英文标题：
《Nonparametric and arbitrage-free construction of call surfaces using
l1-recovery》
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作者：
Pierre M. Blacque-Florentin and Badr Missaoui
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最新提交年份：
2016
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英文摘要：
This paper is devoted to the application of an $l_1$ -minimisation technique to construct an arbitrage-free call-option surface. We propose a nononparametric approach to obtaining model-free call option surfaces that are perfectly consistent with market quotes and free of static arbitrage. The approach is inspired from the compressed-sensing framework that is used in signal processing to deal with under-sampled signals. We address the problem of fitting the call-option surface to sparse option data. To illustrate the methodology, we proceed to the construction of the whole call-price surface of the S\\&P500 options, taking into account the arbitrage possibilities in the time direction. The resulting object is a surface free of both butterfly and calendar-spread arbitrage that matches the original market points. We then move on to an FX application, namely the HKD/USD call-option surface.
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中文摘要：
本文致力于应用$l_1$最小化技术构造无套利看涨期权曲面。我们提出了一种非参数方法来获得与市场报价完全一致且无静态套利的无模型看涨期权曲面。该方法受信号处理中用于处理欠采样信号的压缩传感框架的启发。我们解决了将看涨期权曲面拟合到稀疏期权数据的问题。为了说明该方法，我们继续构建S\\&P500期权的整个看涨期权价格面，同时考虑到时间方向上的套利可能性。由此产生的对象是一个既没有蝴蝶套利也没有日历套利的表面，与原始市场点相匹配。然后我们继续讨论外汇应用，即港元/美元看涨期权。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Computational Finance 计算金融学
分类描述：Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法，包括蒙特卡罗，偏微分方程，格子和其他数值方法，并应用于金融建模
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