Stock Forecasting with GARCH : Stock Trading Basics

How do you use the GARCH model in time series to forecast the volatility of a stock?

Code used in this video:

Theory of GARCH video:

Coding in GARCH video:

[MildlyAmusingComedyC]

By far the best time series related videos available on YouTube! Keep it up!

[spytheman]

Did some testing using GME, using ARCH(2, 0):

Prior to the WSB army,

1) if we incorporate the whole data from same start date as ritvik to 2021 Jan 13th when we first witness the spike, the volatility prediction for the next 7days predict that volatility should move lower subsequently.

2)training from same start date to any dates after that, it always predict volatility to be lower the next 7 days!

Thats why stock market is so tough ...

[cristipopescu]

So clearly explained. Thanks a lot for your work, it really helped me understading the GARCH model!

[paul-edou]

Great content, as always. My grain of salt: it would be more relevant to plot the forecast vs actual volatility rather than vs return

[yourswimpal]

for ritvikmath, i click like before even watching the entire video cause I know it will be good. (prediction using ARCH on average like percentage :p )

[pulkitnijhawan]

Thanks bro..can you please make more videos on stock

[Art_Blue_Liberalism]

Very precisely explained material. Thanks!

[adityakadrekar]

Hey Ritvik, thanks for posting this video. I have some questions:
1. Why are you using the pacf plot of the 'square of returns' and not just the returns?
2. From my understanding, PACF plots help you understand the Auto regressive term which is p in this case. How do you determine the lag of the volatility (q)? I am not sure to follow why did you take q as 3 after plotting the PACF chart.

[MusicMonster]

This is pure gold! Awesome video. Could you show us EWMA volatility in a similar fashion through pandas too and the determination of Lambda?

[ManmeetKaur-xvmh]

You are simply great, Please make more videos on stock market course.

[Raven-bixn]

In your arch video, you said that you'd try to fit the best model you can and fit arch/garch with the residual. So, what not using ARMA model here first and then apply garch to the residual?

[dinhnguyenvo]

Dear Ritvikmath, I am grateful for your work, I have learned a lot. Thank you so much. Can you do a ARMA-GARCH model with stock forecasting?

[nukeee]

Awesome, awesome tutorial, thanks for taking the time to do it and sharing!

One quick question though: if I understand correctly, ARCH/GARCH basically are used to predict volatility (which is variance - in the financial case the 'squared returns') but we are actually using the returns (being the daily percentage change in stock prices) as data to feed the ARCH/GARCH models. Is this correct?

Thank you again!

[เกี๊ยวอย่างเดียว]

SUBSCRIBED !! The best python + time series model !!

[droga]

I'd like to see the difference between the predicted vol and the actual vol.
Also, the orange line is always lagging in making predictions, so I don't know why would it be useful for.
Anyway, interesting. I don't know shit about coding, but I know about how the markets behave.

[taskmaster]

Great video mate. I appreciate your work.

[mogli]

This was great and very simple to understand...!!! Could you please explain the TBATs model as well the same way

[abhirajmandal]

hello hi, how did u find the value of q in GARCH model, from the pacf plot i understand it to be an ARCH (3 ) model, but how did u say that its a GARCH(3, 3) model, could u have used an ARCH(3, 0) model

[hardbass_crew_hauptschule]

at 4:40 you say that the predicted volatiry gets higher exactly when the returns get more jumpy. But to me it looks like the line is really just following the blue line and lagging behind, which seems to indicate overfitting. How do we know this prediction is any good?

[drakecody]

I'm curious to know why you did not use the pyflux library? Do you think your approach is better?