VAR Model in Python : Time Series Talk

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How to code the Vector Auto Regression (VAR) model in Python and interpret the results!

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You are the best :) I am studying the relationship between air pollutants and human health in Mexico, and your explanations are way too good for us the students. Great work!

jbenavidesv

YOU MAY HAVE JUST SAVED MY ENTIRE MASTERS THESIS. thank you.

curation

This is great! Would be nice if you could do a part 2 vid on the forecasting with VAR (following this example). How do we sort the training / test data so that they select the preferred lag as in the final model? Also what's the interpretation of Correlation matrix of residuals at the end of the summary result mean?

meanreversion

@ritvikmath
In this code, no code has been written for the prediction values of this VAR model ?? Additionally, we'll have to split the data into train and test to find the root mean square and MAPE to find the accuracy of the model. Could you please include that in your code also., it will be very helpful for us. Thank You

kaustubhsrivastava

Gosh..this 8 minute video totally crush it. Got more out of this than any other book/video on VAR.

vhphan

LIVE LEGENE! You are killing it for explaining coding and model in the simplest and most efficient way possible. Really appreciate your work!!

chenstephen

Thank you so so much for this video, I had been currently struggling while working on VAR and now you upload this ❤️

kaustubhsrivastava

Hello!
I have a question about the end of the video - how can you say that the model is
I understand that you pick only the significant lags, but the VAR function calculates the coefficients assuming you took all the lags. if you take only the significant ones, then you have to find new coefficients, don't you?
for example, if I decide to leave lag 13 out of my model for any reason, then the coefficients of lag 1 and lag 2 would have to be different, wouldn't they?
thanks in advance!

avrahamturgeman

Hi. I love the way you explain concepts simply for easy understanding. Kudos. Could you please, do a video on transforming a VAR model into Moving average for impulse response calculations? I currently have some challenge with the process. Thanks in advance!

patrickonodje

I watched all your videos with pleasure, you are great 👏I will ask you a question for the first time, I am doing a project with the varmax method, but since I have hourly data in the estimation of the number of rail system passengers, I think it causes noise both annually and seasonality during the day, how can I overcome this problem. Also, my prediction variable is not normally distributed, do I need to do anything for this? Otherwise, Should I do deep learning methods?

TheSerbes

Simple and very interesting .. Thank You

Ibraheem_ElAnsari

Thank you for this video. It really made it very simple and understandable for me. I just have a bit of a follow up questions....
When applying, I realized building the right model based on what you suggest here (picking the significant ones) is not really correct since you are simply dropping the rest of the variables. Doesn't that create a problem? Shouldn't we re-regress and find coefficients again for the significant set of variables with lags from VAR results? Please elaborate...

morahmani

Very nice, but why didn't you apply the predictor equation to show how well it works? But, great video in any case!

mathman

Thank you very much, very good teaching!

serdarufukkara

Wonderful channel! It really helps me a lot. Really appreciate! Thank you so much from Taiwanese student.

eric

Thanks for the video. :) The same equation will be used to predict Ice- cream as well. Same lag values?

shipragupta

Great video, but why do you use a VAR model? The model you ended up with didn’t seem to make use of its benefits.
I’m really new to VAR models, so correct me if I’m wrong

psleo

I have a question that since the maxlag was ensured by Pearson correlation between ice cream lag and heater lag, why do you do the pacf to make sure the ar2 of the heater? what is the meaning of this step?

qqkexgv

Great content!!! Exactly what I needed!

maxwellzhang

Yo keep these vids up, really interesting content. Have been watching for years :)

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