Moving Average (MA) Models| Time Series Forecasting #3|

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Tutorial on Moving average models for time series forecasting . I cover the following topics in this video:
1) Why to use past errors in moving average models?
2)Formal definition and 1st,2nd and q order MA model
3)ACF and using a ACF plot to find order of moving average model

Recommended Books to get better at Time Series Analysis and Python:

Leave any queries in the comments .

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Your explanations are terrific - simple and straight to the point. Thanks alot for this smooth style!

omzka

Man, I have never understood Time Series so smoothly. Thanks!

prathkothari

i love u man...my proff had phd and is twice your age but his explanation was no where near your's..

vigneshrammohan

I don't usually comment on videos. But this one is a Great video

dentrifications

Thanks bhai .Explained it very clearly

shubhamgadhari

You never explained why c1 is 0.5
Did you choose it randomly ? Is it the y intercept ?
Why 0.5, why not another value, like a whole number ? What about negative numbers?

abstract_machine

Hi, why do we use Acf plot lags for Moving average order and Pacf plot lags for Auto regression order?

PraveenKumar-pdsx

Does a negative value for Pearson's coefficient indicate a reverse proportionality or does it mean that there is no relation/dependency between the variables considered?

What happens if in the ACF/PACF plot the graph extends to the negative axis beyond the error band? How do you take that into the order consideration?

ashwin_.

Thank you for the video, sir, how do you get the error for the current prediction "et" when you havent made the prediction yet?

guccikom

in the last example: the predicction value for 4th n 5th itergation are 7 and 7.5, but in graph its 10 and 9??

advisoryaccount

How do we know the current error (epsilon t) if we are forecasting the current value?

edavar

Hey, Hi I cant see your video part 2, it shows private video?

manideepgupta

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