Backtesting Derivative Portfolios with Filtered Historical Simulation (FHS)

By Giovanni Barone-Adesi, K. Giannopoulos, L. Vosper. 2002

116 citations recorded by the source corpus.

Subfields: Finance

View Paper: https://www.semanticscholar.org/paper/22a2c6782bf95ed53765700c94b520f596d791ef

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Citations in the corpus

Value-at-Risk Prediction: A Comparison of Alternative Strategies (2005, result): “Barone-Adesi, Giannopoulos, and Vosper (1999, 2002) and Pritsker (2001) show that this method performs rather well, which agrees with our findings, as detailed below.”
Frontiers in VaR forecasting and backtesting (2016, methodology): “The dynamic quantile (DQ) test, proposed by Engle and Manganelli (2004), can be obtained by testing the orthogonality restriction in (13) when Xt 1 includes lags of VaR α t and of δ α t .”
A comprehensive review of Value at Risk methodologies (2014, background): “Recent empirical evidence shows that this approach works quite well in estimating VaR (see Barone-Adesi and Giannopoulos, 2001; Barone-Adesi et al., 2002; Zenti and Pallotta, 2001; Pritsker, 2001; Giannopoulos and Tunaru, 2005).”
Evaluating Predictive Performance of Value-at-Risk Models in Emerging Markets: A Reality Check (2006, methodology): “2 Following Hull and White (1998) and Barone-Adesi et al. (2002), a VaR model in this paper is said to be ‘filtered’ if it is applied to zt = (rt - mt)/st, the standardized demeaned return series using a time-varying volatility model.”
The Hidden Dangers of Historical Simulation (2006, unknown): “…et al. (1998) and Barone-Adesi et al. (1999).2 The empirical performance of historical simulation has been examined by Hendricks (1996), and Beder (1995) among others; and the empirical performance of FHS has been studied by Barone-Adesi et al. (2001) and Barone-Adesi and Giannopoulos (2002).”