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Description:
We examine two approaches characterized by different tail features to extract market expectations on the Mexican peso-US dollar exchange rate. Expectations are gauged by risk-neutral densities. The methods used to estimate these densities are the Volatility Function Technique (VFT) and the Generalized Extreme Value (GEV) approach. We compare these methods in the context of monetary policy announcements in Mexico and the US. Once the surprise component of the announcements is considered, our results indicate that, although both VFT and GEV suggest similar dynamics at the center of the distribution, these two methods show significantly different patterns in the tails. Our empirical evidence shows that the GEV model captures better the extreme values.