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 weak-form. The results of rolling window analysis suggested that the degree of predictable patterns evolves over the period due to global and regional economic and non-economic 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.

这项研究试图使用来自印度孟买证券交易所（BSE）和国家证券交易所（NSE）的四十年的每日数据来检验适应性市场假说和不断发展的股票收益可预测性。使用最新开发的自动Portmanteau比率（AVR）和野生自举自动方差比率（WAVR）测试进行分析。我们还估计滚动窗口框架中的AVR和WAVR统计信息，以检查不断发展的可预测性。结果表明，BSE和NSE在弱形式中信息效率低下。滚动窗口分析的结果表明，由于全球和区域经济和非经济事件的影响，可预测模式的程度在此期间有所发展。此外，该研究比较了哪个股票市场更有效，并发现NSE比BSE更有效。