Multiple-Days-Ahead Value-At-Risk and Expected Shortfall Forecasting for Stock Indices, Commodities and Exchange Rates: Inter-Day Versus Intra-Day Data
34 Pages Posted: 26 Oct 2018
Date Written: January 1, 2016
Abstract
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 and 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 and 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.
The multi-period and forecasts are estimated for a range of datasets (stock indices, commodities, foreign exchange rates) in order to provide risk managers and financial institutions with information relating the performance of the inter-day and intra-day volatility models across various markets. The inter-day specification predicts and measures adequately at a 95% confidence level. Regarding the 97.5% confidence level that has been recently proposed in the revised 2013 version of Basel III, the GARCH-skT specification provides accurate forecasts of the risk measures for stock indices and exchange rates, but not for commodities (i.e. Silver and Gold). In the case of the 99% confidence level, we do not achieve sufficiently accurate and forecasts for all the assets.
Keywords: Basel II, Basel III, Value-at-Risk, Expected Shortfall, volatility forecasting, intraday data, multi-period-ahead, forecasting accuracy, risk modelling
JEL Classification: G17; G15; C15; C32; C53
Suggested Citation: Suggested Citation