Market Adaptability and Evolving Predictability of Stock Returns: An Evidence from India
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Market Adaptability and Evolving Predictability of Stock Returns: An Evidence from India Biswabhusan Bhuyan1 · Subhamitra Patra1 · Ranjan Kumar Bhuian2
© Springer Japan KK, part of Springer Nature 2020
Abstract This study attempts to examine the adaptive market hypothesis and evolving predictability of stock returns using four decades of daily data from the Bombay Stock Exchange (BSE) and the National Stock Exchange (NSE) in India. The recent developed automatic portmanteau ratio (AVR) and wild bootstrap automatic variance ratio (WAVR) test are used for analysis. We also estimate both the AVR and WAVR statistics in the rolling window framework to examine evolving predictability. The results revealed that BSE and NSE are informationally inefficient in the weakform. The results of rolling window analysis suggested that the degree of predictable patterns evolves over the period due to global and regional economic and noneconomic events. Further, the study compare which stock market is more efficient and found that NSE is more efficient than BSE. The findings of this study provide essential inputs to investors on trading strategies in dynamic economic situations and policymakers to formulate an appropriate policy that can make the Indian stock markets efficient. Keywords Informational efficiency · Adaptive market hypothesis · Emerging stock markets · Financial crises JEL Classifications G14 · G4 · G10 · G01
* Subhamitra Patra [email protected] Biswabhusan Bhuyan [email protected] Ranjan Kumar Bhuian [email protected] 1
Department of Humanities and Social Sciences, Indian Institute of Technology Kharagpur, Kharagpur 721302, West Bengal, India
2
North Orissa University, Baripada 757003, Odisha, India
13
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B. Bhuyan et al.
1 Introduction A large body of scientific literature has been dedicated to testing the essence of the efficient market hypothesis (EMH), which asserts the uncorrelated patterns of the securities returns from its past performance. The absence of autocorrelation between the distance observations makes the security prices unpredictable, and therefore allows the market to follow the random-walk benchmark. But, the continuous occurrences of the dynamic economic events namely bubble, crashes, panics, manias, and reforms, prompted a group of researchers to question such static functioning of the market. Moreover, the changing characteristics of the market microstructure on the eve of the dynamic economic situations make the information costlier, demotivate the market participants to acquire such costly information, and thus depart the market from the random-walk benchmark (Grossman and Stiglitz 1980). Thus, a convincing theory explaining the formal departures from the random-walk and the factors for the evolving predictability of the security returns is essential to understand the time-varying nature of the market efficiency. Lo (2004) proposes an alternative theory, namely the adaptive market hypothesis (AMH), which analyses the market functioning f
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