Forecasting Realized Volatility with Earnings Announcements and Overnight Returns
Master thesis
Permanent lenke
https://hdl.handle.net/11250/3097768Utgivelsesdato
2023Metadata
Vis full innførselSamlinger
- Master of Science [1621]
Sammendrag
In our study, we forecast realized volatility utilizing a large panel of
stocks from the S&P 500, with the inclusion of overnight returns and
earnings announcements. Our comparative analysis employs both the
heterogeneous autoregressive model and gradient boosting. Upon evaluation,
we ascertain that the inclusion of earnings announcements
moderately enhances the precision of RV forecasting. Furthermore,
our findings suggest that the gradient-boosting methodology demonstrates
superior performance in comparison to the HAR model.
Beskrivelse
Masteroppgave(MSc) in Master of Science in Quantitative finance - Handelshøyskolen BI, 2023