Technical paper/Value-at-risk (VAR)
Approximations of value-at-risk as an extreme quantile of a random sum of heavy-tailed random variables
The authors of this paper study the approximation of extreme quantiles of random sums of heavy-tailed random variables. More specifically, sub-exponential random variables.
Improved estimation methods for value-at-risk, expected shortfall and risk contributions with high precision
This paper proposes a technique based on the saddlepoint approximation to quickly and accurately estimate common portfolio risk measures and their associated marginal component contributions.
MVA by replication and regression
Burgard and Kjaer method is extended to include margin valuation adjustment
Two measures for the price of one
Harvey Stein combines risk-neutral and real-world measures into risk methodology
Back-testing expected shortfall
Three easy-to-implement methods for back-testing expected shortfall
Estimation of risk measures for large credit portfolios
In this paper, saddle point techniques are used in the computation of risk measures for large mark-to-market credit portfolios with stochastic recovery and correlation between obligors depending on the state of the economy.
Expectiles behave as expected
Expectiles' results are analogous to those of value-at-risk and expected shortfall
