  In quantitative finance, we often fit a parametric semimartingale model to
asset prices. To ensure our model is correct, we must then perform
goodness-of-fit tests. In this paper, we give a new goodness-of-fit test for
volatility-like processes, which is easily applied to a variety of
semimartingale models. In each case, we reduce the problem to the detection of
a semimartingale observed under noise. In this setting, we then describe a
wavelet-thresholding test, which obtains adaptive and near-optimal detection
rates.
