Abstract
Stock market is a correlated entanglement of companies whose prices depend upon various factors including how well each individual company is doing, their stock’s performance and the general trend of the stock market. A simple linear prediction based upon the past performances of the stock is not enough to declare whether a particular stock will perform in a linear way. To predict the behavior of stocks, it is required to look at all of its correlated counterparts, compile their performance numbers and take a logical guess on whether the stock’s performance will be on the positive side or on the negative side. For that measure, data of all the stocks from Standard and Poor’s 500 Ratings (S&P 500) was collected. The novel idea in this paper is to classify a stock’s performance based upon its correlated features and predict that whether it should be bought, sold, or held.
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Tomer, M., Anand, V., Shandilya, R., Tiwari, S. (2021). Classification of S&P 500 Stocks Based on Correlating Market Trends. In: Bansal, P., Tushir, M., Balas, V., Srivastava, R. (eds) Proceedings of International Conference on Artificial Intelligence and Applications. Advances in Intelligent Systems and Computing, vol 1164. Springer, Singapore. https://doi.org/10.1007/978-981-15-4992-2_26
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DOI: https://doi.org/10.1007/978-981-15-4992-2_26
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