Expected Tail Loss
In the late 1980s, JP Morgan first introduced Value-at-Risk (VaR) into its risk management systems. Since then, VaR has been largely accepted by financial institutions and approved by regulators as the industry standard risk measure.
But while it provides an intuitive description of how much a portfolio may lose, VaR has two significant deficiencies as a true risk measure. First, it is not a coherent measure, meaning that the total VaR of a portfolio may be greater than the sum of the VaRs of the constituents. Secondly, VaR is not a very informative risk measure. It does not describe the likely magnitude of losses. It only reports the minimum level of loss at a given, sufficiently high, confidence level for a predefined time horizon. The combined effect of these deficiencies leaves portfolio managers blind both to the true diversification effect of any portfolio position and to the likely size of the loss when VaR is exceeded.
Expected Tail Loss (ETL) overcomes the inadequacies of VaR. More formally known as Conditional Value at Risk (CVaR), ETL is defined as the average of the losses in the distribution tail which are larger than the VaR for a given confidence level. Thus, ETL quantifies the size of the potential loss when VaR is exceeded. ETL also satisfies all the axioms of a coherent risk measure, thus, always accounting for the true diversification effect of any portfolio constituent.
Cognity integrates ETL across the full risk management and portfolio allocation process in a complete “down side” risk framework that results in more accurate and more intuitive:
- Ranking of assets and managers using ETL-based performance measures.
- Portfolio risk estimation by combining ETL with multivariate, non-normal distribution models.
- Identification of positional risk contributors and diversifiers using Incremental-ETL.
- Rebalancing opportunities using new Marginal Contribution to ETL, Percent Contribution to ETL. and ETL-based Implied Return measures.
- Portfolio optimization allocations yielding superior risk-adjusted returns by minimizing ETL.