Advances in Economics, Management and Political Sciences
- The Open Access Proceedings Series for Conferences
Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
Series Vol. 59 , 05 January 2024
Open
Access | Article
Using Time Series Models to Predict SP500
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Abstract
The S&P 500 index holds significant significance in its reflection of the overall economy, making accurate financial forecasting analysis crucial for investors. This study aims to enhance the understanding of SP500 prediction methods and their practical applications. The study utilized closing price data from January 3, 2022, to June 30, 2023, as the training set, employing three series of models: Simple models, Exponential Smoothing Model, and ARIMA models. Ultimately, a comparison was made between the prediction graphs of the closing prices from July 3 to July 13, 2023, and the evaluation indicators: Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The ETS (A, N, N) model emerged as the most advantageous with an RMSE of 54.85 and an MAE of 42.28. Furthermore, this study acknowledges the inherent inclination towards random walk patterns within the index, particularly in the realm of real-time forecasting. Through this comprehensive investigation, the models cultivated through this all-encompassing inquiry substantiate the formidable potential vested within the crafting of judicious short-term investment strategies. As such, this research harbors the potential to significantly contribute to the refinement and augmentation of investment approaches in a dynamically evolving financial landscape.
Keywords
time series prediction, SP500, exponential smoothing, ARIMA
References
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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 the 2nd International Conference on Financial Technology and Business Analysis
- ISBN (Print)
- 978-1-83558-209-1
- ISBN (Online)
- 978-1-83558-210-7
- Published Date
- 05 January 2024
- Series
- Advances in Economics, Management and Political Sciences
- ISSN (Print)
- 2754-1169
- ISSN (Online)
- 2754-1177
- DOI
- 10.54254/2754-1169/59/20231013
- Copyright
- 05 January 2024
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited