  This paper applies an AR(1)-GARCH (1, 1) process to detail the conditional
distributions of the return distributions for the S&P500, FT100, DAX, Hang
Seng, and Nikkei225 futures contracts. It then uses the conditional
distribution for these contracts to estimate spectral risk measures, which are
coherent risk measures that reflect a user's risk-aversion function. It
compares these to more familiar VaR and Expected Shortfall (ES) measures of
risk, and also compares the precision and discusses the relative usefulness of
each of these risk measures in setting variation margins that incorporate
time-varying market conditions. The goodness of fit of the model is confirmed
by a variety of backtests.
