This study evaluates the effectiveness of using one of the sides of the product to predict daily realized volatility exchange rates the s&p 500 index (spx), the dow jones industry average (djia), the canadian dollar (cad/usd) and the british pound (usd/gbp). Competing models include a simple regression model (srm), a stochastic volatility model with delayed intertemporal dependence (svl), a stochastic volatility model with simultaneous dependence (svc) and a heterogeneous autoregressive model (har). The main goal is to study whether the assumption of asymmetric ratios between profitability zar gbp forecast and volatility and leptocurtosis or modeling the behavior of volatility in long-term memory will lead to an increase in the accuracy of the forecast. When constructing the daily realized volatility, various approaches are considered. Using the realized volatility when evaluating in the sample, the procedure is simple. The famous robust tests of diebold and mariano (1995) are used to investigate whether competing models provide equally accurate predictions. Four different indicators are used to assess the accuracy of forecasting. The results show that the assumption of asymmetric behavior and leptocurtosis does not seem to improve point predictions, while modeling behavior with long-term memory seems to improve.
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