| Autor: |
Kavitha, Mandala, Sai, M. Yaswanth, Arfeen, Md., Harrsha, K. Sri, Mamatha, S., Bajpayee, Shrinidhi Umesh |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2023, Vol. 2796 Issue 1, p1-8, 8p |
| Abstrakt: |
Due to the overall continual flow of news, announcements, worldwide data points, and so on, stocks are volatile and unpredictable. This is affected by market volatility and a variety of other variables in the research, both independent and dependent, that impact the stocks' market˘ value. These variables make it difficult for a stock market expert to precisely predicts the market's peaks and troughs. The major purpose of this essay is to anticipate market stock stability in the future. The studyafocuses˘ on the use of two approaches, gradient boosted decision trees (using XG Boost) and random forests, to forecast whether stock values will rise or fall over the following n days. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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