QuoteOriginally posted by: buckeyeI am trying to implement an Autoregressive Conditional Duration model. According to a paper by Noble Laureate Robert Engle and Joe Lange, the ACD model is given as:EPTIME (t) = omega + alpha1 * PTIME(t-1) + beta1 * EPTIME(t-1) - (A), andEPTIME (t) = omega + alpha1 * PTIME(t-1) + beta1 * EPTIME(t-1) + gamma * spread(t-1) - (B)To estimate parameters omega, alpha, and beta in (A), I use a simple GARCH(1,1) model. How do I incorporate the additonal exogenous lagged variable Spread in (B). I am a newbie and don't know how to do this regression (I am using statistical package Eviews and R, and can get access to Matlab if it is more convenient in Matlab).Any help will be highly appreciated.Thanks.PS: The paper is "Measuring, Forecasting and Explaining Time Varying Liquidity in the Stock Market" by Robert Engle and Joe LangePlease be aware that Garch estimation function for ACD models only works when sample size goes to infinity and when the distribution assumption for the model is the exponential (simplest case).I ahve worked with ACD models in the past and I published some codes for estimations:Rmetrics - fACD packageMatlabIn this packages you can extend the duration process with independent variables so it should work for you.
Last edited by msperlin
on June 15th, 2010, 10:00 pm, edited 1 time in total.