A new measure of Risk - Hybrid VaR
Dario Cintioli, Head of Risk, StatPro
THE FALSE PROMISES OF EXPONENTIAL-WEIGHTING, PRO-CYCLICALITY
AND A NEW MEASURE OF RISK: HYBRID VAR
With each financial failure, the credit crisis generates a new
bout of criticism of Value-at-Risk (VaR) and practice of risk
management in general.
This article does not seek to discuss how most
of the criticism is often ill-placed, that VaR is not the
only risk measure available in risk management, that VaR can be
produced with models other than Gaussian Variance/Covariance, and
so forth.
We want instead to focus our attention on two
serious failures of VaR (and similar measures, including Expected
Shortfall, or Conditional VaR) during this ongoing crisis:
· The significant
failures in backtesting
· VaR
pro-cyclicality
These two criticisms are certainly valid and
while, as risk managers, we can find justifications for the first
(weather forecast tends to be less reliable when dealing with
tornados), the second criticism is more serious and requires
greater attention.
Exponentially Weighted (EW) risk models that
give greater weight to more recent history are very popular and
widely used, but they are also the most pro-cyclical of the models.
In this article we will demonstrate that their pro-cyclicality is
not balanced by better performance in backtesting terms, and will
present a new measure of risk “Hybrid VaR”.
The first part of the article looks at the
methodology for computing Hybrid VaR, and the second part will
demonstrate that it performs better in backtesting than pure
historical VaR or EW VaR (both Gaussian and
Historical-Adjusted).
In addition, Hybrid VaR is anti-cyclical in
boom periods, discouraging risk-taking in good times, and much more
stable than other measures. This significantly mitigates the
problem of pro-cyclicality while also providing a measure that is
more reliable than other risk measures.
To download the full 18-page whitepaper
on Hybrid VaR please click
here.
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