Forecasting the VSTOXX EUR index (V2TX) by a recurrent neural network (RNN)
Colapinto, Filippo (A.A. 2021/2022) Forecasting the VSTOXX EUR index (V2TX) by a recurrent neural network (RNN). Tesi di Laurea in Degree program in finance, Luiss Guido Carli, relatore Emilio Barone, pp. 89. [Master's Degree Thesis]
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Abstract/Index
Volatility. Historical volatility. Implied volatility. The VSTOXX index. Introduction to volatility forecasting. Machine learning for volatility forecasting. Basic theory of machine learning. Machine learning in finance Machine learning overview. Artificial neural networks. Neural networks models for sequential data. Recurrent neural networks. Long short-term memory. Predicting a noisy sine wave. Application to financial time series-VSTOXX EUR index. Data retrieving. Data processing. Model architecture and performance. Results.
References
Bibliografia: pp. 62-65.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Economics and Finance (LM-56) |
| Chair: | Degree program in finance |
| Thesis Supervisor: | Barone, Emilio |
| Thesis Co-Supervisor: | Patnaik, Megha |
| Academic Year: | 2021/2022 |
| Session: | Extraordinary |
| Additional Information: | Tesi discussa all'estero. |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 02 Aug 2023 10:21 |
| Last Modified: | 02 Aug 2023 10:32 |
| URI: | https://tesi.luiss.it/id/eprint/36219 |
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