再校准难题：为可赎回证券进行对冲估值调整
The Recalibration Conundrum: Hedging Valuation Adjustment for Callable Claims
AI总结：
本文提出针对可赎回证券的再校准模型风险调整方法，通过调整风险储备以应对错误行使决策风险，超过传统估值差异储备。
摘要：
动态对冲理论只有在给定模型的设定下才有意义，而动态对冲实践却恰恰相反，模型在数据每日再校准后便逃离了。这在数量金融中形成了一个悖论。本文重新审视Burnett（2021）及Burnett和Williams（2021）提出的对冲估值调整（HVA）概念，最初旨在处理动态对冲摩擦，现在转向再校准和模型风险。具体而言，我们将HVA模型风险方法扩展到可赎回资产，即Bénèzet和Crépey（2024）的方法。传统的处理模型风险方法是保留参考模型与交易员使用的本地模型之间的估值差异。然而，尽管交易员的价格因此被修正，其对冲策略和行使决策仍不正确，这需要调整后的风险储备。我们以一个典型的可赎回范围累积代表产品为例，展示了模型风险储备调整以考虑错误行使决策风险可能远超仅考虑估值差异的基本储备。
英文摘要：
The dynamic hedging theory only makes sense in the setup of one given model, whereas the practice of dynamic hedging is just the opposite, with models fleeing after the data through daily recalibration. This is quite of a quantitative finance paradox. In this paper we revisit Burnett (2021) \& Burnett and Williams (2021)'s notion of hedging valuation adjustment (HVA), originally intended to deal with dynamic hedging frictions, in the direction of recalibration and model risks. Specifically, we extend to callable assets the HVA model risk approach of B{é}n{é}zet and Cr{é}pey (2024). The classical way to deal with model risk is to reserve the differences between the valuations in reference models and in the local models used by traders. However, while traders' prices are thus corrected, their hedging strategies and their exercise decisions are still wrong, which necessitates a risk-adjusted reserve. We illustrate our approach on a stylized callable range accrual representative of huge amounts of structured products on the market. We show that a model risk reserve adjusted for the risk of wrong exercise decisions may largely exceed a basic reserve only accounting for valuation differences.
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