Noise Created Through the Interactions of Arbitrageurs and Noise Traders in the FOREX Market. An Analysis Based on ARCH, GARCH, TGARCH and EGARCH Models

In this article, we have tested the volatility of the returns of the spot exchange rate of EURO/USD, the returns of a real exchange rate index and the money supply, (M1), for changing conditional variances. Autoregressive Conditional Heteroskedastic models (ARCH), Generalized Autoregressive Conditional Heteroskedastic models, (GARCH), Threshold GARCH, (TGARCH) and exponential, (EGARCH) models take into account the non-linearity that arises in financial time series. In this article, we are not testing the regressive relationship between exchange rate volatility and macroeconomic indicators such as the money supply, interest rates, and real GDP. We have checked the volatility clusters for a long period of time that arises in the financial times series of returns or the fact that large and small values occur persistently in clusters. In other words, we have concluded that negative shocks implied a higher next period conditional variance than positive shocks of the same extent. The asymmetry terms are highly statistically significant by using the family of autoregressive models. We have found that there is a significant positive and negative volatility clusters, which confirms the ARCH and GARCH, TGARCH and EGARCH effect on the time series of the EURO/USD spot rate, based on the F-statistic, the Lagrange Multiplier, (LM), the leverage effect, the Jarque – Bera normality tests. The data that we have used are monthly returns starting from 01/01/2000 to 01/01/2013, which total to 156 observations. The data was obtained from the Federal Reserve Statistical Release Department and the symbols of the series are H.10 and H.6