Alpha momentum and alpha reversal in country and industry equity indexes

Adam Zaremba , Mehmet Umutlu , Andreas Karathanasopoulos

Abstract

Do past alphas predict future country and industry returns? Examination of equity indexes from 51 stock markets between 1973 and 2018 allows us to demonstrate new return patterns in the cross-section of country and industry returns. Past short-term (long-term) alphas positively (negatively) predict future returns. These phenomena can be translated into effective international equity allocation strategies, producing economically and statistically significant raw and risk-adjusted returns. The profitability is robust to many considerations, including alternative alpha models, the role of trading costs, different holding periods, or subsample analyses. Furthermore, the alpha momentum subsumes its return-based counterpart.
Author Adam Zaremba (WZ / KIiRK)
Adam Zaremba,,
- Department of Investment and Capital Markets
, Mehmet Umutlu - Yasar University, Turkey
Mehmet Umutlu,,
-
, Andreas Karathanasopoulos - Dubai Business School, University of Dubai
Andreas Karathanasopoulos,,
-
Journal seriesJournal of Empirical Finance, ISSN 0927-5398, e-ISSN 1879-1727, (N/A 100 pkt)
Issue year2019
Vol53
Pages144-161
Publication size in sheets0.85
Keywords in Polishmomentum, międzynarodowe rynki finansowe, anomalie rynku kapitałowego
Keywords in EnglishAlpha momentum, Alpha reversal, International investment, Country momentum, Country reversal, Industry momentum, Industry reversal ,Asset pricing, The cross-section of returns return predictability, Equity anomalies
ASJC Classification2002 Economics and Econometrics; 2003 Finance
DOIDOI:10.1016/j.jempfin.2019.07.003
URL https://www.sciencedirect.com/science/article/abs/pii/S0927539819300581
Languageen angielski
Score (nominal)100
Score sourcejournalList
ScoreMinisterial score = 100.0, 08-04-2020, ArticleFromJournal
Publication indicators WoS Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2018 = 1.177; WoS Impact Factor: 2017 = 0.946 (2) - 2017=1.306 (5)
Citation count*4 (2020-08-03)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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