Hello, I have a few questions concerning the DCC-GARCH model and its programming in R. So here is what I want to do: I take quotes of two indices - S&P500 and DJ. And the aim is to estimate coefficients of the DCC-GARCH model for them. This is how I do it: library(tseries) p1 = get.hist.quote(instrument = "^gspc",start = "2005-01-07",end "2009-09-04",compression = "w", quote="AdjClose") p2 = get.hist.quote(instrument = "^dji",start = "2005-01-07",end "2009-09-04",compression = "w", quote="AdjClose") p = cbind(p1,p2) y = diff(log(p))*100 y[,1] = y[,1]-mean(y[,1]) y[,2] = y[,2]-mean(y[,2]) T = length(y[,1]) library(ccgarch) library(fGarch) f1 = garchFit(~ garch(1,1), data=y[,1],include.mean=FALSE) f1 = f1@fit$coef f2 = garchFit(~ garch(1,1), data=y[,2],include.mean=FALSE) f2 = f2@fit$coef a = c(f1[1], f2[1]) A = diag(c(f1[2],f2[2])) B = diag(c(f1[3], f2[3])) dccpara = c(0.2,0.6) dccresults = dcc.estimation(inia=a, iniA=A, iniB=B, ini.dcc=dccpara,dvar=y, model="diagonal") dccresults$out DCCrho = dccresults$DCC[,2] matplot(DCCrho, type='l') dccresults$out deliver me the estimated coefficients of the DCC-GARCH model. And here is my first question: How can I check if these coefficients are significant or not? How can I test them for significance? second question would be: Is this true that matplot(DCCrho, type='l') shows conditional correlation between the two indices in question? and the third one: What is actually dccpara and why do I get totally different DCC-alpha and DCC-beta coefficients if I change dccpara from c(0.2,0.6) to, let's say, c(0.01, 0.98) ? What determines which values should be chosen? Hopefully someone will find time to give me a hand. Thank you very much in advance, people of good will, for looking at/checking what I wrote and helping me. Best regards Marcin [[alternative HTML version deleted]]
Hello, I have a few questions concerning the DCC-GARCH model and its programming in R. So here is what I want to do: I take quotes of two indices - S&P500 and DJ. And the aim is to estimate coefficients of the DCC-GARCH model for them. This is how I do it: library(tseries) p1 = get.hist.quote(instrument = "^gspc",start = "2005-01-07",end "2009-09-04",compression = "w", quote="AdjClose") p2 = get.hist.quote(instrument = "^dji",start = "2005-01-07",end "2009-09-04",compression = "w", quote="AdjClose") p = cbind(p1,p2) y = diff(log(p))*100 y[,1] = y[,1]-mean(y[,1]) y[,2] = y[,2]-mean(y[,2]) T = length(y[,1]) library(ccgarch) library(fGarch) f1 = garchFit(~ garch(1,1), data=y[,1],include.mean=FALSE) f1 = f1@fit$coef f2 = garchFit(~ garch(1,1), data=y[,2],include.mean=FALSE) f2 = f2@fit$coef a = c(f1[1], f2[1]) A = diag(c(f1[2],f2[2])) B = diag(c(f1[3], f2[3])) dccpara = c(0.2,0.6) dccresults = dcc.estimation(inia=a, iniA=A, iniB=B, ini.dcc=dccpara,dvar=y, model="diagonal") dccresults$out DCCrho = dccresults$DCC[,2] matplot(DCCrho, type='l') dccresults$out deliver me the estimated coefficients of the DCC-GARCH model. And here is my first question: How can I check if these coefficients are significant or not? How can I test them for significance? second question would be: Is this true that matplot(DCCrho, type='l') shows conditional correlation between the two indices in question? and the third one: What is actually dccpara and why do I get totally different DCC-alpha and DCC-beta coefficients if I change dccpara from c(0.2,0.6) to, let's say, c(0.01, 0.98) ? What determines which values should be chosen? Hopefully someone will find time to give me a hand. Thank you very much in advance, people of good will, for looking at/checking what I wrote and helping me. Best regards Marcin [[alternative HTML version deleted]]
Hello, I have a few questions concerning the DCC-GARCH model and its programming in R. So here is what I want to do: I take quotes of two indices - S&P500 and DJ. And the aim is to estimate coefficients of the DCC-GARCH model for them. This is how I do it: library(tseries) p1 = get.hist.quote(instrument = "^gspc",start = "2005-01-07",end "2009-09-04",compression = "w", quote="AdjClose") p2 = get.hist.quote(instrument = "^dji",start = "2005-01-07",end "2009-09-04",compression = "w", quote="AdjClose") p = cbind(p1,p2) y = diff(log(p))*100 y[,1] = y[,1]-mean(y[,1]) y[,2] = y[,2]-mean(y[,2]) T = length(y[,1]) library(ccgarch) library(fGarch) f1 = garchFit(~ garch(1,1), data=y[,1],include.mean=FALSE) f1 = f1@fit$coef f2 = garchFit(~ garch(1,1), data=y[,2],include.mean=FALSE) f2 = f2@fit$coef a = c(f1[1], f2[1]) A = diag(c(f1[2],f2[2])) B = diag(c(f1[3], f2[3])) dccpara = c(0.2,0.6) dccresults = dcc.estimation(inia=a, iniA=A, iniB=B, ini.dcc=dccpara,dvar=y, model="diagonal") dccresults$out DCCrho = dccresults$DCC[,2] matplot(DCCrho, type='l') dccresults$out deliver me the estimated coefficients of the DCC-GARCH model. And here is my first question: How can I check if these coefficients are significant or not? How can I test them for significance? second question would be: Is this true that matplot(DCCrho, type='l') shows conditional correlation between the two indices in question? and the third one: What is actually dccpara and why do I get totally different DCC-alpha and DCC-beta coefficients if I change dccpara from c(0.2,0.6) to, let's say, c(0.01, 0.98) ? What determines which values should be chosen? Hopefully someone will find time to give me a hand. Thank you very much in advance, people of good will, for looking at/checking what I wrote and helping me. Best regards Marcin [[alternative HTML version deleted]]
Dear Marcin, This document should clarify your questions: http://www.google.be/url?sa=t&rct=j&q=ccgarch%3A%20an%20r%20package%20for%20building%20multivariate%20garch&source=web&cd=1&ved=0CCMQFjAA&url=http%3A%2F%2Fhhs.diva-portal.org%2Fsmash%2Fget%2Fdiva2%3A320449%2FFULLTEXT02&ei=8V1GT_uDDcLq8QOWyqSwDg&usg=AFQjCNE36DZu4qWOK-5AlZXhlDaT_sZ1sg&sig2=Z-dnG2bprPpL1FxtAuUCeA -- View this message in context: http://r.789695.n4.nabble.com/DCC-GARCH-model-tp3524387p4414223.html Sent from the R help mailing list archive at Nabble.com.
Hello Marcin, did you get the answer to your questions. I have the same questions and would appreciate your help if you found the answers. Thanks, Ankur -- View this message in context: http://r.789695.n4.nabble.com/DCC-GARCH-model-tp3524387p4634776.html Sent from the R help mailing list archive at Nabble.com.