Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: Inter-day versus intra-day data
Stavros Degiannakis () and
International Review of Financial Analysis, 2017, vol. 49, issue C, 176-190
In order to provide reliable Value-at-Risk (VaR) and Expected Shortfall (ES) forecasts, this paper attempts to investigate whether an inter-day or an intra-day model provides accurate predictions. We investigate the performance of inter-day and intra-day volatility models by estimating the AR(1)-GARCH(1,1)-skT and the AR(1)-HAR-RV-skT frameworks, respectively. This paper is based on the recommendations of the Basel Committee on Banking Supervision. Regarding the forecasting performances, the exploitation of intra-day information does not appear to improve the accuracy of the VaR and ES forecasts for the 10-steps-ahead and 20-steps-ahead for the 95%, 97.5% and 99% significance levels. On the contrary, the GARCH specification, based on the inter-day information set, is the superior model for forecasting the multiple-days-ahead VaR and ES measurements. The intra-day volatility model is not as appropriate as it was expected to be for each of the different asset classes; stock indices, commodities and exchange rates.
Keywords: Basel II; Basel III; Value-at-risk; Expected shortfall; Volatility forecasting; Intra-day data; Multi-period-ahead; Forecasting accuracy; Risk modeling (search for similar items in EconPapers)
JEL-codes: C15 C32 C53 G15 G17 (search for similar items in EconPapers)
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Working Paper: Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: inter-day versus intra-day data (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:49:y:2017:i:c:p:176-190
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