EconPapers    
Economics at your fingertips  
 

Forecasting volatility: does continuous time do better than discrete time?

Helena Veiga () and Carles Bretó

DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística

Abstract: In this paper we compare the forecast performance of continuous and discrete-time volatility models. In discrete time, we consider more than ten GARCH-type models and an asymmetric autoregressive stochastic volatility model. In continuous-time, a stochastic volatility model with mean reversion, volatility feedback and leverage. We estimate each model by maximum likelihood and evaluate their ability to forecast the two scales realized volatility, a nonparametric estimate of volatility based on highfrequency data that minimizes the biases present in realized volatility caused by microstructure errors. We find that volatility forecasts based on continuous-time models may outperform those of GARCH-type discrete-time models so that, besides other merits of continuous-time models, they may be used as a tool for generating reasonable volatility forecasts. However, within the stochastic volatility family, we do not find such evidence. We show that volatility feedback may have serious drawbacks in terms of forecasting and that an asymmetric disturbance distribution (possibly with heavy tails) might improve forecasting.

Keywords: Asymmetry; Continuous; and; discrete-time; stochastic; volatility; models; GARCH-type; models; Maximum; likelihood; via; iterated; filtering; Particle; filter; Volatility; forecasting (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ets, nep-for, nep-mst and nep-ore
Date: 2011-07
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed

Downloads: (external link)
https://e-archivo.uc3m.es/bitstream/handle/10016/12065/ws112518.pdf?sequence=1 (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:cte:wsrepe:ws112518

Access Statistics for this paper

More papers in DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística
Bibliographic data for series maintained by Ana Poveda ().

 
Page updated 2018-07-10
Handle: RePEc:cte:wsrepe:ws112518