SMU Data Science Review


While the options market may be intimidating for a beginner, having the right tools can help improve the outcome of their investments. This project aims to develop a tool that uses time-series analysis and forecasting to model the future demand of S&P 500 and AAPL options contracts. The open interest of these contracts will be analyzed using various models such as AR, ARIMA, Neural Networks, and VAR, along with the put-call ratio. The goal is not to make buy or sell recommendations, but alert the user when money is flowing into a security or index. Of all the models, the use of the ARMA model provides the best results for predicting the open interest in contracts for these specific symbols.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License