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Specification Tests for Jump-Diffusion Models Based on the Characteristic Function
Goodness-of-fit tests are suggested for several popular jump-diffusion processes. The suggested test statistics utilise the marginal characteristic function of the model and its L2-type discrepancy from an empirical counterpart. Model parameters are estimated either by minimising the aforementioned L2-type discrepancy or by maximum likelihood. A hybrid estimation method that uses moment estimation is also proposed as a standalone method, or to calculate initial points. A fairly extensive Monte Carlo study is conducted in which the performance of a bootstrap version of the new tests is measured against classical specification procedures involving the empirical distribution function. The study concludes with empirical applications on a number of financial assets, as well as an analysis on the impact of misspecification on option pricing.