Realized Volatility Forecasting: Continuous versus Discrete Time Models
Shuping Shi (),
Jun Yu and
Chen Zhang ()
Additional contact information
Shuping Shi: Department of Economics, Macquarie University
Chen Zhang: Department of Economics, Sun Yat-sen University
No 202537, Working Papers from University of Macau, Faculty of Business Administration
Abstract:
Forecasting realized volatility (RV) is central to financial econometrics, with important implications for risk management, asset allocation, and derivative pricing. Motivated by the ongoing debate on volatility modeling, this paper provides a comprehensive empirical comparison of many alternative models. We evaluate leading continuous time models estimated using state-of-the-art methods from the rough volatility literature, together with both standard long-memory autoregressive fractionally integrated moving average (ARFIMA) models and their rough-volatility extensions, as well as several variants of the heterogeneous autoregressive (HAR) model and their logarithmic counterparts. The models are applied to a large panel of equities and cryptocurrencies, with performance assessed using both statistical and economic criteria. Our results show that for equities, continuous time models consistently outperform discrete time alternatives across all evaluation criteria and forecasting horizons. The fractional Brownian motion model for log RV performs best at short horizons, while the fractional Ornstein Uhlenbeck model for log RV dominates in the long run. For cryptocurrencies, a mild divergence emerges between economic and statistical performance: based on realized utility, the quarticity-augmented heterogeneous autoregressive (HARQ) model for RV leads in the short term and the Brownian semistationary models prevail at longer horizons, whereas the HAR-type models for log RV deliver superior statistical accuracy.
Keywords: Realized volatility; Continuous-time models; Discrete-time models; forecasting; economic utility (search for similar items in EconPapers)
Pages: 43 pages
Date: 2025-10
New Economics Papers: this item is included in nep-for, nep-rmg and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations:
Published in UM-FBA Working Paper Series
Downloads: (external link)
https://fba.um.edu.mo/wp-content/uploads/RePEc/doc/202537.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:boa:wpaper:202537
Access Statistics for this paper
More papers in Working Papers from University of Macau, Faculty of Business Administration Contact information at EDIRC.
Bibliographic data for series maintained by Carla Leong ().