Unveiling the Global Predictive Power of Moving Average Distance in Market Timing (Part II)

As financial markets traverse borders, the quest for predictive indicators transcends national boundaries. In December 2023, groundbreaking research by Menachem (Meni) Abudy, Guy Kaplanski, and Yevgeny Mugerman illuminates an intriguing avenue — the use of Moving Average Distance (MAD) to forecast future returns of international market-wide indices.

The essence of this study lies in exploring MAD’s efficacy in predicting returns across 92 international market-wide indices. While prior research had primarily focused on MAD as a predictor for U.S. stock returns, this study extends its scope, delving into the global landscape of market indices.

Avramov et al.’s seminal work in 2021 introduced MAD as a potent predictor for U.S. stock returns. The rationale behind MAD’s predictability was attributed to investor behavior anchored in long-run moving averages of stock prices. However, the question remained: would this hold true in the context of market-wide indices and international settings?

The study presents compelling evidence that indeed, MAD predicts future returns of international market indices. The portfolios crafted based on MAD not only yield abnormal profits but importantly, these profits sustain themselves over time. This phenomenon suggests a global tendency of investors to underreact to information, lending credence to the anchoring explanation for MAD’s predictive power.