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setting persistence upper limit in garchFit()
3 messages · wc90024-email at yahoo.com, Patrick Burns, Brian G. Peterson
I don't know the answer to your question, but I have a guess of what your data are like. The sum of the two parameters in garch(1,1) is essentially telling you the time it takes for the volatility from a shock to damp down. If there is a trend in the volatility over the time frame of the data, then the estimation is likely to "think" that it hasn't seen the volatility damp down -- hence an infinite waiting time and a sum of the parameters more than 1. More data can often help the problem. Another piece of software whose existence I'm doubtful of would be a Bayesian estimate of the model. Patrick Burns patrick at burns-stat.com +44 (0)20 8525 0696 http://www.burns-stat.com (home of "The R Inferno" and "A Guide for the Unwilling S User")
wc90024-email at yahoo.com wrote:
I'm using garchFit() on a volatile time series. I'd like to set a limit such that the SUM(alpha, beta) < 1. Is there a way to configure that by passing a parameter into garchFit()? Or is there another way to do it? Thanks. [[alternative HTML version deleted]] ------------------------------------------------------------------------
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Patrick Burns wrote:
I don't know the answer to your question, but I have a guess of what your data are like. The sum of the two parameters in garch(1,1) is essentially telling you the time it takes for the volatility from a shock to damp down. If there is a trend in the volatility over the time frame of the data, then the estimation is likely to "think" that it hasn't seen the volatility damp down -- hence an infinite waiting time and a sum of the parameters more than 1. More data can often help the problem. Another piece of software whose existence I'm doubtful of would be a Bayesian estimate of the model.
http://cran.r-project.org/web/packages/bayesGARCH/index.html perhaps? - Brian
Brian G. Peterson http://braverock.com/brian/ Ph: 773-459-4973 IM: bgpbraverock