Stock Closing Price Prediction using Machine Learning Techniques
Jaypee Institute of Information Technology · National Institute of Technology Rourkela
Abstract
Accurate prediction of stock market returns is a very challenging task due to volatile and non-linear nature of the financial stock markets. With the introduction of artificial intelligence and increased computational capabilities, programmed methods of prediction have proved to be more efficient in predicting stock prices. In this work, Artificial Neural Network and Random Forest techniques have been utilized for predicting the next day closing price for five companies belonging to different sectors of operation. The financial data: Open, High, Low and Close prices of stock are used for creating new variables which are used as inputs to the model. The models are evaluated using standard strategic indicators:…
Citation impact
- FWCI
- 59.11
- Percentile
- 100%
- References
- 27
Authors
4Topics & keywords
- Computer science
- Closing (real estate)
- Stock (firearms)
- Artificial neural network
- Random forest
- Stock market
- Econometrics
- Stock price
- Life in Land