摘要

This paper introduces a novel method to price arithmetic Asian options in Levy-driven models, with discrete and continuous averaging, by expanding on the approach of sequential characteristic function recovery. By utilizing frame duality and an FFT-based implementation of density projection, we obtain rapidly converging value approximations to high precision, consistently resulting in a 10 to 100-fold time reduction compared to state-of-the-art procedures. Theoretical convergence rates are confirmed by an in-depth analysis of error propagation. Formulas for Greeks are provided, in addition to generalized averaging and in-progress option pricing.

  • 出版日期2016