Volume- 8
Issue- 6
Year- 2021
DOI: 10.55524/ijirem.2021.8.6.154 | DOI URL: https://doi.org/10.55524/ijirem.2021.8.6.154
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)
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Satish Swankar
Stock market forecasting has long piqued the curiosity of analysts and academics. Stock markets, according to common thinking, are essentially random walks, and trying to predict them is a fool's game. Predicting stock prices is a tough endeavor in and of itself due to the many variables involved. In the short term, the market works like a voting machine, but in the long run, it works like a weighing machine, allowing for the prediction of market movements over a longer period of time. Machine learning and other algorithms may be used to assess and forecast stock values, and this is an area with a lot of promise. In this article, we begin with a quick review of stock markets and a taxonomy of stock market prediction approaches. The focus changes to some of the scientific achievements in stock analysis and forecasting after that. We go through stock analysis approaches such as technical, fundamental, short-term, and long-term. Finally, we go through some of the field's challenges and research opportunities.
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Assistant Professor, Department of Management Studies, Vivekananda Global University, Jaipur Email Id- satish.k@vgu.ac.in
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