Stock Price Prediction Using the ARIMA Model

Прогнозирование цены акций с использованием модели ARIMA
Ayodele A. Adebiyi, Aderemi O. Adewumi, C. K. Ayo, Adebiyi A. Ariyo
2014-03-01

ARIMANew York Stock Exchange (NYSE)autoregressive integrated moving averagestock price predictiontime series prediction
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.
1
ARIMA-based predictions can compete favourably with existing stock price prediction techniques according to the obtained results.
2
Results indicate ARIMA has strong potential for short-term stock price prediction.
3
The paper develops a stock price predictive model using the ARIMA framework applied to NYSE and NSE historical data.

Stock price time series from NYSE and NSE

Short-term prediction performance of ARIMA models for stock prices

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Publication Date
2014-03-01
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Authors
Ayodele A. Adebiyi
Aderemi O. Adewumi
C. K. Ayo
Adebiyi A. Ariyo
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