This paper proposes a simulation-lattice procedure to estimate financial risk measures for option positions. The framework proposed can be applied to many different kinds of options, including exotic and vanilla options; it can take account of early exercise features; heavy tails in underlying processes; estimate different risk measures, including VaR, Expected Shortfall and Spectral Risk Measures; and in a limited way it can be generalized to accommodate multiple-factors. It avoids many of the limitations of existing approaches and, in particular, avoids the problems associated approaches based on delta–gamma and similar approximations. It also generates some interesting results about the risk measures of some illustrative options positions.

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.