Relatore: Rita L. D’Ecclesia, Daniele Clementi - Sapienza University of Rome
Date: 30 JANUARY 2020 from 16:00 to 18:00
Event location: Seminar Room, 1st floor, Department of Statistics, Via Belle Arti 41, Bologna
Type: Statistics Seminars
Forecasting and adequately measuring equity returns volatility is crucial for portfolio selection and trading strategies. Implied volatility is often considered to be informationally superior to the realized volatility. When available, implied volatility is largely used by practitioners and investors to forecast future volatility. To this extent we want to identify the best approach to track equity return implied volatility. In this paper we use parametric and ANN approaches to track stock returns implied volatility. Using daily prices for regularly traded stocks on major international Exchanges, together with data of stock market indices we estimate time varying volatility using the E-GARCH approach, the HESTON model and introducing a novel ANN framework to replicate the corresponding implied volatility. Overall the E-GARCH and the ANN approaches result accurate to track the equity return implied volatility.