The adaptive mesh model: a new approach to efficient option pricing
提出自适应网格模型，通过在粗网格上嫁接精细网格来减少非线性误差，用于高效定价普通期权、障碍期权并计算希腊字母，精度可提升数个数量级而不增加计算时间。
Most derivative securities must be priced by numerical techniques. These models contain "distribution error" and "nonlinearity error". The Adaptive Mesh Model (AMM) sharply reduces nonlinearity error by grafting one or more small sections of fine high-resolution lattice onto a tree with coarser time and price steps. Three different AMM structures are presented, one for pricing ordinary options, one for barrier options, and one for computing delta and gamma efficiently. The AMM approach can be adapted to a wide variety of contingent claims. For some common problems, accuracy increases by several orders of magnitude with no increase in execution time.