WHS
The MRA Accelerator provides the “Weighted” variations of the VaR and ES measures which implement the WHS - exponentially weighted historical simulation approach.
References
The implemented algorithm is described in Section 3 of the following paper:
- Richardson, Matthew P. and Boudoukh, Jacob and Whitelaw, Robert F., The Best of Both Worlds: A Hybrid Approach to Calculating Value at Risk (November 1997). Available at SSRN: https://ssrn.com/abstract=51420 or http://dx.doi.org/10.2139/ssrn.51420
Implementation
- The default value for the decay parameter $$\lambda$$ is 0.94, it is configured in the
risk-config.properties
and can be overridden using the WeightedVaRLambda context value. - Each historical scenario is assigned a weight, computed based on the $$\lambda$$ value and the number of business days ago.
- The simulated PL input data, which can be displayed using the PnLVectorExpand measure, is ranked from the worst loss to the highest profit.
- The scenario weights are accumulated starting from the worst loss and further along the scenarios ranked by PL.
- The Weighted VaR is obtained by linearly interpolating the PLs of the ranked scenarios where accumulated weights contain the desired VaRConfidenceLevel.
- The Weighted ES is obtained by averaging the PL across scenarios below the Weighted VaR. Please note however, that the confidence level for the Weighted ES is controlled by a different context value - ESConfidenceLevel.
See also
- WeightedVaRLambda (cube)