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The only significant predictor of the ultimate outcome, in particular, should be the most recent observed value ( Richard and Vecer 2021). Another model that challenges EMH is Paul Samuelson’s martingale model ( Samuelson 1973), according to which, given all available information, current prices are the best predictors of an event’s outcome. Whereas according to the random walk theory, stock prices conduct a ‘random walk’, which means that all future prices do not follow any trends or patterns, and are a spontaneous deviation from previous prices, and an investor cannot possibly forecast the market ( Cheng and Deets 1971 Van Horne and Parker 1967). Since market participants optimally use all known information, price fluctuations are unpredictable, as new information happens randomly ( Fama 1970). EMH states that a stock price absorbs all known market knowledge at any time. There are two traditional theories to take into account when estimating the stock price, namely, efficient market hypotheses (EMH) and random walk (RW) theory. We conclude by establishing a research agenda for potential financial market analysts, artificial intelligence, and soft computing scholarship. Our findings highlight that AI techniques can be used successfully to study and analyze stock market activity. We group the surveyed articles based on two major categories, namely, study characteristics and model characteristics, where ‘study characteristics’ are further categorized as the stock market covered, input data, and nature of the study and ‘model characteristics’ are classified as data pre-processing, artificial intelligence technique, training algorithm, and performance measure. This paper reviews 148 studies utilizing neural and hybrid-neuro techniques to predict stock markets, categorized based on 43 auto-coded themes obtained using NVivo 12 software. Artificial intelligence (AI) techniques can detect such non-linearity, resulting in much-improved forecast results. The stock market is characterized by extreme fluctuations, non-linearity, and shifts in internal and external environmental variables.