Risk measures for the 21st century

By G. Szegö. 2004

307 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/1d30bdff726aba88f42f608cd585b1624be855a2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Absolutely Continuous Copulas with Given Diagonal Sections (2008, background): “…to Fabrizio Durante, Department of Knowledge-Based Mathematical Systems, Johannes Kepler University, Linz A-4040, Austria; E-mail: fabrizio. durante@jku.at 2924 Malevergne and Sornette (2006), Embrechts and Puccetti (2006), Jaworski (2006), Jouanin et al. (2004), and the references therein.”
DESIRABLE PROPERTIES OF AN IDEAL RISK MEASURE IN PORTFOLIO THEORY (2008, background): “In particular, the most celebrated and used benchmark approaches are based on coherent risk measures (see Szegö (2004)).”
Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm (2005, unknown): “However, the limitations of the method in these applications became apparent, because background corrections proved troublesome and for the more complicated cases, the intervention of skilled operators during the fitting procedure was usually required.”
Dynamic Monetary Risk Measures for Bounded Discrete-Time Processes (2004, background): “For relations of coherent and convex monetary risk measures to pricing and hedging in incomplete markets, we refer to Jaschke and Küchler (2001), Carr et al. (2001), Frittelli and Rosazza Gianin (2004), and Staum (2004).”
Value-at-risk versus expected shortfall: A practical perspective (2005, unknown): “…0:1Þ þ X100 n¼0 0:04 0:005 0:05n 0:95100 n 100Cn ln ~wð0:1; 0:1Þ; ð3Þ where ~wða; bÞ ¼ 1:0475aX 1 þ 1:0075bX 2 þ 1:055X 3 100 0:9n 100 þ 1:0025ðW 0 X 1 X 2 X 3Þ; 11 For general issues in optimization of VaR and expected shortfall, see Rockafellar and Uryasev (2002), and Alexander et al. (2004).”
Using extreme value theory to measure value-at-risk for daily electricity spot prices (2006, methodology): “The AR-EGARCH-N model (that is, 17 Manganelli and Engle (2004) note that it is common to utilize a rolling window of between 6 and 24 months (i.e., between 180 and 730 observations) for HS approaches. the autoregressive model with Normally distributed errors) significantly underestimates the 95%…”
Bid-Ask Dynamic Pricing in Financial Markets with Transaction Costs and Liquidity Risk (2007, background): “Theorems of representation have been proved in the static case for monetary convex risk measures in [36], [37] and [39].”
Channel Coordination with a Risk‐Neutral Supplier and a Downside‐Risk‐Averse Retailer (2005, background): “The measure is also closely related to Value at Risk (VaR), a widely used downside risk measure deﬁned to be the maximum loss at a given conﬁdence level, since the probability of the return falling below VaR equals the conﬁdence level (Jorion 2001; Szego¨ 2004).”
Coordination of Supply Chains with Risk‐Averse Agents (2004, background): “b = λr λr + λs (p − v) , (28) w = p λr λr + λs + λs λr + λs c, (29)”