英文标题：
《A backward Monte Carlo approach to exotic option pricing》
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作者：
Giacomo Bormetti, Giorgia Callegaro, Giulia Livieri, Andrea
  Pallavicini
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最新提交年份：
2015
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英文摘要：
  We propose a novel algorithm which allows to sample paths from an underlying price process in a local volatility model and to achieve a substantial variance reduction when pricing exotic options. The new algorithm relies on the construction of a discrete multinomial tree. The crucial feature of our approach is that -- in a similar spirit to the Brownian Bridge -- each random path runs backward from a terminal fixed point to the initial spot price. We characterize the tree in two alternative ways: in terms of the optimal grids originating from the Recursive Marginal Quantization algorithm and following an approach inspired by the finite difference approximation of the diffusion\'s infinitesimal generator. We assess the reliability of the new methodology comparing the performance of both approaches and benchmarking them with competitor Monte Carlo methods.
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中文摘要：
我们提出了一种新的算法，该算法允许在局部波动模型中从基础价格过程中采样路径，并在对奇异期权定价时实现显著的方差减少。新算法依赖于离散多项式树的构造。我们的方法的关键特征是——以类似于布朗桥的精神——每条随机路径从终端固定点向后运行到初始现货价格。我们用两种不同的方法来描述这棵树：根据源自递归边际量化算法的最优网格，以及遵循受扩散无穷小生成器的有限差分近似启发的方法。我们评估了新方法的可靠性，比较了两种方法的性能，并将其与竞争对手的蒙特卡罗方法进行了基准测试。
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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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