What are ARCH & GARCH Models

My favorite time series topic - ARCH and GARCH volatility modeling! Here I talk about the premise behind modeling and the famous class of models that spawned many many adaptations to changing the world of volatility modeling. Of course, all in under 5 minutes!

[rishant]

Wached mit 1 hour video and couldn't understand the concept and you just explained it in 5 mins, amazing

[CleverSmart]

Excellent explanation, that makes the notation much easier to understand. Thank you for this great video and sharing your knowledge

[vadimkorontsevich]

That video had to be recorded...
You and rikvitmath make the best econometrics videos on whole Youtube

[nukeee]

Sweet explanation, loved it! Thank you very much!

[ghada]

Never have I ever seen arch/garch models explained with this level of intuitiveness before. Thanks Prof. I have a few questions tho as this doesn't perfectly look similar to how it's written in textbooks. You explain that in the variance equation for ARCH1 the return variance at time t+1 depends on the lagged squared return (that's the variance) at time t, but isn't reserved for the GARCH model ? Because that's how almost every econometrics textbook explains it. And is the lagged squared "forecasted value" in the variable equation in GARCH as shown in the video, equivalent to the lagged squared error ? Again isn't that supposed to be seen in ARCH? I feel like things got mixed up for me.

[vickdeem]

Mind blowing! Practically made it easy to relearn the ARCH/GARCH framework. Thanks for sharing with us.

[prishaputri]

thank u so much sir, you're such a lifesaver!

[asharablack]

Thanks for these videos, I love the channel!

[jbetanco]

What do you do if the average of the returns are not zero?
Excellent video by the way

[notasan]

Great video. thank you. You explain it well and in a non-boring manner.

So, in the variance formula, the assumption is that it's the population variance with 1/t. for the sample variance with 1/(t-1) this assumption won't work.

[svenunmuig]

Great video! Is it possible to teach something about the Barndorff-Nielsen and Shephard Model?

[quangsonma]

Thank you very much, Profs, for this very handy video. I've been learning the Arch and Garch model and have really been struggling to deal with the notation and expression in the papers. Your way of addressing the problem is really straightforward and inspiring.
Btw, could you pls help me to get a grasp of the residual terms in a GRACH model?. It's been making me confused for some time
As we know, after estimating the parameters of a Garch model, for example, GARCH(1, 1) model. So we can forecast the return of tomorrow's stock by the equation: r_(t+1) = σ _(t+1)* ε_(t+1) where σ _(t+1) is our forecast volatility for tomorrow from our GARCH (1, 1) model and ε_(t+1) is i.i.d from N(0, 1) distribution. That means the forecast return tomorrow is still unknown since ε_(t+1) is a random variable. So where we can get the fitted return for tomorrow and calculate the residual afterward?

[spp]

Hello sir, should we have stationary data for applying GARCH model?

[harrishnandhan]

2:20 Sir how to create these charts?? Do we have to do this in E-views or Excel???

[efepeterman]

Hi
I need a follow up on this.
Point me in the right direction