Nonparametric Estimation of Conditional Expected Shortfall

By Olivier Scaillet. Assurances et gestion des risques, 2004

112 citations recorded by the source corpus.

We consider a nonparametric method to estimate conditional expected shortfalls, i.e. conditional expected losses knowing that losses are larger than a given loss quantile. We derive the asymptotic properties of kernal estimators of conditional expected shortfalls in the context of a stationary process satisfying strong mixing conditions. An empirical illustration is given for several stock index returns, namely CAC40, DAX30, S&P500, DJI, and Nikkei225.

Subfields: Finance, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d9940bcf6efe90daf530b4ffdfc78d513f95690d

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Citations in the corpus

Nonparametric estimation of conditional VaR and expected shortfall (2008, methodology): “…at both boundary and interior 2 See Chernozhukov and Umanstev (2001), Cai (2002), Fan and Gu (2003), Engle andManganelli (2004), Cai andXu (2008), Scaillet (2005) and Cosma et al. (2007) for conditionalmodels, andDuffie and Pan (1997), Artzner et al. (1999), Rockafellar and Uryasev (2000),…”
Systemic Risk in Europe (2013, unknown): “8Alternatively, the expected shortfall could be estimated using a nonparametric tail expectation estimator, as in Scaillet (2005) or Brownlees and Engle (2012).”
Asymmetric power distribution: Theory and applications to risk measurement (2007, background): “…work offers a variety of approaches to the expected shortfall estimation, ranging from fully parametric (see Aas and Haff, 2006), to semi-parametric (see McNeil and Frey, 2000; Bassett et al., 2004), and nonparametric (see Scaillet, 2004; Chen, 2005; Fermanian and Scaillet, 2005; Scaillet, 2005).”
NONPARAMETRIC ESTIMATION OF CONDITIONAL VALUE-AT-RISK AND EXPECTED SHORTFALL BASED ON EXTREME VALUE THEORY (2016, methodology): “These estimators for a -CVaR( x ) can then be used to produce nonparametric estimators for a -CES( x ) as in Scaillet (2005), Cai and Wang (2008), Kato (2012) and Linton and Xiao (2013).”
A Theoretical and Empirical Comparison of Systemic Risk Measures (2013, methodology): “To do so, we follow Brownlees and Engle (2011) and use a nonparametric kernel estimation method (Scaillet, 2005).”
How Useful is the Marginal Expected Shortfall for the Measurement of Systemic Exposure? A Practical Assessment (2013, unknown): “According to Scaillet (2005), the tail expectations can be estimated via Et−1 (εm,t | εm,t κ) = ∑t−1 j=1 εm,jKh (εm,t κ) (t− 1) p̂h (26) Et−1 ( ξi,t | εm,t κ ) = ∑t−1 j=1 ξi,jKh (εm,t κ) (t− 1) p̂h (27) with p̂h = ∑t−1 j=1Kh (εmjt κ) t− 1 (28) From a practical point of view, we chose a…”