Dear Statisticians,
I am having some issues modeling the effect of news events on market indices. Namely, I am using garch (1,1) and have 8 dummy variables each corresponding to different dates.
Ideally, I would like to have something that looks like the following: arch lnfdbra, arch(1/1) garch(1/1) het(Lehman Usbail Icebail Irbail Portbail Spabail Grkbail Cypbail)
The issue is that I get an error message "could not calculate numerical derivatives missing values encountered". r(430)
My procedure so far has been as follows:
First I checked the stationarity using the ADF test. As a result, I took the log first difference of the data and used the akaike information criteria to determine which model best captured the volatility. Garch (1,1) was best and next I tested the residuals for white noise, which indicated that the model was fine. Adding the dummy variable for Lehman works perfectly. However, as soon as I add another variable, I get the error message.
For example:
This works: arch lnfdbra, arch(1/1) garch(1/1) distribution(t) het(Lehman)
This doesn't: arch lnfdbra, arch(1/1) garch(1/1) distribution(t) het(Lehman Usbail Portbail )
When I run the regression with the dummies one by one, I either get good results, negative coefficients, or the error message. How is it possible for the coefficients to be negative (sometimes the values are -1000) and why does the error message appear? Does anybody have any suggestions/solutions to this problem? I would really appreciate any help!
I am having some issues modeling the effect of news events on market indices. Namely, I am using garch (1,1) and have 8 dummy variables each corresponding to different dates.
Ideally, I would like to have something that looks like the following: arch lnfdbra, arch(1/1) garch(1/1) het(Lehman Usbail Icebail Irbail Portbail Spabail Grkbail Cypbail)
The issue is that I get an error message "could not calculate numerical derivatives missing values encountered". r(430)
My procedure so far has been as follows:
First I checked the stationarity using the ADF test. As a result, I took the log first difference of the data and used the akaike information criteria to determine which model best captured the volatility. Garch (1,1) was best and next I tested the residuals for white noise, which indicated that the model was fine. Adding the dummy variable for Lehman works perfectly. However, as soon as I add another variable, I get the error message.
For example:
This works: arch lnfdbra, arch(1/1) garch(1/1) distribution(t) het(Lehman)
This doesn't: arch lnfdbra, arch(1/1) garch(1/1) distribution(t) het(Lehman Usbail Portbail )
When I run the regression with the dummies one by one, I either get good results, negative coefficients, or the error message. How is it possible for the coefficients to be negative (sometimes the values are -1000) and why does the error message appear? Does anybody have any suggestions/solutions to this problem? I would really appreciate any help!
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