The Impact of Financial Statement Integration in Machine Learning for Stock Price Prediction

Автор: Febrian Wahyu Christanto, Victor Gayuh Utomo, Rastri Prathivi, Christine Dewi

Журнал: International Journal of Information Technology and Computer Science @ijitcs

Статья в выпуске: 1 Vol. 16, 2024 года.

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In the capital market, there are two methods used by investors to make stock price predictions, namely fundamental analysis, and technical analysis. In computer science, it is possible to make prediction, including stock price prediction, use Machine Learning (ML). While there is research result that said both fundamental and technical parameter should give an optimum prediction there is lack of confirmation in Machine Learning to this result. This research conducts experi-ment using Support Vector Regression (SVR) and Support Vector Machine (SVM) as ML method to predict stock price. Further, the result is compared between 3 groups of parameters, technical only (TEC), financial statement only (FIN) and combination of both (COM). Our experimental results show that integrating financial statements has a neutral impact on SVR predictions but a positive impact on SVM predictions and the accuracy value of the model in this research reached 83%.

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Stock Prediction, Technical Analysis, Financial Statement, Support Vector Regression

Короткий адрес: https://sciup.org/15018963

IDR: 15018963 | DOI: 10.5815/ijitcs.2024.01.04

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