Forecast of Short Run Nominal Interest Rates in Chile: Complex vs. Naive Models
Abstract
This paper explores the explanatory and predictive capability of one-factor theoretical interest rate modeis and a naive AR(1) model for the short-term interest rate in Chile. The theoretical models outperform the naive alternative: the CKLS model correctly predicts 70% of the time the direction of change in interest rates while the naive model does it only 50% of the time. Moreover, the forecast error for the interest rate is in the range of 0.21% to 0.43% in the theoretical models versus a range of 0.67% to 0.76% in the case of the AR(1) models. Interest rates also display mean reversion.
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