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Analyzing Stock Market with Machine Learning Techniques

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Proceedings of International Conference on Recent Innovations in Computing (ICRIC 2022)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1011))

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Abstract

The financial market is extremely volatile, and this unstable nature of the stock market is not easy to understand. But technological advancements have given a ray of hope that it might be possible that one can make the machines understand this level of volatility and can make accurate predictions about the future market prices. This paper emphasizes various techniques by which machines can learn the financial markets and their future trends/movements. This paper has made use of four such techniques along with sentiment analysis on the news related to the undertaken tickers. This study shows that classification techniques give a good estimate of unusual highs and lows of the market, which in turn can prove helpful for the traders in taking timely and accurate decisions, i.e., bullish or bearish trends. This study is focused on determining the trends of the market while considering not only the stock trends but also the sentiments of the news headlines, using the polarity scores. The ensembled technique has given better results than other techniques in terms of R2 score and mean absolute error.

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Authors and Affiliations

  1. School of Computer Application, Lovely Professional University, Phagwara, Punjab, India

    Kirti Sharma & Rajni Bhalla

Authors
  1. Kirti Sharma
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  2. Rajni Bhalla
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Corresponding author

Correspondence to Kirti Sharma .

Editor information

Editors and Affiliations

  1. Central University of Jammu, Jammu, Jammu and Kashmir, India

    Yashwant Singh

  2. Department of Media and Educational Informatics, Faculty of Informatics, Eötvös Loránd University, Budapest, Hungary

    Chaman Verma

  3. Department of Media and Educational Informatics, Faculty of Informatics, Eötvös Loránd University, Budapest, Hungary

    Illés Zoltán

  4. Department of Computer Engineering, National Institute of Technology Kurukshetra, Kurukshetra, Haryana, India

    Jitender Kumar Chhabra

  5. KIET Group of Institutions, Ghaziabad, Uttar Pradesh, India

    Pradeep Kumar Singh

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Sharma, K., Bhalla, R. (2023). Analyzing Stock Market with Machine Learning Techniques. In: Singh, Y., Verma, C., Zoltán, I., Chhabra, J.K., Singh, P.K. (eds) Proceedings of International Conference on Recent Innovations in Computing. ICRIC 2022. Lecture Notes in Electrical Engineering, vol 1011. Springer, Singapore. https://doi.org/10.1007/978-981-99-0601-7_16

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  • DOI: https://doi.org/10.1007/978-981-99-0601-7_16

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-0600-0

  • Online ISBN: 978-981-99-0601-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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