Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

Browse

Filters

20201

Settings

Author: search.filters.author.Bhat, S.S.Subject: search.filters.subject.Deep learning

Search Results

Now showing 1 - 1 of 1
  • No Thumbnail Available
    Item
    A TFD Approach to Stock Price Prediction
    (Springer, 2020) Chanduka, B.; Bhat, S.S.; Rajput, N.; Mohan, B.R.
    Accurate 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.