Approximation of CVaR minimization for hedging under exponential-Lévy models
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摘要
In this paper, we study the hedging problem based on the CVaR in incomplete markets. As the superhedging is quite expensive in terms of initial capital, we construct a self-financing strategy that minimizes the CVaR of hedging risk under a budget constraint on the initial capital. In incomplete markets, no explicit solution can be provided. To approximate the problem, we apply the Neyman–Pearson lemma approach with a specific equivalent martingale measure. Afterwards, we explicit the solution for call options hedging under the exponential-Lévy class of price models. This approach leads to an efficient and easy to implement method using the fast Fourier transform. We illustrate numerical results for the Merton model.
论文关键词:Conditional Value-at-Risk,Exponential-Lévy models,Incomplete market,Neyman–Pearson lemma,Esscher martingale measure,Fast Fourier transform
论文评审过程:Received 7 February 2017, Available online 26 May 2017, Version of Record 6 July 2017.
论文官网地址:https://doi.org/10.1016/j.cam.2017.05.005