Maximum likelihood drift estimation for a threshold diffusion
- Antoine, Lejay
- Pigato, Paolo
2010 Mathematics Subject Classification
- 62M05 62F12 60J60
- Threshold diffusion, oscillating Brownian motion, maximum likelihood estimator, null recurrent process, ergodic process, transient process, mixed normal distribution
We study the maximum likelihood estimator of the drift parameters of a stochastic differential equation, with both drift and diffusion coefficients constant on the positive and negative axis, yet discontinuous at zero. This threshold diffusion is called the drifted Oscillating Brownian motion. The asymptotic behaviors of the positive and negative occupation times rule the ones of the estimators. Differently from most known results in the literature, we do not restrict ourselves to the ergodic framework: indeed, depending on the signs of the drift, the process may be ergodic, transient or null recurrent. For each regime, we establish whether or not the estimators are consistent; if they are, we prove the convergence in long time of the properly rescaled difference of the estimators towards a normal or mixed normal distribution. These theoretical results are backed by numerical simulations.