Adaptive market hypothesis and investor sentiments: global evidence

Abstract

PurposeThe purpose of this study is to investigate the adaptive market hypothesis (AMH) for 21 major global market indices for the period 1998–2018. These market indices cover the 16 largest global financial markets.Design/methodology/approachQuantile-regression methodology is employed to examine the market efficiency of a large number of financial markets from America, Europe and the Asia–Pacific region.FindingsThe results show that the returns in higher quantiles are negatively autocorrelated, and those in lower quantiles are positively autocorrelated. This evidence is stronger for the tails of return distribution. The positive autocorrelation (momentum effect) suggests market underreaction, and the negative autocorrelation (reversal effect) suggests overreaction. Overall, market efficiency appears to be time-varying and conditioned to the state of the market.Originality/valueThis study offers considerable evidence in favor of the AMH, for a large number of financial markets. These markets are substantially different from each other in terms of geography, nature of operation and size of the economy. The results from this study would be helpful to the academics, regulators and practitioners interested in financial markets.

Cryptocurrencies, gold, and WTI crude oil market efficiency: a dynamic analysis based on the adaptive market hypothesis

“…They concluded that Litecoin was the most efficient cryptocurrency, and Ripple was the least efficient one. Tripathi et al (2020) investigated the AMH for 21 major global market indices for 1998-2018. They employed quantile-regression methodology to scrutinize the market efficiency of 16 financial markets.…”

Adaptive Market Hypothesis and Return Predictability: A Hidden Markov Model Application in Borsa Istanbul

“…By applying the GARCH methodology, the AMH was specified as more useful than any other approach when explaining the evolving trend for the TOM effect. Tripathi et al (2020) applied quantile regression methodology to test the AMH in 21 major global market indices. Daily, weekly and monthly data were included in the analysis for the 1998-2018 period.…”

The efficiency of CO2 market in the phase III EU ETS: analyzing in the context of a dynamic approach

“…Generally, the findings support the AMH for the most well-established cryptocurrency market. Tripathi et al (2020) investigate the adaptive market hypothesis (AMH) for 21 major global market indices for 1998-2018. They employed quantile-regression methodology to scrutinize the market efficiency of 16 financial markets.…”