Non-asymptotic statistical test of the covariance matrix rank of a 2-dimensional SDE
The aim of this work is to develop a testing procedure which determines the rank of the noise in a two-dimensional stochastic process from discrete observations of this process on a fixed time interval $[0,T]$ sampled with a fixed time step $\Delta$. First, we construct the main statistics of the test, given by a random matrix determinant, as proposed in Jacod et Podolskij (2013). We show that the performance of the test based on this statistics is limited in a non-asymptotic setting, when $\Delta$ is fixed.