Autoregressive Conditional Density Estimation
扩展了Engle的自回归条件异方差模型，允许对均值和方差之外的条件依赖进行参数化设定，通过建模条件密度的参数为条件信息的函数，并应用于美国国债超额持有收益率和美元/瑞士法郎汇率数据。
R. F. Engle's autoregressive conditional heteroskedastic model is extended to permit parametric specifications for conditional dependence beyond the mean and variance. The suggestion is to model the conditional density with a small number of parameters, and then model these parameters as functions of the conditioning information. This method is applied to two data sets. The first application is to the monthly excess holding yield on U.S. Treasury securities, where the conditional density used is a Student's t distribution. The second application is to the U.S. Dollar/Swiss Franc exchange rate, using a new skewed Student t conditional distribution. Copyright 1994 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.