Modeling Heteroscedasticity in Daily Foreign-Exchange Rates
用10年日数据对五种货币估计ARCH和GARCH模型，发现这些模型通常能消除所有汇率变化的异方差性，并指出特定非正态分布下的指数GARCH对加元拟合极好。
This article estimates autoregressive conditionally heteroscedastic (ARCH) and generalized ARCH (GARCH) models for five foreign currencies, using 10 years of daily data, a variety of ARCH and GARCH specifications, a number of nonnormal error densities, and a comprehensive set of diagnostic checks. It finds that ARCH and GARCH models can usually remove all heteroscedasticity in price changes in all five currencies. Goodness-of-fit diagnostics indicate that exponential GARCH with certain nonnormal distributions fits the Canadian dollar extremely well and the Swiss franc and the deutsche mark reasonably well. Only one nonnormal distribution fits the Japanese yen reasonably well. None fit the British pound.