A simple joint model for returns, volatility and volatility of volatility

Ding, Yashuang (Dexter)

Journal of Econometrics, 2023, vol. 232, issue 2, 521-543

Abstract: We propose a model that allows for conditional heteroskedasticity in the volatility of asset returns and incorporates current return information into the volatility nowcast and forecast. Our model can capture all stylised facts of asset returns even with Gaussian innovations and is simple to implement. Moreover, we show that our model converges weakly to the GARCH-type diffusion as the length of the discrete time intervals between observations goes to zero. Empirical evidence shows that our model has a better fit, a more efficient parameter estimator as well as more accurate volatility and VaR forecasts than other common GARCH-type models.

Keywords: GARCH; SV; Forecasting; Nowcasting; Volatility of volatility (search for similar items in EconPapers)
JEL-codes: C22 C32 C53 C58 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407621002268
Full text for ScienceDirect subscribers only

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:eee:econom:v:232:y:2023:i:2:p:521-543

DOI: 10.1016/j.jeconom.2021.09.012

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().