Chanduka B.Bhat S.S.Rajput N.Mohan B.R.2021-05-052021-05-052020Advances in Intelligent Systems and Computing , Vol. 1034 , , p. 635 - 644https://doi.org/10.1007/978-981-15-1084-7_61https://idr.nitk.ac.in/handle/123456789/15054Accurate stock price predictions can help investors take correct decisions about the selling/purchase of stocks. With improvements in data analysis and deep learning algorithms, a variety of approaches has been tried for predicting stock prices. In this paper, we deal with the prediction of stock prices for automobile companies using a novel TFD—Time Series, Financial Ratios, and Deep Learning approach. We then study the results over multiple activation functions for multiple companies and reinforce the viability of the proposed algorithm. © 2020, Springer Nature Singapore Pte Ltd.Conference Paper