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The study examines the adaptive market hypothesis (AMH) as an evolutionary principle of the alternative efficient market hypothesis in the Indian stock market (Sensex and Nifty50) on the daily return from April 2014 to May 2020. Based on AMH, investors behave, learn, and adapt to market conditions. This distinction of dynamic market conditions is divided into bull and bear market classifications. We apply three variations of the variance ratio test and the returns have been whitened using the Autoregressive model with generalized autoregressive conditional heteroskedasticity (AR-GARCH) approach to examine the nonlinear predictability test. Further, we evaluate a fixed-length subsample window framework to detect the time-varying predictability and examine whether market conditions affect stock return predictability and market condition. The study confirms inefficient market behaviour during crises, fear, panic, macroeconomic events and each market adapts differently to certain market conditions. Furthermore, the return series exhibits significant periods of efficiency and inefficiency consistent with the adaptive market hypothesis. The evidence of our findings sheds light on efficient market behaviour in dynamic market conditions and market environments for researchers, investors in investment strategies and policy intervention in risk containment measures and control market manipulation.
Sing et al. (2024) studied this question.