Modeling volatility with Range-based Heterogeneous Autoregressive Conditional Heteroskedasticity model

Tomasz Skoczylas

No 2014-06, Working Papers from Faculty of Economic Sciences, University of Warsaw

Abstract: In this paper a new ARCH-type volatility model is proposed. The Range-based Heterogeneous Autoregressive Conditional Heteroskedasticity (RHARCH) model draws inspiration from Heterogeneous Autoregressive Conditional Heteroskedasticity presented by Muller et al. (1995), but employs more efficient, range-based volatility estimators instead of simple squared returns in conditional variance equation. In the first part of this research range-based volatility estimators (such as Parkinson, or Garman-Klass estimators) are reviewed, followed by derivation of the RHARCH model. In the second part of this research the RHARCH model is compared with selected ARCH-type models with particular emphasis on forecasting accuracy. All models are estimated using data containing EURPLN spot rate quotation. Results show that RHARCH model often outperforms return-based models in terms of predictive abilities in both in-sample and out-of-sample periods. Also properties of standardized residuals are very encouraging in case of the RHARCH model.

Keywords: volatility modelling; volatility forecasting; ARCH; range-based volatility estimators; heterogeneity of volatility (search for similar items in EconPapers)
JEL-codes: C13 C22 C53 (search for similar items in EconPapers)
Pages: 11 pages
Date: 2014
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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http://www.wne.uw.edu.pl/inf/wyd/WP/WNE_WP123.pdf First version, 2014 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:war:wpaper:2014-06

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