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A comparative study of Different Machine Learning Regressors For Stock Market Prediction

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  • Nazish Ashfaq
  • Zubair Nawaz
  • Muhammad Ilyas

Abstract

For the development of successful share trading strategies, forecasting the course of action of the stock market index is important. Effective prediction of closing stock prices could guarantee investors attractive benefits. Machine learning algorithms have the ability to process and forecast almost reliable closing prices for historical stock patterns. In this article, we intensively studied NASDAQ stock market and targeted to choose the portfolio of ten different companies belongs to different sectors. The objective is to compute opening price of next day stock using historical data. To fulfill this task nine different Machine Learning regressor applied on this data and evaluated using MSE and R2 as performance metric.

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  • Nazish Ashfaq & Zubair Nawaz & Muhammad Ilyas, 2021. "A comparative study of Different Machine Learning Regressors For Stock Market Prediction," Papers 2104.07469, arXiv.org.
    • Handle: RePEc:arx:papers:2104.07469
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    References listed on IDEAS

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    1. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
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