Abstract
The Stock market is a key player in determining the financial facet of any nation’s growth. The stock market is predominantly driven by the companies whose stocks rise and fall depending on various parameters, thus making it volatile and complex in nature. The need of stock market analysis is driven by the huge demand to predict stock prices so as to facilitate the investors in selecting the best trading chance accurately in advance, thereby bringing in high profit. The dynamic time warping algorithm (DTW) is used to explore the best investment strategy using technical indicators and predict the stock price based on the same. DTW is used for stock market prediction because it measures similarities among various market patterns and offers investment strategies using technical indicators.
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Arya, M.S., Deepa, R., Gandhi, J. (2021). Dynamic Time Warping-Based Technique for Predictive Analysis in Stock Market. In: Mahapatra, R.P., Panigrahi, B.K., Kaushik, B.K., Roy, S. (eds) Proceedings of 6th International Conference on Recent Trends in Computing. Lecture Notes in Networks and Systems, vol 177. Springer, Singapore. https://doi.org/10.1007/978-981-33-4501-0_3
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DOI: https://doi.org/10.1007/978-981-33-4501-0_3
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