| Autor: |
Y Srividhya, CH Rajesh, K. Bhaskara Srinivas, G. Ramya Sanju Sree, S. Durga Prasad |
| Rok vydání: |
2023 |
| Zdroj: |
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT. |
| ISSN: |
2582-3930 |
| Popis: |
In the finance world stock trading is one of the most important activities. Stock market prediction is an act of trying to determine the future value of a stock other financial instrument traded on a financial exchange. The technical and fundamental or the time series analysis is used by the most of the stockbrokers while making the stock predictions. The programming language is used to predict the stock market using machine learning is Python. In this project the prediction of stock market is done by the Support Vector Machine (SVM). In the project, we proposed the use of the data collected from different global financial markets with machine learning algorithms in order to predict the stock index movements. SVM algorithm works on the large dataset value which is collected from different global financial markets. Various machine learning based models are proposed for predicting the daily trend of Market stocks. The model generates higher profit compared to the selected benchmarks. Keywords: Stock Market, Machine Learning, Predictions, Support Vector Machine. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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