Eric Beutner, Alexander Heinemann, Stephan Smeekes
arXiv 28 Aug 2018 · Econometrics
arXiv:1808.09125 · PDF · Extracted main text
A fixed-design residual bootstrap method is proposed for the two-step estimator of Francq and Zako\"ian (2015) associated with the conditional Value-at-Risk. The bootstrap's consistency is proven for a general class of volatility models and intervals are constructed for the conditional Value-at-Risk. A simulation study reveals that the equal-tailed percentile bootstrap interval tends to fall short of its nominal value. In contrast, the reversed-tails bootstrap interval yields accurate coverage. We also compare the theoretically analyzed fixed-design bootstrap with the recursive-design bootstrap. It turns out that the fixed-design bootstrap performs equally well in terms of average coverage, yet leads on average to shorter intervals in smaller samples. An empirical application illustrates the interval estimation.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Falk, M. and E. Kaufmann (1991) Coverage probabilities of bootstrap-confidence intervals for quantiles | 1.000 | 9 | 3 | 100% |
| 2 | Cavaliere, G., R.S. Pedersen, and A. Rahbek (2018) The fixed volatility bootstrap for a class of ARCH($q$) models | 1.000 | 5 | 4 | 100% |
| 3 | Spierdijk, L (2016) Confidence intervals for ARMA–GARCH value-at-risk: the case of heavy tails and skewness | 0.928 | 4 | 3 | 100% |
| 4 | Francq, C. and J.M. Zakoän (2015) Risk-parameter estimation in volatility models | 0.881 | 19 | 6 | 68% |
| 5 | Gao, F. and F. Song (2008) Estimation risk in GARCH VaR and ES estimates | 0.874 | 5 | 2 | 100% |
| 6 | Shimizu, K (2009) Bootstrapping Stationary ARMA–GARCH Models | 0.874 | 5 | 2 | 100% |
| 7 | Beutner, E., A. Heinemann, and S. Smeekes (2021) A justification of conditional confidence intervals self | 0.845 | 21 | 2 | 90% |
| 8 | Cavaliere, G., H.B. Nielsen, R.S. Pedersen, and A. Rahbek (2022) Bootstrap inference on the boundary of the parameter space, with application to conditional volatility models | 0.843 | 3 | 3 | 100% |
| 9 | Francq, C. and J.M. Zakoïan (2011) GARCH Models: Structure, Statistical Inference and Financial Applications | 0.836 | 12 | 3 | 58% |
| 10 | Berkes, I. and L. Horváth (2003) Limit results for the empirical process of squared residuals in GARCH models | 0.754 | 7 | 3 | 43% |
Showing the top 10 of 134 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | V1 A Residual Bootstrap for Conditional Expected Shortfall | 0.809 | 51 | 7 |
| 2 | A Bootstrap Test for the Existence of Moments for GARCH Processes | 0.540 | 19 | 4 |
| 3 | Estimating Conditional Value-at-Risk with Nonstationary Quantile Predictive Regression Models | 0.405 | 1 | 1 |