Abstract
We have selectively presented a few risk measures in the preceding chapters that, in our experience, cover many relevant aspects and tasks in a real-world market risk setup. We propose to mainly use the volatility-rescaled historical VaR[Ω] for daily risk management. It is especially well-suited to capturing “tomorrow’s PnL,” as it reacts fast to changes in volatility levels. The concurrent use of the sensitivity-based analytical VaR(s Ω) serves as a sanity check and provides an additive decomposition to VaR-contributions of the risk factors, which is a handy analysis tool because it appropriately weighs risk factors by both their sensitivity and volatility. Finally, the most helpful measure we take away from the expected shortfall world is the position-wise conditional expected shortfall cES[α|Ω], which provides a useful complementary breakdown of risk to positions.
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Notes
- 1.
This issue gets even more pronounced for negatively correlated positions, where more return pairs yield close VaR contenders.
- 2.
The concepts involved here are more deeply connected, as one could consider each position to represent a separate asset. While we tried to delineate those views on risk decomposition, they really represent two sides of the same coin. The terms marginal VaR and component VaR are commonly used in this context. The names used here I chose by sympathy and memorability; marginal VaR often also refers to what we called incremental VaR, while component VaR sounds a bit like poet laureate or Astronomer Royal.
- 3.
We must refrain from dubbing this excremental VaR.
- 4.
The regulator prescribes the window size to be used for this purpose; one-year periods are typically used for the stressed VaR.
- 5.
The fast analytical approach can provide valuable support for speeding up this procedure. It can, for example, run a first tentative selection, thus limiting the number of full VaR evaluations required.
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Auer, M. (2018). Support Measures. In: Hands-On Value-at-Risk and Expected Shortfall. Management for Professionals. Springer, Cham. https://doi.org/10.1007/978-3-319-72320-4_11
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DOI: https://doi.org/10.1007/978-3-319-72320-4_11
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-72319-8
Online ISBN: 978-3-319-72320-4
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