Stock Price Prediction Using the ARIMA Model
University of KwaZulu-Natal · Covenant University
Abstract
Stock price prediction is an important topic in finance and economics which has spurred the interest of researchers over the years to develop better predictive models. The autoregressive integrated moving average (ARIMA) models have been explored in literature for time series prediction. This paper presents extensive process of building stock price predictive model using the ARIMA model. Published stock data obtained from New York Stock Exchange (NYSE) and Nigeria Stock Exchange (NSE) are used with stock price predictive model developed. Results obtained revealed that the ARIMA model has a strong potential for short-term prediction and can compete favourably with existing techniques for stock price prediction.
Citation impact
- FWCI
- 10.92
- Percentile
- 100%
- References
- 18
Authors
3- AAAdebiyi A. AriyoCorresponding
University of KwaZulu-Natal
- AOAderemi O. Adewumi
University of KwaZulu-Natal
- CKC. K. Ayo
Covenant University
Topics & keywords
- Autoregressive integrated moving average
- Stock exchange
- Econometrics
- Stock (firearms)
- Autoregressive model
- Stock price
- Time series
- Computer science