Dr Stavros Degiannakis and Dr Christos Floros acknowledge the support from the European Community's Seventh Framework Programme (FP7-PEOPLE-IEF) funded under grant agreement No. PIEF-GA-2009-237022. We would like to thank two anonymous referees for their constructive criticism and suggestions which helped us to improve the scope and clarity of the paper.
A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification
Article first published online: 6 DEC 2012
© 2012 The Authors. The Manchester School © 2012 The University of Manchester and John Wiley & Sons Ltd
The Manchester School
Volume 82, Issue 1, pages 71–102, January 2014
How to Cite
Degiannakis, S., Dent, P. and Floros, C. (2014), A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification. The Manchester School, 82: 71–102. doi: 10.1111/manc.12001
- Issue published online: 17 DEC 2013
- Article first published online: 6 DEC 2012
- Manuscript Accepted: 23 MAR 2012
- Manuscript Received: 31 MAY 2011
- European Community. Grant Number: PIEF-GA-2009-237022
The paper provides a methodological contribution to the multi-step Value-at-Risk (VaR) and Expected Shortfall (ES) forecasting through a new adaptation of the Monte Carlo simulation approach for forecasting multi-period volatility to a Fractionally Integrated Generalized Autoregressive Conditional Heteroscedasticity (FIGARCH) framework for leptokurtic and asymmetrically distributed portfolio returns. Accounting for long memory within the conditional variance process with skewed Student-t (skT) conditionally distributed innovations, accurate 95 per cent and 99 per cent VaR and ES forecasts are calculated for multi-period time horizons. The results show that the FIGARCH-skT model has a superior multi-period VaR and ES forecasting performance.