英文标题：
《Nonparametric estimates of pricing functionals》
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作者：
Carlo Marinelli, Stefano d\'Addona
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最新提交年份：
2017
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英文摘要：
We analyze the empirical performance of several non-parametric estimators of the pricing functional for European options, using historical put and call prices on the S&P500 during the year 2012. Two main families of estimators are considered, obtained by estimating the pricing functional directly, and by estimating the (Black-Scholes) implied volatility surface, respectively. In each case simple estimators based on linear interpolation are constructed, as well as more sophisticated ones based on smoothing kernels, \\`a la Nadaraya-Watson. The results based on the analysis of the empirical pricing errors in an extensive out-of-sample study indicate that a simple approach based on the Black-Scholes formula coupled with linear interpolation of the volatility surface outperforms, both in accuracy and computational speed, all other methods.
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中文摘要：
我们利用2012年标普500指数的历史看跌和看涨价格，分析了欧洲期权定价函数的几种非参数估计的实证表现。考虑了两类主要的估计量，分别通过直接估计定价函数和估计（Black-Scholes）隐含波动率面获得。在每种情况下，都会构造基于线性插值的简单估值器，以及基于平滑核的更复杂估值器，\\`a la Nadaraya Watson。基于大量样本外研究中经验定价误差分析的结果表明，基于Black-Scholes公式的简单方法加上波动率曲面的线性插值，在精度和计算速度上都优于所有其他方法。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Pricing of Securities 证券定价
分类描述：Valuation and hedging of financial securities, their derivatives, and structured products
金融证券及其衍生产品和结构化产品的估值和套期保值
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