英文标题：
《Numerical analysis on quadratic hedging strategies for normal inverse
Gaussian models》
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作者：
Takuji Arai, Yuto Imai and Ryo Nakashima
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最新提交年份：
2018
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英文摘要：
The authors aim to develop numerical schemes of the two representative quadratic hedging strategies: locally risk minimizing and mean-variance hedging strategies, for models whose asset price process is given by the exponential of a normal inverse Gaussian process, using the results of Arai et al. \\cite{AIS}, and Arai and Imai. Here normal inverse Gaussian process is a framework of L\\\'evy processes frequently appeared in financial literature. In addition, some numerical results are also introduced.
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中文摘要：
作者旨在利用Arai et al.{AIS}和Arai and Imai的结果，针对资产价格过程由正态逆高斯过程的指数给出的模型，开发两种具有代表性的二次套期保值策略的数值方案：局部风险最小化和均值方差套期保值策略。这里，正态逆高斯过程是金融文献中经常出现的列维过程的一个框架。此外，还介绍了一些数值结果。
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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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