TY - GEN
T1 - Share price prediction of Indian Stock Markets using timeseries data-A Deep Learning Approach
AU - Raviraj, Shravan
AU - Manohara Pai, M. M.
AU - Pai, Krithika M.
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Stock markets form the largest avenues of investment in India primarily through two stock exchanges: Bombay Stock Exchange(BSE) and National Stock Exchange(NSE). Analysts and investors look into various factors and try to predict the trends in stock prices in these exchanges. Being extremely volatile in nature, share price prediction is a fairly complex task. Despite the abundance of data, technology has not been able to carry out right predictions up to a desired accuracy most of the time. The recent developments in deep learning technology have proven to be a useful resource in improving the accuracy of predictions. The proposed deep learning based prediction algorithms makes use of Recurrent Neural Network, Long Short Term Memory and Gated Recurrent Unit over time series data obtained online. The developed algorithms predicts the trends five days in advance. The results of the prediction on stocks from various industries are explored to derive valuable insights.
AB - Stock markets form the largest avenues of investment in India primarily through two stock exchanges: Bombay Stock Exchange(BSE) and National Stock Exchange(NSE). Analysts and investors look into various factors and try to predict the trends in stock prices in these exchanges. Being extremely volatile in nature, share price prediction is a fairly complex task. Despite the abundance of data, technology has not been able to carry out right predictions up to a desired accuracy most of the time. The recent developments in deep learning technology have proven to be a useful resource in improving the accuracy of predictions. The proposed deep learning based prediction algorithms makes use of Recurrent Neural Network, Long Short Term Memory and Gated Recurrent Unit over time series data obtained online. The developed algorithms predicts the trends five days in advance. The results of the prediction on stocks from various industries are explored to derive valuable insights.
UR - http://www.scopus.com/inward/record.url?scp=85123835579&partnerID=8YFLogxK
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U2 - 10.1109/MysuruCon52639.2021.9641726
DO - 10.1109/MysuruCon52639.2021.9641726
M3 - Conference contribution
AN - SCOPUS:85123835579
T3 - 2021 IEEE Mysore Sub Section International Conference, MysuruCon 2021
SP - 744
EP - 751
BT - 2021 IEEE Mysore Sub Section International Conference, MysuruCon 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1st IEEE Mysore Sub Section International Conference, MysuruCon 2021
Y2 - 24 October 2021 through 25 October 2021
ER -