Prediction of Cathay Pacific Airways Stock Price via Time Series Model for Year 2023 and 2024
DOI:
https://doi.org/10.54691/bcpbm.v21i.1196Keywords:
ACF, ARIMA, Forecast, PACF, Stationary, Time SeriesAbstract
This essay explains and demonstrates the prediction of the future trend of the stock of Cathay Pacific Airways Limited in the following two years using time series model. In order to correct the stationary of the primary data, the p-value in Augmented Dickey-Fuller test is used to check whether the model is stationary. After that, auto-correlation function (ACF) and partial auto-correlation function (PACF) which gives the lagged values from different series and find correlation of the residuals with the next lag value. Finally, use Autoregressive Integrated Moving Average model to function the corrected model to test which is the best fitted model. Afterwards, forecasting the confidence interval and the specific fluctuations by the best ARIMA model. The result doesn’t show the actual stock price in the future time, the forecasting model, however, only shows the trend of its stock price. The results of the modelling and analysis are presented such that can be used as a study to the prediction of any non-stationary data.
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