Abstract
This work develops a comparison between the volatility prediction of traditional time series models (ARIMA, EGARCH and PARCH), against two new proposed models based on fuzzy theory (FTSFuzzy ARIMA Tseng’s and FTS-Fuzzy ARIMA Tanaka’s). To make this comparison, we estimated
the Mexican peso - US dollar exchange rate yield from January 2008 to December 2017. Our main result is that the models based on fuzzy theory generate a better estimate of the volatility. The fuzzy models show a smaller least forecast error than the traditional time series in both; in and out of sample tests; for the volatility in the yield of the Mexican peso – US dollar exchange rate. Therefore, the fuzzymodels showed higher efficiency and better reflects the market information.
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