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Automated passive income from stock market using machine learning and big data analytics with security aspects

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Abstract

Digital data has grown dramatically with the development of big data, the Internet of Things, and machine learning. In many different fields, high-performance computers are utilised to handle and process such a massive amount of data. In the financial capital market, which includes stocks, bonds, commodities, foreign currency, and cryptocurrencies, supercomputers essentially trade securities with sophisticated algorithms and excellent processing power. Big capitalizing financial institutions invest a lot of money in data analysts and programmers to create the highest accuracy trading algorithms that will propel the market as a whole. Finding profitable trades or stocks to spend their hard-earned money in over a short- to long-term time frame can be challenging for a newbie trader or investor with little to no expertise in the financial markets. They can suffer significant losses when they rely on professional guidance for investment recommendations. This paper focuses on creating a universal trend trading indicator capable of analysing and forecasting the overall future trend of any stock, bond, commodity, FX, or cryptocurrency with the highest possible profit. A colossal dataset of historically traded stock prices and investment reports from large financial institutions worldwide is compiled. Various machine learning and decision-making models are used for technical and fundamental analysis across numerous securities. The output of the trend trading indicator is displayed on charting platforms, which can provide entry-exit levels at which even novice investors can decide where to invest their money. Multi-timeframe analysis is deployed to predict short-term, medium-term, and long-term overall trends, thus increasing the output accuracy. The indicator is helpful for all types of retail traders and investors worldwide who struggle to benefit from financial markets. Our proposed approach generated annual profits of 86.28%. The entire system, including trading orders, is automated, allowing anyone to create additional passive income from the stock market every month.

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Authors and Affiliations

  1. University of Hertfordshire, Hatfield, UK

    Gaurav Sharma & Stilianos Vidalis

  2. ABV-Indian Institute of Information Technology & Management, Gwalior, India

    P. Mankar & Somesh Kumar

  3. Indian Institute of Information Technology Lucknow (IIITL), Lucknow, India

    Niharika Anand

  4. Madhav Institute of Technology and Science (MITS), Gwalior, India

    Minakshi

Authors
  1. Gaurav Sharma
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  2. Stilianos Vidalis
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  3. P. Mankar
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  4. Niharika Anand
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  5. Minakshi
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  6. Somesh Kumar
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Correspondence to Niharika Anand.

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Sharma, G., Vidalis, S., Mankar, P. et al. Automated passive income from stock market using machine learning and big data analytics with security aspects. Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-024-19340-3

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  • DOI: https://doi.org/10.1007/s11042-024-19340-3

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