英文标题：
《Calibration to American Options: Numerical Investigation of the
  de-Americanization》
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作者：
Olena Burkovska, Maximilian Ga{\\ss}, Kathrin Glau, Mirco Mahlstedt,
  Wim Schoutens and Barbara Wohlmuth
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最新提交年份：
2016
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英文摘要：
  American options are the reference instruments for the model calibration of a large and important class of single stocks. For this task, a fast and accurate pricing algorithm is indispensable. The literature mainly discusses pricing methods for American options that are based on Monte Carlo, tree and partial differential equation methods. We present an alternative approach that has become popular under the name de-Americanization in the financial industry. The method is easy to implement and enjoys fast run-times. Since it is based on ad hoc simplifications, however, theoretical results guaranteeing reliability are not available. To quantify the resulting methodological risk, we empirically test the performance of the de-Americanization method for calibration. We classify the scenarios in which de-Americanization performs very well. However, we also identify the cases where de-Americanization oversimplifies and can result in large errors.
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中文摘要：
美式期权是对一大类重要的单只股票进行模型校准的参考工具。对于这项任务，快速准确的定价算法是必不可少的。文献主要讨论了基于蒙特卡罗、树和偏微分方程方法的美式期权定价方法。我们提出了一种在金融业中以“去美国化”的名义流行的替代方法。该方法易于实现，运行速度快。然而，由于它基于特殊的简化，因此无法获得保证可靠性的理论结果。为了量化由此产生的方法学风险，我们对非美国化校准方法的性能进行了实证测试。我们对非美国化表现良好的情景进行了分类。然而，我们也发现了反美化过于简单化并可能导致较大错误的情况。
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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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