional mean return dispersion have been proposed, evidence of time-series autocorrelation from Fama-MacBeth cross-sectional regressions persists without any good risk/return explanation. In this paper I show that common implementations of the Fama-MacBeth procedure will yield upward biased estimates of time-series autocorrelation coefficients. Even in absence of autocorrelation, the bias is strictly positive, leading to apparent momentum when there is, in fact, none. This biased implementation of the Fama-MacBeth procedure has found its way into a great many other studies and may, similarly, lead to apparent effects when there are none. I outline conditions under which this bias occurs and prove the existence of bias under these conditions. I also provide a Monte Carlo simulation showing the magnitude ...
http://www.ssrn.com/abstract=2947340
http://www.ssrn.com/1606346.htmlSat, 08 Jul 2017 15:03:26 GMTREVISION: Momentum, Reversals, and Other Puzzles in Fama-Macbeth Cross-Sectional RegressionsThe existence of reversals and momentum in equity returns has challenged proponents of efficient markets for over 30 years. Although explanations for momentum profits based on cross-sectional mean return dispersion have been proposed, evidence of time-series autocorrelation from Fama-MacBeth cross-sectional regressions persists without any good risk/return explanation. In this paper I show that common implementations of the Fama-MacBeth procedure will yield upward biased estimates of time-series autocorrelation coefficients. Even in absence of autocorrelation, the bias is strictly positive, leading to apparent momentum when there is, in fact, none. This biased implementation of the Fama-MacBeth procedure has found its way into a great many other studies and may, similarly, lead to apparent effects when there are none. I outline conditions under which this bias occurs and prove the existence of bias under these conditions. I also provide a Monte Carlo simulation showing the magnitude ...
http://www.ssrn.com/abstract=2947340
http://www.ssrn.com/1583094.htmlSun, 16 Apr 2017 01:35:03 GMTREVISION: Momentum, Reversals, and Other Puzzles in Fama-Macbeth Cross-Sectional RegressionsThe existence of reversals and momentum in equity returns has challenged proponents of efficient markets for over 30 years. Although explanations for momentum profits based on cross-sectional mean return dispersion have been proposed, evidence of time-series autocorrelation from Fama-MacBeth cross-sectional regressions persists without any good risk/return explanation. In this paper I show that common implementations of the Fama-MacBeth procedure will yield upward biased estimates of time-series autocorrelation coefficients. Even in absence of autocorrelation, the bias is strictly positive, leading to apparent momentum when there is, in fact, none. This biased implementation of the Fama-MacBeth procedure has found its way into a great many other studies and may, similarly, lead to apparent effects when there are none. I outline conditions under which this bias occurs and prove the existence of bias under these conditions. I also provide a Monte Carlo simulation showing the magnitude ...
http://www.ssrn.com/abstract=2947340
http://www.ssrn.com/1581193.htmlSat, 08 Apr 2017 13:08:31 GMT