Expected Shortfall: a natural coherent alternative to Value at Risk

By C. Acerbi, Dirk Tasche. 2001

639 citations recorded by the source corpus.

We discuss the coherence properties of Expected Shortfall (ES) as a financial risk measure. This statistic arises in a natural way from the estimation of the "average of the 100p % worst losses" in a sample of returns to a portfolio. Here p is some fixed confidence level. We also compare several alternative representations of ES which turn out to be more appropriate for certain purposes.

Subfields: Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/33b28f72d5674237fd3bc003c5b3b60d463349a9

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In Management Science and Operations Research

Citations in the corpus

Pessimistic Portfolio Allocation and Choquet Expected Utility (2004, background): “Variants of %να(X) have been suggested under a variety of names, including expected shortfall (Acerbi and Tasche (2002)), conditional value at risk (Rockafellar and Uryasev (2000)), tail conditional expectation (Artzner, Delbaen, Eber, and Heath (1999)).”
Master Funds in Portfolio Analysis with General Deviation Measures (2006, background): “Acerbi [1] independently arrived at this risk measure by an integral formula, calling it “expected shortfall,” and that term has subsequently been used also in [3, 28].”
Fat tails, VaR and subadditivity☆ (2013, neutral): “3 See e.g. Artzner et al. (1999), Acerbi and Tasche (2001) and Acerbi et al. (2001).”
Quantile cointegrating regression (2009, methodology): “cointegration include Campbell and Shiller (1987) in the study of bubbles in asset prices, Cochrane (1994) and Lettau and Ludvigson (2001) on the predictability of stock prices, Hall, Anderson and Granger (1992) on term structure of interest rates, Pindyck and Rothemberg (1992), Lucas (1997) and Ale”
Subadditivity Re–Examined: the Case for Value-at-Risk (2005, neutral): “It can be proved easily by constructing suitable examples that VaR violates sub-additivity property (Artzner et al., 1999; Acerbi & Tasche, 2001; Acerbi et al., 2001).”
Frontiers in VaR forecasting and backtesting (2016, methodology): “The probability in (1) is usually defined with respect to the distribution of returns conditional on the information available at time t 1.”
ON A CONVEX MEASURE OF DRAWDOWN RISK (2014, neutral): “We know that the tail mean is a convex and degree-one positive homogenous measure of risk, independent of the underlying distribution (see Acerbi and Tasche (2002a,b)). To investigate properties of CED with respect to the return universe VTn , we will need to characterize the transformation μ. Befor”
Coherent measures of risk in everyday market practice (2007, background): “This has also been the spirit of the author’s research line in recent years Acerbi 2002, Acerbi and Simonetti 2002, Acerbi and Tasche 2002a, b (see Acerbi (2003) for a review).”
Coherent risk measures (2000, background): “It is also important to consider different time horizons, because the probability that some catastrophy will happen during the next 15 years is higher than that it will happen in the next year.”
Spectral measures of risk: A coherent representation of subjective risk aversion (2002, background): “It was recently discovered (Acerbi et al., 2001; Acerbi and Tasche, 2001, 2002; Rockafellar and Uryasev, 2000, 2001) that the a-expected shortfall ESðaÞ, correctly defined as the ‘‘average of the a100% worst losses’’ of a portfolio is a coherent risk measure 1 for any chosen confidence level a 2…”
Reward-Risk Portfolio Selection and Stochastic Dominance (2005, neutral): “Other risk measures have been proposed for portfolio selection, as for example Value-at-Risk (Jorion 1997, Duffie and Pan 1997) or Expected-Shortfall (Acerbi and Tasche 2001).”