  Optimal liquidation of an asset with unknown constant drift and stochastic
regime-switching volatility is studied. The uncertainty about the drift is
represented by an arbitrary probability distribution; the stochastic volatility
is modelled by $m$-state Markov chain. Using filtering theory, an equivalent
reformulation of the original problem as a four-dimensional optimal stopping
problem is found and then analysed by constructing approximating sequences of
three-dimensional optimal stopping problems. An optimal liquidation strategy
and various structural properties of the problem are determined. Analysis of
the two-point prior case is presented in detail, building on which, an outline
of the extension to the general prior case is given.
