Designing an investment strategy in transition economies is a difficult task, because stock markets opened through time, time series are short, and there is little guidance how to obtain expected returns and covariance matrices necessary for mean-variance asset allocation. Moments of market returns can be expected to be time varying as structural changes occur in nascent market economies. We develop an ad-hoc optimal asset-allocation strategy with a flavor of Bayesian learning adapted to these various characteristics. Since an extreme event often heralds a new state of the economy, we re-initialize learning when unlikely returns materialize. By considering a Cornell benchmark, we show the usefulness of our strategy for certain types of re-initializations. Our model can also be used in situations when new industries emerge or when companies are subject toimportant restructuring.