Forecasting Cameco Corporation Monthly Stock Price Using ARIMA Model

Kenrick Saputra Tedja, Edwin Setiawan Nugraha

Abstract


This paper forecasts the monthly stock price of Cameco Corporation using data sourced from Yahoo Finance, spanning from May 2018 to April 2023. The Autoregressive Integrated Moving Average (ARIMA) method is employed to predict the company's stock price. Among various models, ARIMA (2, 1, 2) is selected due to its lowest Akaike Information Criterion (AIC). The model forecasts the stock price based on historical data, achieving an error rate of 7.79903%, equivalent to an accuracy of 92.20097%, which is considered very good. This forecast provides investors with valuable insights into the future stock price.

Keywords


ARIMA; forecasting; stock price; uranium production

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References


Cameco, "History," Cameco, [Online]. Available: https://www.cameco.com/about/history.

World Nuclear Association, "World Uranium Mining Production," 16 May 2024. [Online]. Available: https://www.world-nuclear.org/information-library/nuclear-fuel-cycle/mining-of-uranium/world-uranium-mining-production.aspx.

World Nuclear Association, "Uranium Market," 16 May 2024. [Online]. Available: https://world-nuclear.org/information-library/nuclear-fuel-cycle/uranium-resources/uranium-markets.aspx.

K. Deka and A. Kumar, "Westinghouse to be sold in $7.9-bln deal as interest in nuclear power grows," Reuters, 12 October 2022. [Online]. Available: https://www.reuters.com/markets/deals/cameco-corp-brookfield-renewable-partners-buy-westinghouse-79-bln-deal-2022-10-11/.

Fuqua School of Business, "Introduction to ARIMA Models," [Online]. Available: https://people.duke.edu/~rnau/411arim.htm.

P. Mondal, L. Shit and S. Goswami, "Study of Effectiveness of Time Series Modeling (ARIMA) in Forecasting Stock Prices," International Journal of Computer Science, Engineering and Applications, vol. 4, no. 2, pp. 13-29, 2014.

S. Khan and H. Alghulaiakh, "ARIMA Model for Accurate Time Series Stocks Forecasting," International Journal of Advanced Computer Science and Applications, vol. 11, no. 7, pp. 524-528, 2020.

Australian Bureau of Statistics, "Time Series Analysis: The Basics," Australian Bureau of Statistics, 1 March 2023. [Online]. Available: https://www.abs.gov.au/websitedbs/d3310114.nsf/home/time+series+analysis:+the+basics.

A. Dotis-Georgiu, "An introduction to time series forecasting," InfoWorld, 22 July 2021. [Online]. Available: https://www.infoworld.com/article/3622246/an-introduction-to-time-series-forecasting.html.

A. Yunishafira, "Determining the Appropriate Demand Forecasting Using Time Series Method: Study Case at Garment Industry in Indonesia," in International Conference on Economics, Business and Economic Education 2018 (ICE-BEES 2018), Semarang, 2018.

Y. Tingqing and Y. Xiangfeng, "Analysis and prediction of confirmed COVID-19 cases in China with uncertain time series," Fuzzy Optimization and Decision Making, vol. 20, pp. 209-228, 2021.

J. D. Hamilton, Time Series Analysis, 1 ed., Princeton: Princeton University Press, 1994, pp. 44-46.

R. J. Hyndman and G. Athanasopoulos, Forecasting: Principles and Practice, Melbourne: Otexts, 2021.

PennState Eberly College of Science, "10.2 - Autocorrelation and Time Series Methods," PennState Eberly College of Science, 2018. [Online]. Available: https://online.stat.psu.edu/stat462/node/188/.

N. Dritsakis and P. Klazoglou, "Forecasting Unemployement Rates in USA Using Box-Jenkins Methodology," International Journal of Economics and Financial Issues, vol. 8, no. 1, pp. 9-20, 2018.

Yahoo! Finance, "Cameco Corporation (CCJ) Stock Historical Prices & Data," Yahoo!, [Online]. Available: https://finance.yahoo.com/quote/CCJ/history?p=CCJ.

R. Elizabeth and S. Sitorus, "Gold Price Forecasting Using Autoregressive Integrated," Journal of Mathematics Technology and Education, vol. 1, no. 1, pp. 11-18, 2021.

S. Mehrmolaei, "Time series forecasting using improved ARIMA," in IEEE Artificial Intelligence and robotics (IRANOPEN), 2017.

C. Dritsaki, D. Niklis and P. Stamatiou, "Oil Consumption Forecasting using ARIMA Models: An Empirical Study for Greece," International Journal of Energy Economics and Policy, vol. 11, no. 4, pp. 214-224, 2021.

M. Murat, I. Malinowska, M. Gos and J. Krzyszczak, "Forecasting daily meteorological time series using ARIMA and regression models," International Agrophysics, vol. 32, no. 2, pp. 253-264, 2018.

G. Scott, "Box-Jenkins Model: Definition, Uses, Timeframes, and Forecasting," Investopedia, 30 August 2022. [Online]. Available: https://www.investopedia.com/terms/b/box-jenkins-model.asp.


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