Articlegold2023

Financial stock market forecast using evaluated linear regression based machine learning technique

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Stock Market Forecasting Methods Financial Markets and Investment Strategies Forecasting Techniques and Applications

Abstract

The objective of Stock Market Forecasting (SMF) is to forecast the future value of a company's financial stocks. The availability of Machine Learning (ML), particularly obtains forecasts regarding specific prices of current stock market indexes through training on actual high economic value, constitutes a significant improvement in stock market prediction automation. ML itself utilizes a wide range of models to improve as well as evaluate prediction. Regarding the nonlinearities as well as discontinuities of the factors that are anticipated to effect stock markets, the selection of a modest price of global financial data is frequently acknowledged as a significant basic phase in any stock market prediction model. The fundamental emphasis of the study is the application of Evaluated Linear Regression based Machine Learning (ELR-ML) technique to forecast stock financial values of the Standard and Poor's 500 (s & p 500) index with Open, close, low, high, and volume factors.

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References

2021Machine learning in the Chinese stock market 2021The applications of artificial neural networks, support vector machines, and long–short term memory for stock market prediction 2022RETRACTED ARTICLE: An optimal deep learning-based LSTM for stock price prediction using twitter sentiment analysis 2022Machine Learning Approaches in Stock Price Prediction: A Systematic Review 2022Stock Market Prediction Using Microblogging Sentiment Analysis and Machine Learning 2021Multi-Model Generative Adversarial Network Hybrid Prediction Algorithm (MMGAN-HPA) for stock market prices prediction 2021An efficient equilibrium optimizer with support vector regression for stock market prediction

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