Equity Autocalls and Vanna Negative Carries: Pricing and Hedging with a Simple Add-On

G. Salon
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引用次数: 1

Abstract

Autocall products: a toxic best-seller. Over the past twenty years, the autocall pay-off has been the most traded exotic equity product. Outstandingly popular, it is mainly sold to final customers in Europe and Asia trough notes: its average yearly volumes reaches 100 billion euros. Nevertheless, it is responsible for major losses suffered by banks’ Exotic trading desks. Roughly, when the spot remains in a [80%,105%] area around the recall barrier, daily carry loss is worth 1 to 3 basis points (depending on the product complexity, as several variations exist). Indeed, it shows a strong model-dependency due to the cancellation feature: when the spot moves, books need dynamic rehedging via vanilla options, forward contracts, correlation products. As such, it requires the use of a pricing model which correctly combines market data dynamics (volatility, repo, equity correlations, quanto drifts…) and spot dynamic, in order to price properly the cost of daily rehedging. In practice, building a pricing model complex enough to calibrate the relevant covariances while remaining numerically stable and computationally reasonable has proved to be a very serious challenge. Not mentioning ultimately the need for comprehensive interpretations of outputs. Escaping this issue, we exhibit here, a convenient way to price and hedge autocalls toxic behaviors through an additional and corrective pay-off. There are approximations throughout the building of such an approach that have been tested numerically and justified qualitatively. Nonetheless, this is cheaper in terms of model complexity and development, and it provides a comprehensive and efficient pricing scheme combined with a hedging strategy which tackles the issue of negative carries generated by an autocall replication strategy.
股票自动赎回和Vanna负持有:定价和对冲与一个简单的附加组件
Autocall产品:有毒的畅销产品。在过去的二十年里,自动赎回期权一直是交易量最大的外来股票产品。它非常受欢迎,主要通过票据销售给欧洲和亚洲的最终客户:其平均年交易量达到1000亿欧元。然而,它对银行的外汇交易部门遭受的重大损失负有责任。粗略地说,当现货保持在召回障碍周围的[80%,105%]区域时,每日利差损失值为1至3个基点(取决于产品的复杂性,因为存在几种变化)。事实上,由于取消功能,它显示出强烈的模型依赖性:当现货移动时,账簿需要通过香草期权、远期合约、相关产品进行动态重新对冲。因此,它需要使用一种定价模型,该模型正确地结合了市场数据动态(波动性、回购、股票相关性、定量漂移……)和现货动态,以便对每日再对冲的成本进行合理定价。在实践中,建立一个足够复杂的定价模型来校准相关的协方差,同时保持数值稳定和计算合理,这已被证明是一个非常严峻的挑战。最后没有提到需要对产出作出全面的解释。为了避免这个问题,我们在这里展示了一种方便的方法,通过额外的纠正性回报来定价和对冲自动调用的有害行为。在构建这种方法的过程中,有一些近似的方法已经经过了数值测试和定性验证。尽管如此,就模型复杂性和开发而言,这是更便宜的,并且它提供了一个全面而有效的定价方案,并结合了一个对冲策略,该策略解决了由自动呼叫复制策略产生的负携带问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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