Document Type
Journal Article
Publication Title
Risks
Publisher
MDPI
School
School of Business and Law
RAS ID
31609
Abstract
The paper examines the relative performance of Stochastic Volatility (SV) and Generalised Autoregressive Conditional Heteroscedasticity (GARCH) (1,1) models fitted to ten years of daily data for FTSE. As a benchmark, we used the realized volatility (RV) of FTSE sampled at 5 min intervals taken from the Oxford Man Realised Library. Both models demonstrated comparable performance and were correlated to a similar extent with RV estimates when measured by ordinary least squares (OLS). However, a crude variant of Corsi’s (2009) Heterogeneous Autoregressive (HAR) model, applied to squared demeaned daily returns on FTSE, appeared to predict the daily RV of FTSE better than either of the two models. Quantile regressions suggest that all three methods capture tail behaviour similarly and adequately. This leads to the question of whether we need either of the two standard volatility models if the simple expedient of using lagged squared demeaned daily returns provides a better RV predictor, at least in the context of the sample.
DOI
10.3390/risks8010012
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comments
Allen, D. E., & McAleer, M. (2020). Do we need stochastic volatility and generalised autoregressive conditional heteroscedasticity? Comparing squared end-of-day returns on FTSE. Risks, 8(1), Article 12. https://doi.org/10.3390/risks8010012