Thank you so much for such a thorough and easy to understand explanation of garch modelling in R! It is so helpful, even 6 years after you have uploaded this video
These videos are like portals. I know the views are not that high, but please do not ever stop doing them - we assure you that you are helping students from around the world in ways and measures you do not imagine.
I sense we should all go for a beer one day as like-minded people and remember the times where we probably over-estimated our ability to implement M-GARCH models =)
Thank you sir for nice explanation I have a query how to see the impact of some exogenous variable X on the correlation of different assets in dcc garch model in R
how can I estimate out-of-sample forecast and what is the difference between ugarchboot, ugarchforecast and ugarchroll. Also how to estimate the RMSE for the models.
Dear Ralf, nice explanations and tips for Multivariate GARCH models. Thanks. I am facing a "matrix multiplication: problem with matrix inverse; suggest to use solve() instead" while dccfit. Any suggestion?
Dear Dr. Ralf, Thank you for this video. I would like to ask you how can we validate GARCH model and calculate RMSE ANS MAPE of GARCH MODELS TO DO A COMPARISON WITH OTHER MODELS such as ARIMA?
Hi. A GARCH model does not produce an RMSE over the values of a time series. The GARCH models the volaility of a series (how confident are we that the point forecast we estimated is within a certain range). The point forecast itself is still found by setting up an ARIMA model.
Dear Dr. Ralf, Thank you for this video. I would like to ask you how can I find Value at Risk and Expected Shortfall of Multivariate GARCH Model , Can you show me by Code R Thank you for helping me to do my master' Thesis.
As i understand it the covariance matrix is computed ex-post, is there also a function for calculating ex-ante through the coefficients estimated and compare with the realized? Or do i need to do it manually?
I saw a paper on the net indicating that we could estimate the Beta of a stock/portfolio. I do not see at all the link between the CAPM and the Garch model. can someone could explain ?
Hi, great video! Can anyone help me to replicate this DCC-GARCH model but with a VAR model for the conditional mean equation? Not sure how to implement this...
Hi! I am using a daily data in a CSV file but each time I run the as.xts command, the date that comes with the graph starts from 1970. How do I correct it so that the date starts from the 2015-01-08, which is the start date of my data. Thanks!
Is there a way to plot the variance estimated by GARCH and OLS in one graph? I would like to graphically compare the estimations in R, however, I only know how to graph the variance of the GARCH model.
Dear, We use our own excel data set, and since this is another way of importing data, could you please tell us how to convert it to times series data? Such that our variables also have the xts value? Thank you in advance!
How would you add external regressors to the univariate garch variance equation? I have three time series, I estimated them employing GARCH(1,1) for each of them, and I want to add lagged residual and variance of one series to another's conditional variance equation and I dont know how to do that. Thank you very much.
Great Videol sir, I really have learnt a lot, but how do I go about estimating the parameters of a Gargh(1,1) model assuming a Generalized Logistic regression? Please I need help
Thank you so much for this video. I have one question: Do you know how I can put external regressors into DCC Garch model? Xreg seems not to work (. In univariate Part of Garch xreg works, but unfortunately not in multivariate part. Maybe someone can help me. Thanks )
Good evening, i have a problem. When i run "fit1 = dccfit(spec1, data = rX, fit.control = list(eval.se = TRUE), fit = multf)" for the model estimation it returns to me: What should i Do?
In case this problem affects someone else in the future: I managed to solve it by installing the package Rcpp. With this package loaded, the code seems to work without issues. Code: install.packages('Rcpp') library(Rcpp)
i have question, when i am predicting variability stock use GARCH-GJR and want check with errors i must use calculated variability use GARCH-GJR or calculated normall standard deviation? I forercasting also with use GARCH, GJR-GARCH, IGARCH, EGARCH, GARCH, and GARCH - M, and i have problem with this what variability use to compare and calculated errors. Sorry for my english ;)
I am not 100% sure I understand what you are after, but I think you want to know which of the different models you ought to use. You evaluate GARCH models by looking at the standardised residuals (residuals / sqrt(var)). When you plot the estimation results you get some specification tests on these. Basically you want to use the simplest model that passes these tests.
Thank you for this very useful tutorial! However, I couldn't figure out by myself how to implement the asymmetric dcc model. Could you help me with this please?
I think this is the way to go: spec1 = dccspec(uspec = uspec.n, dccOrder = c(1,1), model = "aDCC", distribution = 'mvnorm'). However when I tried this for replicating results from a paper, I didn't get the correct results, which I did get for the normal DCC model.
