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Published on 1 November 2024
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Liu,C. (2024). Prediction of the Technology Stock Market in American: based on Apple, Microsoft and Netflix. Theoretical and Natural Science,51,26-33.
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Prediction of the Technology Stock Market in American: based on Apple, Microsoft and Netflix

Che Liu *,1,
  • 1 King's College London

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2753-8818/51/2024CH0148

Abstract

Stock market has been and will always be the central of the financial market. It is also a leading indicator of the economy react before the business cycle. Thus, predicted the trend of the stock market should be considered by market participants, policymakers and academicians. Simultaneously, technology stock market is gradually dominating the market. Under such a background, this paper will forecast the trend of the technology stock market based on a few technology companies, which are highly weighted in the technology industry, via the Autoregressive Integrated Moving Average (ARIMA) model. This study has successfully predicted the price of the technology stock market, which the predicted outcome is a close match to the actual price. The trend of the technology market analyzed by the ARIMA model with first order difference parameters, is going upward. The result represents American business cycle is undergoing a transition from contraction phase to recovery phase to some extent.

Keywords

Prediction, Technology stock market, Time series, ARIMA model.

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Cite this article

Liu,C. (2024). Prediction of the Technology Stock Market in American: based on Apple, Microsoft and Netflix. Theoretical and Natural Science,51,26-33.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of CONF-MPCS 2024 Workshop: Quantum Machine Learning: Bridging Quantum Physics and Computational Simulations

Conference website: https://2024.confmpcs.org/
ISBN:978-1-83558-653-2(Print) / 978-1-83558-654-9(Online)
Conference date: 9 August 2024
Editor:Anil Fernando, Marwan Omar
Series: Theoretical and Natural Science
Volume number: Vol.51
ISSN:2753-8818(Print) / 2753-8826(Online)

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