The role of high frequency intra-daily data, daily range and implied volatility in multi-period Value-at-Risk forecasting

Dimitrios Louzis, Spyros Xanthopoulos-Sisinis and Apostolos P. Refenes

MPRA Paper from University Library of Munich, Germany

Abstract: In this paper, we assess the informational content of daily range, realized variance, realized bipower variation, two time scale realized variance, realized range and implied volatility in daily, weekly, biweekly and monthly out-of-sample Value-at-Risk (VaR) predictions. We use the recently proposed Realized GARCH model combined with the skewed student distribution for the innovations process and a Monte Carlo simulation approach in order to produce the multi-period VaR estimates. The VaR forecasts are evaluated in terms of statistical and regulatory accuracy as well as capital efficiency. Our empirical findings, based on the S&P 500 stock index, indicate that almost all realized and implied volatility measures can produce statistically and regulatory precise VaR forecasts across forecasting horizons, with the implied volatility being especially accurate in monthly VaR forecasts. The daily range produces inferior forecasting results in terms of regulatory accuracy and Basel II compliance. However, robust realized volatility measures such as the adjusted realized range and the realized bipower variation, which are immune against microstructure noise bias and price jumps respectively, generate superior VaR estimates in terms of capital efficiency, as they minimize the opportunity cost of capital and the Basel II regulatory capital. Our results highlight the importance of robust high frequency intra-daily data based volatility estimators in a multi-step VaR forecasting context as they balance between statistical or regulatory accuracy and capital efficiency.

Keywords: Realized GARCH; Value-at-Risk; multiple forecasting horizons; alternative volatility measures; microstructure noise; price jumps (search for similar items in EconPapers)
JEL-codes: C53 (search for similar items in EconPapers)
Date: 2011-10-29
New Economics Papers: this item is included in nep-ban, nep-for, nep-mst, nep-ore and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/35252/1/MPRA_paper_35252.pdf original version (application/pdf)

Related works:
Journal Article: The Role of High‐Frequency Intra‐daily Data, Daily Range and Implied Volatility in Multi‐period Value‐at‐Risk Forecasting (2013)
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:pra:mprapa:35252

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().