Stock Return Predictability from Moving Averages of Prices

48 Pages Posted: 16 Feb 2018 Last revised: 27 Nov 2019

See all articles by Doron Avramov

Doron Avramov

Interdisciplinary Center (IDC) Herzliyah

Guy Kaplanski

Bar-Ilan University - Graduate School of Business Administration

Avanidhar Subrahmanyam

University of California, Los Angeles (UCLA) - Finance Area; Institute of Global Finance, UNSW Business School; Financial Research Network (FIRN)

Date Written: May 22, 2018

Abstract

The distance between short- and long-run moving averages of prices (MAD) is strongly linked to future equity returns in the cross-section. Annualized alphas from the accompanying hedge portfolios are in the range of 9%-14%, and the predictability goes beyond momentum, 52-week highs, profitability, and other prominent anomalies. MAD-based investment payoffs easily survive reasonable trading costs. The predictability also applies at the aggregate market and industry levels. We also find that top MAD stocks are not markedly different from other stocks in terms of size or institutional holdings, and tend to be liquid and have higher turnover than other stocks.

Keywords: market efficiency, technical analysis, moving averages, crossing rules

JEL Classification: G12, G14

Suggested Citation

Avramov, Doron and Kaplanski, Guy and Subrahmanyam, Avanidhar, Stock Return Predictability from Moving Averages of Prices (May 22, 2018). Available at SSRN: https://ssrn.com/abstract=3111334 or http://dx.doi.org/10.2139/ssrn.3111334

Doron Avramov

Interdisciplinary Center (IDC) Herzliyah ( email )

P.O. Box 167
Herzliya, 46150
Israel

Guy Kaplanski

Bar-Ilan University - Graduate School of Business Administration ( email )

Ramat Gan
Israel

Avanidhar Subrahmanyam (Contact Author)

University of California, Los Angeles (UCLA) - Finance Area ( email )

Los Angeles, CA 90095-1481
United States
310-825-5355 (Phone)
310-206-5455 (Fax)

Institute of Global Finance, UNSW Business School

Sydney, NSW 2052
Australia

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

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