The fluctuation of a bilateral exchange rate in a target zone is often chosen as part of official agreements between two or more countries (such as in the European Monetary System - EMS) or of informal unilateral monetary policy packages a country adopts for itself. The defendability of such a regime in the face of asymmetric shocks is always an issue. In this paper, we examine a long period in the life of the EMS and we argue that the increase in volatility in the interest rates could help identifying periods of possible impending crisis for the exchange rates. Our framework provides a way to put to test the quality of the reaction by monetary authorities and to relate perceived weakness to subsequent episodes of realignment in the central parity.

We examine ten years of Italian Lira one month Eurodeposit daily between 1983 and 1993 addressing three empirical questions:

Is interest rate volatility a measure of the perceived degree of vulnerability of the institutional agreements and hence a good predictor of the timing of realignments?

Does the adoption of a new central parity always bring about an immediate increase in the level of credibility?

Are there episodes in which an increase in volatility is successfully countered and hence does not lead to a realignment?

We analyze these questions in the framework of a Markov Switching ARCH model which accomodates the volatility clustering features in the interest rates and the presence of economically interpretable regimes.

We analyze the properties of multiperiod forecasts which are formulated by a number of companies for a fixed horizon ahead which moves each month one period closer and are collected and diffused each month by some polling agency. Some descriptive evidence and a formal model suggest that knowing the views expressed by other forecasters the previous period is influencing individual current forecasts in the form of an attraction to conform to the mean forecast. There are two implications: one is that the forecasts polled in a multiperiod framework cannot be seen as independent from one another and hence the practice of using standard deviations from the forecasts' distribution as if they were standard errors of the estimated mean is not warranted. The second is that the forecasting performance of these groups may be severely affected by the detected imitation behavior and lead to convergence to a value which is not the "right" target (either the first available figure or some final values available at a later time).