Extreme Spectral Risk Measures: An Application to Futures Clearinghouse Margin Requirements
By John Cotter, Kevin Dowd. 2006
124 citations recorded by the source corpus.
This paper applies the Extreme-Value (EV) Generalised Pareto distribution to the extreme tails of the return distributions for the S&P500, FT100, DAX, Hang Seng, and Nikkei225 futures contracts. It then uses tail estimators from these contracts to estimate spectral risk measures, which are coherent risk measures that reflect a user's risk-aversion function. It compares these to VaR and Expected Shortfall (ES) risk measures, and compares the precision of their estimators. It also discusses the usefulness of these risk measures in the context of clearinghouses setting initial margin requirements, and compares these to the SPAN measures typically used. Keywords: Spectral risk measures, Expected Shortfall, Value at Risk, Extreme Value
Subfields: Economics and Econometrics, Finance, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/8392c57f0387ea801e141372813d0db30782f5d1
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
In Finance
In Management Science and Operations Research
Citations in the corpus
- Portfolio diversification and value at risk under thick-tailedness (2009, background): “It is not difficult to see that existence of means of the risks in considerations is also required for finiteness of coherent spectral measures of risk (see Acerbi 2002 , Cotter and Dowd 2006 ) that generalize the expected shortfall.”