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Vibrato and automatic differentiation for high-order derivatives and sensitivities of financial options

机译:颤动和自动微分对高阶衍生工具和金融期权的敏感性

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This paper deals with the computation of second-order or higher Greeks of financial securities. It combines two methods, vibrato and automatic differentiation (AD), and compares these with other methods. We show that this combined technique is faster and more stable than AD of second-order derivatives or finite-difference approximations. We present a generic framework to compute any Greeks and discuss several applications to different types of European and American contracts. We also extend AD for second-order derivatives of options with non-twice-differentiable payoff.
机译:本文涉及金融证券的二阶或更高阶希腊文的计算。它结合了颤音和自动微分(AD)这两种方法,并将它们与其他方法进行了比较。我们表明,该组合技术比二阶导数或有限差分近似的AD更快,更稳定。我们提供了一个通用框架来计算任何希腊文,并讨论了对不同类型的欧美合同的几种应用。我们还将AD扩展为具有不可两次微分收益的期权的二阶导数。

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