Predicting CBOE Values with ARIMA

版本 1.0.0 (372.2 KB) 作者: Porawat
ARIMA model predicts stock volatility (VIX) using data from 1992-2019. Accurate forecasts for 2014 suggest potential for economic prediction
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更新时间 2024/10/25

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This project aimed to predict stock market volatility using the VIX index and various regression methods. The study focused on building an ARIMA model to forecast the VIX's opening value using historical data from 1992-2019. After transforming the data to ensure stationarity, an ARIMA(2,1,2) model was selected based on its strong performance indicated by AIC and BIC metrics. This model was then used to forecast 2014 VIX values, showing promising alignment with actual data. The project served as a valuable learning experience in time series analysis and web scraping techniques. We used VIX data from https://github.com/NathanMaton/vix_prediction.

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Porawat (2025). Predicting CBOE Values with ARIMA (https://ww2.mathworks.cn/matlabcentral/fileexchange/174455-predicting-cboe-values-with-arima), MATLAB Central File Exchange. 检索时间: .

Visutsak, P., Wongpanti, R., & Netisopakul, P. (2024). Forecasting CBOE opening values: An effective ARIMA approach with transformation and model diagnostics. Science Journal of Suranaree University of Technology, 31(4), 030218(1-11). https://doi.org/10.55766/sujst-2024-04-e04932

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1.0.0