金融工程研究中心学术报告：Efficient Willow Tree Methods for Pricing and Risk-Minimizing Hedging in Financial Engineering

来源：

学校官网

收录时间：

2026-03-17 19:21:06

时间：

2025-12-10 15:00:00

地点：

腾讯会议：940-2668-5088

报告人：

马俊美

学校：

苏州大学

关键词：

Willow Tree, derivative pricing, risk-minimizing hedging, rough volatility, Rough Heston model, data-driven, implied tree, numerical efficiency

简介：

This talk presents efficient Willow Tree methods for derivative pricing and risk-minimizing hedging in financial engineering. The discussion focuses on two complementary components: a rough-volatility-based Willow Tree method and a model-free, data-driven implied Willow Tree framework. For the rough-volatility component, we work with the Rough Heston model, which captures essential market features but poses substantial numerical challenges due to its non-Markovian structure, especially in the valuation of American options. Our method constructs a three-dimensional affine Volterra process and employs Johnson-curve transformations together with moment-generating functions to build the discrete grid and approximate transition probabilities. This design effectively mitigates the curse of dimensionality associated with simulating rough volatility dynamics. Beyond pricing, it also enables the computation of globally risk-minimizing hedging strategies, thus providing a unified framework for valuation and hedging. The second component develops a data-driven implied Willow Tree method, calibrated directly from market prices of American options. It constructs discrete asset-price nodes and determines transition probabilities entirely from observed data, thereby reconstructing the underlying risk-neutral process without imposing any parametric stochastic model and eliminating model-specification risk. Numerical experiments demonstrate that these Willow Tree methods deliver improved accuracy and computational efficiency compared with traditional approaches, highlighting their practical potential in modern financial engineering.

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