Testing the effects of oral interventions on the covariance of exchange rates in a state-of-the-art computational environment

In the last decade, both Federal Reserve System (FED) and European Central Bank (ECB) abandoned direct market interventions and relied on communication as their main policy tool to affect exchange rates. This paper investigates the impacts of officials’ statements (oral intervention) on the covariance of the EUR/USD and JPY/USD. Using generalized autoregressive conditional heteroscedasticity (GARCH) model’s diagonal vector error correction (DVEC) representation, we find that strengthening oral interventions in US and Japan decrease while in Eurozone increase the covariance between EUR/USD and JPY/USD. Also reversely, weakening oral interventions in US and Japan increase while in Eurozone decrease the covariance. Since oral interventions are explanatory variables of the conditional covariance structure of G3 currencies (USD, EUR and JPY), ignoring oral interventions may cause errors in foreign exchange (forex) covariance forecasts. During the estimation procedure, we use a different approach than the commonly practiced in the literature. We solve the resulting optimization problem from maximum likelihood estimation (MLE) of DVEC model in two steps: first by genetic algorithm (GA) and then by sequential quadratic programming (SQP) algorithm. Furthermore, to land at a better local optimal, the experiments are conducted in NEOS Servers1 . Comparing our results with those of benchmark S+ GARCH module (a commercial software), we find that our approach yields much higher objective value than the benchmark does. Hence, we conclude that our computational methodology provides substantial improvement to in-sample forex covariance forecasting. Our results have applications in portfolio management as well.