Prediction of stock market trends is considered as an important task and is of great attention as predicting stock prices successfully may lead to attractive profits by making proper decisions. Stock market prediction is a major challenge owing to non-stationary, blaring, and chaotic data, and thus, the prediction becomes challenging among the investors to invest the money for making profits. Several techniques are devised in the existing techniques to predict the stock market trends. This work presents the detailed review of 50 research papers suggesting the methodologies, like Bayesian model, Fuzzy classifier, Artificial Neural Networks (ANN), Support Vector Machine (SVM) classifier, Neural Network (NN), Machine Learning Methods and so on, based on stock market prediction. The obtained papers are classified based on different prediction and clustering techniques. The research gaps and the challenges faced by the existing techniques are listed and elaborated, which help the researchers to upgrade the future works. The works are analyzed using certain datasets, software tools, performance evaluation measures, prediction techniques utilized, and performance attained by different techniques. The commonly used technique for attaining effective stock market prediction is ANN and the fuzzy-based technique. Even though a lot of research efforts, the current stock market prediction technique still have many limits. From this survey, it can be concluded that the stock market prediction is a very complex task, and different factors should be considered for predicting the future of the market more accurately and efficiently.

预测股票市场趋势被认为是一项重要的任务，因此备受关注，因为成功预测股票价格可能会通过做出正确的决策而带来可观的利润。由于不稳定的数据，混乱的数据和混乱的数据，股票市场的预测是一个重大挑战，因此，在投资者中进行投资以赚钱的预测变得越来越具有挑战性。现有技术中设计了几种技术来预测股市趋势。这项工作详细介绍了50篇研究论文，提出了基于贝叶斯模型，模糊分类器，人工神经网络（ANN），支持向量机（SVM）分类器，神经网络（NN），机器学习方法等的方法论。关于股市预测。根据不同的预测和聚类技术对获得的论文进行分类。列举并阐述了现有技术所面临的研究空白和面临的挑战，这有助于研究人员升级未来的工作。使用某些数据集，软件工具，性能评估方法，使用的预测技术以及通过不同技术获得的性能来分析作品。获得有效的股票市场预测的常用技术是ANN和基于模糊的技术。即使进行了大量的研究工作，当前的股市预测技术仍然有很多局限性。从调查中可以得出结论，股票市场预测是一项非常复杂的任务，应考虑各种因素来更准确，更有效地预测市场的未来。