Hello Everyone! Thanks for your support! ✅ Buy the material of the video: Slides+EViews workfile with instructions and results: payhip.com/b/R2EbW 📈 Download the dataset for free and replicate the content of the video: www.jdeconomics.com/eviews-tutorials/arch-models-in-eviews ✅ Visit my website to see all my FREE tutorials: www.jdeconomics.com ✅If you haven't subscribed to my channel yet, feel free to do so clicking: ruclips.net/channel/UC5P21WGFO4WRUlAiGLcwymg Thanks a lot for your support! JD Economics.
Sir thank you so much for sharing with us. I really appreciate it. I have a question. When you checked with 1 lag the result was appropriate• Again when you checked with lag 2; again result was approprite. So why you selected ARCH (2 ) over ARCH (1 ) ls there any specific reason or you selected it randomly
Thanks for your comment. It was based on the existence of arch effects and also based on the information criterions. Next week I will post a video with the details.
You are doing great job! Thank you again for your help. Did you upload the new video you wrote me about? It's gonna be very helpful for us. One more request! Make a video on MGARCH including it's types with different examples please....
Hi, thanks so much for sharing this material, very informative indeed. May I ask, if there are still lags after estimating the equation, what is the next step. Thanks again.
Great tutorial. One question: do all the variables in the mean equation have to be stationary? Or can the dependent variable be non-stationary, while having a lagged version of that variable on the right side of the equation as a control for the auto-correlation present in the dependent variable?
Hello Daniele, Thanks for your message. I have in mind two videos next. One about GARCH models, and another about ARCH tips. I will spend some more minutes talking about model diagnostics, and how changing the orders of ARCH effects can create some issues. I may get into multivariate garch models, but won't be shortly. I have many topics still to cover. Thanks for the input though! I will add it to my list. Feel free to check my website if you haven't. I launched it some weeks ago and have organized the information a bit better. Regards, JD!
Thanks 👍 But Question is : 5:01 How Errors are Normally Distributed,If Heterocadasticity Exists i.e Errors Variance is not Constant or is Increasing ? Or is it Better to Switch to Some other Distribution
Hi, thanks for your comment. Distribution not need to be normal necessarily. We assume a normal distribution, BUT with changing variance. That’s the central part of Arch models. You have a variance changing over time. Regards, Jd
Thanks! I will do one about Garch shortly, so feel free to subscriber to my channel to get notified. Also, check my arch article at www.jdeconomics.com/how-to-estimate-arch-models-in-eviews/ good luck!
@@JDEconomics I saw your page, you have paid tutorials. if you did some garch tutorial and I could insert several companies and equal independent variables (a panel data garch) it would be very interesting (I would definitely pay for this tutorial- panel data garch)
@@daiane_2310 hi Daiane. Thanks four your message. I will post the video hopefully within 2 weeks. It does take time to make the slides, find the data, make the model, film, edit, post. Thanks again!
Great videos numero uno latest fresh crisp and most suited for celebrating Xmas and happy new year in cosy confines of sweet home thanks to environmental waves forcing us indoors, but learning lessons for sure to stop us from contracting dementia thanks for your yeoman efforts bro
Good evening sir, I need your help in garch model. I have emailed you the same. If you can it will be my pleasure. If you have computed these arch values in your video also kindly provide me the value so i can understood properly.
WHY IS BACKCAST PARAMETER SET TO 0.7, WHY NOT ANY OTHER VALUE LESS THAN 1.0, SAY 0.6 OR 0.5, OR 0.4, WHAT IS LOGIC OF SETTING AT 0.7 IN ARCH EFFECT 2 TESTING??
@@JDEconomics if I have returns of 2 different stocks would you have any tips to estimate an arch model with the aim of proving a contagion effect between the two.
Hello Everyone! Thanks for your support!
✅ Buy the material of the video: Slides+EViews workfile with instructions and results:
payhip.com/b/R2EbW
📈 Download the dataset for free and replicate the content of the video:
www.jdeconomics.com/eviews-tutorials/arch-models-in-eviews
✅ Visit my website to see all my FREE tutorials:
www.jdeconomics.com
✅If you haven't subscribed to my channel yet, feel free to do so clicking:
ruclips.net/channel/UC5P21WGFO4WRUlAiGLcwymg
Thanks a lot for your support!
JD Economics.
Excellent work. For me very helpful in learning and understanding the concept with practical example.
Glad it was helpful!
at 11:33 please explain what do you mean by "non-stationary in levels" and "stationary in differences"?
very well explained. wonderful. thanks for sharing this knowledge
Thanks for you feedback! Make sure to check my website. Regards, JD
Thanks so much sir. I really appreciate your all videos.
Thanks! Feel free to check out my website: www.jdeconomics.com
Regards,
JD
Great video! thank you!!!
Thanks!
Sir thank you so much for sharing with us. I really appreciate it. I have a question. When you checked with 1 lag the result was appropriate• Again when you checked with lag 2; again result was approprite. So why you selected ARCH (2 ) over ARCH (1 ) ls there any specific reason or you selected it randomly
Thanks for your comment. It was based on the existence of arch effects and also based on the information criterions. Next week I will post a video with the details.
You are doing great job! Thank you again for your help. Did you upload the new video you wrote me about? It's gonna be very helpful for us. One more request! Make a video on MGARCH including it's types with different examples please....
Thanks your videos are best
Thanks a lot! Kind Regards, JD
Excellent, you helped me thank you
Glad it helped!
Hi, thanks so much for sharing this material, very informative indeed. May I ask, if there are still lags after estimating the equation, what is the next step. Thanks again.
Great tutorial. One question: do all the variables in the mean equation have to be stationary? Or can the dependent variable be non-stationary, while having a lagged version of that variable on the right side of the equation as a control for the auto-correlation present in the dependent variable?
Hey! As long as you have a mean equation, it can be any methodology. If you estimated a mean equation model that is solid, go ahead! Cheers
Great lecture, one word great!
Thanks a lot ! Make sure to check my website: www.jdeconomics.com and feel free to share it with your friends! I wish you good luck! JD
Thanks for the great videos! Are you planning to upload any video about Panel regressions? I hope you will! your explantions are simply excellent!
Thanks Dudi! I am not sure yet, I am currently publishing DSGE models videos. Thanks again for your kind comment. Regards, JD
So Modelling ARCH is simply accounting for Heteroskedasticity in the model?
You are trying to model the true behaviour of the variance of the model.
@@michaelasare4987 yes, you are trying to model the variance.
@@JDEconomics Thank
Thank You Sir. For sharing the video. Can you please share Video on Multivariate GARCH MODEL ,Spill Over Effect or DCC garch
Will add it to the list of future videos. Thanks for your suggestion. Regards, JD
Hi Juan! Great video! Please keep up with this. Just wondering, will you be treating multivariate garch models (VECH and BEKK)?
Hello Daniele, Thanks for your message. I have in mind two videos next. One about GARCH models, and another about ARCH tips. I will spend some more minutes talking about model diagnostics, and how changing the orders of ARCH effects can create some issues.
I may get into multivariate garch models, but won't be shortly. I have many topics still to cover. Thanks for the input though! I will add it to my list. Feel free to check my website if you haven't. I launched it some weeks ago and have organized the information a bit better.
Regards, JD!
@@JDEconomics Thank you Juan. I'll make sure to check your website regularly. Thanks again for your work!
@@danielefraietta9904 My Pleasure! Take care.
Thanks 👍
But Question is :
5:01 How Errors are Normally Distributed,If Heterocadasticity Exists i.e Errors Variance is not Constant or is Increasing ?
Or is it Better to Switch to Some other Distribution
Hi, thanks for your comment. Distribution not need to be normal necessarily. We assume a normal distribution, BUT with changing variance. That’s the central part of Arch models. You have a variance changing over time. Regards, Jd
Thank you , very informative. Can you do some videos related to GARCH and ARDL Models too.
Thanks! I will do one about Garch shortly, so feel free to subscriber to my channel to get notified. Also, check my arch article at www.jdeconomics.com/how-to-estimate-arch-models-in-eviews/
good luck!
@@JDEconomics I'm coming to your RUclips page every day waiting for the garch video.
@@JDEconomics I saw your page, you have paid tutorials. if you did some garch tutorial and I could insert several companies and equal independent variables (a panel data garch) it would be very interesting (I would definitely pay for this tutorial- panel data garch)
@@daiane_2310 hi Daiane. Thanks four your message. I will post the video hopefully within 2 weeks. It does take time to make the slides, find the data, make the model, film, edit, post. Thanks again!
@@JDEconomics thank you! I used “ECONOMATICA” for database
EXCELLENT BRO
Most welcome! Happy holidays, JD
Great videos numero uno latest fresh crisp and most suited for celebrating Xmas and happy new year in cosy confines of sweet home thanks to environmental waves forcing us indoors, but learning lessons for sure to stop us from contracting dementia thanks for your yeoman efforts bro
Sir my correlogram shows ar and ma 16 as significant. Can this be taken for further calculation?
You can try, but keep it simple. As I said in the video a garch 1,1 model normally fits most of the series with a non constant variance. Regards.
WHAT IS THIS BACKCAST PARAMETER ROLE? WHAT IT DOES? WHY IT DOES? AND PRACTICAL SIG IN MODELLING? MEANING AND INTERPRETATION PLEASE?
Wonderful Class Sir. I am highly grateful. Utmost Regards
Thanks for your feedback! Feel free to check my website for more tutorials and all the content! Best regards, JD
mean equation of TSXt ? or Returns? I think it should be Retruns. please rectify me.
Its of returns, and I have used returns. Good luck!
Good evening sir, I need your help in garch model. I have emailed you the same. If you can it will be my pleasure. If you have computed these arch values in your video also kindly provide me the value so i can understood properly.
I answered your email. Regards, JD
if you want to watch the garch video too go to that video that involves arch too.
WHY IS BACKCAST PARAMETER SET TO 0.7, WHY NOT ANY OTHER VALUE LESS THAN 1.0, SAY 0.6 OR 0.5, OR 0.4, WHAT IS LOGIC OF SETTING AT 0.7 IN ARCH EFFECT 2 TESTING??
If your data does not show any arch effects does that mean you cannot estimate an arch model from it?
It means you may not need to model the variance
@@JDEconomics if I have returns of 2 different stocks would you have any tips to estimate an arch model with the aim of proving a contagion effect between the two.