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

• URL: http://arxiv.org/abs/2104.07469v1
• Date: Wed, 14 Apr 2021 15:37:33 GMT
• Title: A comparative study of Different Machine Learning Regressors For Stock Market Prediction
• Authors: Nazish Ashfaq, Zubair Nawaz, Muhammad Ilyas
• Abstract summary: We intensively studied NASDAQ stock market and targeted to choose the portfolio of ten different companies. 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.
• Score: 2.1485350418225244
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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