We train a universal LSTM network based on a pooled dataset made of hundreds of liquid stocks aiming at forecasting next day realized volatility.
- Speaker
- Date
- Thursday 6 Apr 2023, 12:00 - 13:00
- Type
- Seminar
- Spoken Language
- English
- Room
- ET-18
- Building
- E Building
- Location
- Campus Woudestein
Showing its consistently superior performance compared to asset-specific parametric models, we uncover nonparametric evidences of universal volatility formation mechanism across assets relating past market realizations, including daily returns and volatilities, to current volatilities. A simple blended forecast combining the rough fractional stochastic volatility and quadratic rough Heston models with fixed parameters results in the same level of performance as the universal LSTM, which confirms the universal volatility formation process from a parametric perspective. This is joint work with Jianfei Zhang.
You can sign up for this seminar by sending an email to eb-secr@ese.eur.nl.
Lunch will be provided (vegetarian option included).
Organisers
- More information
Secretariat Econometrics: eb-secr@ese.eur.nl