jump garch程序


jump garch程序,做跳跃模型

Jump GARCH function evaluation procedures

Jump GARCH function evaluation procedures. jumpGARCH is a function for a standard jump GARCH, while ARJIGARCH is for the ARJI-Garch model of Chan and Maheu(2002), "Conditional Jump Dynamics in Stock Market Returns", JBES, vol 20, no. 3, 377-389. The names of the components are taken from that paper.

kmax, which is the maximum value of jumps to be used in the infinite sum, is a global variable which needs to be set before using either of these procedures. The default is 20.
Note that in evaluating the likelihood, rather than use the standard exp(-lambda) integrating constant for the Poisson, this sums the kernels of the Poisson into wt and divides by that. In effect, this computes the log likelihood conditional on the number of jumps being <= kmax. This should make the estimation less sensitive to the choice of kmax. (Even if the final converged likelihood is unaffected by a slight change in kmax, it's possible for function evaluations for large test values of lambda to produce misleading results if the standard integrating constant is used).

jump_garch.zip (2.11KB)  
jumpgarch.m  jumpgarchfun.m  


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