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NASDAQ Forecast Based on ARIMA and ETS Models
- 1 College of Letters, Arts and Sciences, University of Southern California, Los Angeles, US
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Abstract
In the financial markets, stock price prediction has always been a classic, popular, and challenging research topic. The ability to effectively predict stock movements can allow investors to maximize returns and manage risks, which reinforces the efficiency of capital markets. Furthermore, understanding and improving prediction models contributes to the academic study of market behavior and the development of more robust financial models. However, stock prices are subject to various economic, political, and psychological factors, introducing high uncertainty and making accurate forecasting a complex endeavor. In this research, two forecasting methods will be used to forecast the NASDAQ index. Their prediction result will then be compared. The ARIMA model and the ETS model are the two forecasting models used in this study. The past 10 years (2013-2024) of NASDAQ index (open) will be used as the data for the training set and test set. The goal of this study is to compare and evaluate the accuracy of each model and determine the model that is better suited for financial forecasting. The result shows that the RMSE value of ARIMA model fitting is lower than ETS model fitting. The ARIMA model provides a better predicting result in predicting the NASDAQ index. This paper compares ARIMA and ETS models to provide insights for future investment decisions and show a new perspective on stock price forecasting.
Keywords
ARIMA, ETS, NASDAQ, Time series, Prediction
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Cite this article
Cai,S. (2025). NASDAQ Forecast Based on ARIMA and ETS Models. Advances in Economics, Management and Political Sciences,144,44-51.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of ICFTBA 2024 Workshop: Finance's Role in the Just Transition
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