Abstract
A stock market, sometimes referred to as an equity market, is a gathering of buyers and sellers of stocks that represent company ownership. In this market, various investors sell and acquire shares based on stock availability. Stock trading is an important practice in the world of finance, and it is the cornerstone of many enterprises. A developing country’s rapid economic development, such as India’s, is dependent on its stock market. It is crucial in today’s economic and social environment. The stock market’s ups and downs have an impact on stakeholders’ benefits. Stock market value prediction has long captivated the interest of investors and researchers because of its complexity, inherent ambiguity, and ever-changing nature. “Stock market prediction” is a method of trying to anticipate the worth of a given “stock” in the coming days. This is performed by considering historical stock values as well as price variances throughout the previous days. Due to market volatility, forecasting stock indices is definitely tough, necessitating an accurate forecast model. Recent advancement in stock market prediction technology is machine learning, which produces forecasts based on the values of current stock market indices by training on their prior values. The term “machine learning” (ML) refers to a subdivision of “artificial intelligence” (AI) in which we train machines with data and use test data to forecast the future. This study presents an overview of deep learning techniques that are currently being used to anticipate stock market movements and predictions.
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Raj, P., Ashu Mehta, Singh, B. (2023). Stock Market Prediction Using Deep Learning Algorithm: An Overview. In: Gupta, D., Khanna, A., Bhattacharyya, S., Hassanien, A.E., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. Lecture Notes in Networks and Systems, vol 471. Springer, Singapore. https://doi.org/10.1007/978-981-19-2535-1_25
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