A0601
Title: A goodness-of-fit test for geometric Brownian motion
Authors: Daniel Gaigall - FH Aachen University of Applied Sciences (Germany)
Philipp Wuebbolding - FH Aachen University of Applied Sciences (Germany) [presenting]
Abstract: In the functional data setting, a new goodness-of-fit test is studied for the composite null hypothesis that the data are coming from a geometric Brownian motion. Critical values are easily obtained and ensure that the test keeps the significance level in the finite sample case. In particular, the implementation of the new approach reduces computational effort. In a comprehensive simulation study, the novel test compares favorably against competitors. An obvious application is for testing financial data, whether the Black-Scholes model applies. For illustration, data examples are provided for different stock and interest rate time series.
