Frontiers in VaR forecasting and backtesting Articles uri icon

publication date

  • April 2016

start page

  • 475

end page

  • 501

issue

  • 2

volume

  • 32

international standard serial number (ISSN)

  • 0169-2070

electronic international standard serial number (EISSN)

  • 1872-8200

abstract

  • The interest in forecasting the Value at Risk (VaR) has been growing over the last two decades, due to the practical relevance of this risk measure for financial and insurance institutions. Furthermore, VaR forecasts are often used as a testing ground when fitting alternative models for representing the dynamic evolution of time series of financial returns. There are vast numbers of alternative methods for constructing and evaluating VaR forecasts. In this paper, we survey the new benchmarks proposed in the recent literature. (C) 2015 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

keywords

  • backtesting; extreme value theory; garch; quantile; risk; value-at-risk; financial time-series; autoregressive conditional duration; empirical likelihood intervals; heavy-tailed distributions; extreme-value theory; expected shortfall; garch models; quantile regression; asset returns