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학술논문

A Prediction of Stock Price Movements Using Support Vector Machines in Indonesia

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영문명
발행기관
한국유통과학회
저자명
Ervandio Irzky ARDYANTA Hasrini SARI
간행물 정보
『The Journal of Asian Finance, Economics and Business(JAFEB)』Vol. 8 No.8, 399~407쪽, 전체 9쪽
주제분류
경제경영 > 경제학
파일형태
PDF
발행일자
2021.08.30
무료

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국문 초록

영문 초록

Stock movement is difficult to predict because it has dynamic characteristics and is influenced by many factors. Even so, there are some approaches to predict stock price movements, namely technical analysis, fundamental analysis, and sentiment analysis. Many researches have tried to predict stock price movement by utilizing these analysis techniques. However, the results obtained are varied and inconsistent depending on the variables and object used. This is because stock price movement is influenced by a variety of factors, and it is likely that those studies did not cover all of them. One of which is that no research considers the use of fundamental analysis in terms of currency exchange rates and the use of foreign stock price index movement related to the technical analysis. This research aims to predict stock price movements in Indonesia based on sentiment analysis, technical analysis, and fundamental analysis using Support Vector Machine. The result obtained has a prediction accuracy rate of 65,33% on an average. The inclusion of currency exchange rate and foreign stock price index movement as a predictor in this research which can increase average prediction accuracy rate by 11.78% compared to the prediction without using these two variables which only results in average prediction accuracy rate of 53.55%.

목차

1. Introduction
2. Literature Review
3. Methodology
4. Results and Discussion
5. Conclusion

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APA

Ervandio Irzky ARDYANTA,Hasrini SARI. (2021).A Prediction of Stock Price Movements Using Support Vector Machines in Indonesia. The Journal of Asian Finance, Economics and Business(JAFEB), 8 (8), 399-407

MLA

Ervandio Irzky ARDYANTA,Hasrini SARI. "A Prediction of Stock Price Movements Using Support Vector Machines in Indonesia." The Journal of Asian Finance, Economics and Business(JAFEB), 8.8(2021): 399-407

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