Abstract
The most important aspect of the stock market is finding a stock in which anyone can put their money with confidence. Most traders these days do not know where to invest or on what premise to put their money. In this work, we created a strategy that assists traders in deciding whether or not to put their money in a specific stock. This method is being developed by leveraging long short-term memory (LSTM) in machine learning to anticipate stock performance based on prior data from the firm.
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References
Ican O, Celik TB (2017) Stock market prediction performance of neural networks: a literature review. Int J Econ Financ 9(11):100–108
Deepak RS, Uday SI, Malathi D (2017) Machine learning approach in stock market prediction. Int J Pure Appl Math 115(8):71–77
Reddy VKS (2018) Stock market prediction using machine learning. Int Res J Eng Technol (IRJET) 5(10):1033–1035
Pathak A, Shetty NP (2017) Indian stock market prediction using machine learning and sentiment analysis. Department of Information and Communication Technology. In: Research output: chapter in book/report/conference proceeding conference contribution, Manipal institute of technology, Manipal
Singh A (2018) Stock prices prediction using machine learning and deep learning techniques (with Python codes). Anal Vidhya
Rajamani P (2020) Price suggestion and price prediction algorithms, Int J Adv Sci Technol 29(8):2576–2582
Bhardwaj N, Ansari MA (2019) Prediction of stock market using machine learning algorithms. Int Res J Eng Technol (IRJET) 6(5)
Shen J, Shafiq MO (2020) Short-term stock market price trend prediction using a comprehensive deep learning system. J Big Data 7:66
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Boosi, S., Tukkoji, C., Nadhan, A.S., Ruby, A.U. (2023). Stock Price Analysis Using LSTM. In: Dutta, P., Chakrabarti, S., Bhattacharya, A., Dutta, S., Piuri, V. (eds) Emerging Technologies in Data Mining and Information Security. Lecture Notes in Networks and Systems, vol 491. Springer, Singapore. https://doi.org/10.1007/978-981-19-4193-1_72
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DOI: https://doi.org/10.1007/978-981-19-4193-1_72
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