Trading Events: Smiles, Frowns and Moustaches – the Many Faces of the Options Market

Mark Baker, T. Gillberg, Shaun A. Thomas
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引用次数: 3

Abstract

Financial markets are becoming increasingly event driven. These can take the form of economic releases, speeches and elections. The arrival of this new information often causes the underlying asset to jump. Consequently, the expectation of these known announcements can produce significant distortions in option volatility surfaces. This presents a challenge, or opportunity, for pricing and risk management. We therefore undertake an examination of large events. Firstly, we perform an empirical analysis of the UK referendum in 2016. This is in order to give market practitioners intuition for these extreme scenarios and to guide us towards a quantitative approach. As a result, we introduce a new bimodal jump model. By varying the two jump parameters, we show how to parsimoniously produce the aforementioned smile distortions – specifically: skews, frowns and W-shapes. Furthermore, we demonstrate the model’s calibration to the observed volatility surface leading up to the referendum, and the French election in 2017. If jump parameters are frozen with time, the model can be used in the temporal volatility interpolation. Finally, we discuss how the jump probabilities are becoming increasingly observable via alternative data, such as betting markets, election polls and research reports.
交易事件:微笑,皱眉和胡须-期权市场的许多面孔
金融市场正变得越来越受事件驱动。这些可以采取经济发布、演讲和选举的形式。这些新信息的到来通常会导致相关资产的价格上涨。因此,对这些已知公告的预期可能会对期权波动率产生重大扭曲。这给定价和风险管理带来了挑战或机遇。因此,我们对大型事件进行研究。首先,我们对2016年英国公投进行了实证分析。这是为了给市场从业者对这些极端情况的直觉,并指导我们走向量化方法。因此,我们引入了一个新的双峰跳跃模型。通过改变两个跳跃参数,我们展示了如何简约地产生前面提到的微笑扭曲-特别是:歪斜,皱眉和w形。此外,我们还证明了该模型对2017年公投和法国大选前观察到的波动面进行了校准。如果跳跃参数随时间冻结,则该模型可用于时间波动率插值。最后,我们讨论了如何通过其他数据,如博彩市场、选举民意调查和研究报告,越来越多地观察到跳跃概率。
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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