Machine Learning Models for Stock Price Prediction
| Autor: | Amna Akram Sahib, Maha AlaaEddin, Ali Bou Nassif |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
business.industry
Computer science Feature extraction 020206 networking & telecommunications Statistical model 02 engineering and technology Machine learning computer.software_genre Investment (macroeconomics) Stock price Market research Linear regression 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business computer |
| Zdroj: | 2020 Seventh International Conference on Information Technology Trends (ITT). |
| DOI: | 10.1109/itt51279.2020.9320871 |
| Popis: | In 1950, there was a well-known investment data which was most generally used informational sets in the entirety of the applied econometrics in the United States called "Grunfeld investment data". The full dataset points out errors and inconsistencies in several currently available versions. The main goal of this paper is to use Machine Learning and Statistical models to clean up data and to predict the stock price using the Grunfeld investment data. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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