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Use of Artificial Intelligence in Stock Trading

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  • Chowdhury, Emon Kalyan

Abstract

Artificial Intelligence (AI) implies the imitation of human intelligence in machines that are programed to think like humans and replicate their actions. Stock trading means buying and selling of shares of a particular company. AI-based stock trading refers to buying and selling of shares using technology which is programed to act like human being and ensures more accuracy and speed. AI-based apparatuses are already in use to forecast stock market trends. AI not only analyzes data on the stock market, but can also predict stock market trends, trading patterns of investors, stock brokers and the market. Well-renowned companies on Wall Street such as Goldman Sachs and Morgan Stanley have started to focus on narrow AI solutions through data mining, natural language processing, and using self-learning algorithms tools, which are capable of interacting faster than our daily use applications like the Google Assistant of Android, Alexa of Amazon and Siri of Apple. It also helps wealth management companies to keep a constant control on the stock market movement and rebalance the portfolios to ensure the target profit. At present, AI can reduce the work load and save time by performing multiple tasks and provide real-time suggestions but it cannot remove the human involvement entirely.

Suggested Citation

  • Chowdhury, Emon Kalyan, 2019. "Use of Artificial Intelligence in Stock Trading," MPRA Paper 118175, University Library of Munich, Germany, revised 18 Apr 2019.
    • Handle: RePEc:pra:mprapa:118175
    as

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    File URL: https://mpra.ub.uni-muenchen.de/118175/1/Use%20of%20AI%20in%20Stock%20Trading.pdf
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    References listed on IDEAS

    as
    1. Andre Esteva & Brett Kuprel & Roberto A. Novoa & Justin Ko & Susan M. Swetter & Helen M. Blau & Sebastian Thrun, 2017. "Correction: Corrigendum: Dermatologist-level classification of skin cancer with deep neural networks," Nature, Nature, vol. 546(7660), pages 686-686, June.
    2. Emon Kalyan Chowdhury, 2022. "Disastrous consequence of coronavirus pandemic on the earning capacity of individuals: an emerging economy perspective," SN Business & Economics, Springer, vol. 2(10), pages 1-16, October.
    3. Emon Kalyan Chowdhury & Shafaitun Nahar, 2017. "Perceptions of Accountants toward Sustainability Development Practices in Bangladesh," Journal of Management and Sustainability, Canadian Center of Science and Education, vol. 7(3), pages 112-119, September.
    4. Andre Esteva & Brett Kuprel & Roberto A. Novoa & Justin Ko & Susan M. Swetter & Helen M. Blau & Sebastian Thrun, 2017. "Dermatologist-level classification of skin cancer with deep neural networks," Nature, Nature, vol. 542(7639), pages 115-118, February.
    5. Emon Kalyan Chowdhury, 2022. "Strategic approach to analyze the effect of Covid-19 on the stock market volatility and uncertainty: a first and second wave perspective," Journal of Capital Markets Studies, Emerald Group Publishing Limited, vol. 6(3), pages 225-241, October.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Artificial Intelligence; Stock; Finance; Trading; Forecasting;
    All these keywords.

    JEL classification:

    • A1 - General Economics and Teaching - - General Economics
    • A20 - General Economics and Teaching - - Economic Education and Teaching of Economics - - - General
    • D7 - Microeconomics - - Analysis of Collective Decision-Making
    • F0 - International Economics - - General
    • G0 - Financial Economics - - General

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