Abstract
The presence of structural breaks in the analysis of volatility in the financial field has been ignored in research done in Latin America. This paper fills this gap by analyzing the behavior of the dollar exchange rate in Peru by evaluating the impact of structural breaks in volatility forecasting. The return behavior was analyzed for the period 05/01/2010 to 09/30/2021. Econometric analysis was used, which consisted of: (1) use of the modified Iterative Cumulative Sum of Squares (ICSS) algorithm to determine the structural breakpoints; (2) estimation of GARCH Models for the subsamples originated by the identified breakpoints; and (3) comparison of alternative models with the GARCH(1,1) expanding window model for horizons of 1, 20, 60 and 120 days. The ICSS algorithm identified 8 breaks in volatility behavior. The models were compared based on out-of-sample forecast performance. It was determined that the GARCH model that considers structural breaks is only effective for a one-day horizon. Finally, the GARCH(1,1) 0.25 rolling window model provides a better strategy for forecasting the volatility of exchange rate returns in Peru for longer horizons.
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