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Advances in Data Computing, Communication and Security pp 157–168Cite as

Stock Market Analysis of Beauty Industry During COVID-19

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Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT,volume 106)

Abstract

COVID-19 has significant influence on the financial market. This paper aimed to explore the COVID-19 scenario analysis for stock market of beauty industry. Stock data of Estée Lauder Companies (EL), Revlon Inc. (REV) and Coty Inc. (COTY) is considered for this purpose. Deep learning models (LSTM and CNN) are utilized for the stock price prediction of beauty companies during COVID-19 era. LSTM and CNN, both the model worked well for the stock price prediction; however, LSTM performed better in all cases. Lockdown scenario along with the stock data is taken for the analysis purpose. Study shows that beauty industries got affected during initial spread of the virus, but now recovering.

Keywords

  • COVID-19
  • Stock market
  • Beauty industry
  • Deep learning
  • LSTM
  • CNN

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Authors and Affiliations

  1. Department of Information Technology, National Institute of Technology, Raipur, India

    Satya Verma, Satya Prakash Sahu & Tirath Prasad Sahu

Authors
  1. Satya Verma
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  2. Satya Prakash Sahu
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  3. Tirath Prasad Sahu
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Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, National Institute of Technology, Kurukshetra, Kurukshetra, India

    Dr. Pankaj Verma

  2. Department of Electronics and Communication Engineering, National Institute of Technology, Kurukshetra, Kurukshetra, India

    Dr. Chhagan Charan

  3. Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada

    Prof. Xavier Fernando

  4. Department of Electrical and Computer Engineering, Oakland University, Rochester, MI, USA

    Dr. Subramaniam Ganesan

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Verma, S., Sahu, S.P., Sahu, T.P. (2022). Stock Market Analysis of Beauty Industry During COVID-19. In: Verma, P., Charan, C., Fernando, X., Ganesan, S. (eds) Advances in Data Computing, Communication and Security. Lecture Notes on Data Engineering and Communications Technologies, vol 106. Springer, Singapore. https://doi.org/10.1007/978-981-16-8403-6_14

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