英文标题：
《High-Order Splitting Methods for Forward PDEs and PIDEs》
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作者：
Andrey Itkin
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最新提交年份：
2014
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英文摘要：
This paper is dedicated to the construction of high-order (in both space and time) finite-difference schemes for both forward and backward PDEs and PIDEs, such that option prices obtained by solving both the forward and backward equations are consistent. This approach is partly inspired by Andreasen & Huge, 2011 who reported a pair of consistent finite-difference schemes of first-order approximation in time for an uncorrelated local stochastic volatility model. We extend their approach by constructing schemes that are second-order in both space and time and that apply to models with jumps and discrete dividends. Taking correlation into account in our approach is also not an issue.
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中文摘要：
本文致力于为前向和后向偏微分方程和PIDE构造高阶（空间和时间）有限差分格式，以便通过求解前向和后向方程得到的期权价格是一致的。这种方法的部分灵感来自Andreasen&Gig，2011，他报告了一对不相关局部随机波动率模型的一阶时间近似一致有限差分格式。我们通过构造在空间和时间上都是二阶的、适用于具有跳跃和离散红利的模型的方案来扩展他们的方法。在我们的方法中考虑相关性也不是问题。
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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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