论文标题
大量波动微笑的马鞍点方法
Saddle-Point Approach to Large-Time Volatility Smile
论文作者
论文摘要
我们扩展了[1]中提出的鞍点方程，以推导大型模型的波动性微笑，提供其理论基础并研究其在经典模型中的应用。只要特征函数在巨大的时间内实现莱维型缩放行为，该方法就可以在特定模型下分析地研究大型的微笑行为，并以与随机性 - vlotity-vlotility-nistribility-nistribal-niverinal-niverization（SVI）相同。
We extend upon the saddle-point equation presented in [1] to derive large-time model-implied volatility smiles, providing its theoretical foundation and studying its applications in classical models. As long as characteristic function fulfills a Lévy-type scaling behavior in large time, the approach allows us to study analytically the large-time smile behaviors under specific models, and moreover, to reach a very wide class of arbitrage-free model-inspired parametrizations, in the same manner as stochastic-volatility-inspired (SVI).
