Time Series Forecasting Theory | AR, MA, ARMA, ARIMA | Data Science
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- เผยแพร่เมื่อ 20 ส.ค. 2024
- #machinelearning #timeseries #datascience #quantitativefinance #AI #finance #riskmanagement #creditrisk #marketrisk
In this video you will learn the theory of Time Series Forecasting. You will what is univariate time series analysis, AR, MA, ARMA & ARIMA modelling and how to use these models to do forecast. This will also help you learn ARCH, Garch, ECM Model & Panel data models.
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It was difficult for me to have a big picture about time series. Now, i have the big picture with your video..thank you alot!...from Ecuador!!!
This is probably the most complete video on TH-cam on this subject! Thank you!!
thanks
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Time series analysis is one of most complicated topics for me and your video has simplified it so much for me. Your handwritten notes also helped a lot to understand the concept. Thank a lot for explaining in such a brilliant way!!!
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This is really very well explained in a practical and clear manner. Thank you so much, this really made the concepts hit home, and I can read supplemental material on this with much better context and understanding. Thank you for taking the time to make this video.
There are plenty of videos on youtube. If you don't like how he teaches, go find another one. That is the beauty of internet. For me, it served the purpose and now I understand time series. Thank you, very much.
This is the best explanation of time series model on you tube!
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Can't agree more. Some people just have a title of doctor and no brain. This is the first time I understood the concept after reading and watching so many stuff.
Just coz it worked for you doesn't mean its gonna work for everyome
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had to like and favorite this, so much info condensed into one video
Nicely done! Throughout this session, you have articulated clearly why we need to perform certain steps. That was quite helpful for me.
One of the most productive 53.14 minutes of my life🤗
thanks
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Can you also share these slides?
Hi sir, could you please make another video specifically for BPO analysts?. Please cover all the methods used in BPO call volume forecasting.
This truly is the best video on the subject. I have regression and time series exam this Saturday! This was a huge help!
Ads every 2-2,5 minutes, that would be too many even for a tv channel! Useful video, but get your ads setting in order!
don't watch it! simple
@@indianarchangel irresponsible respond
Yes it's hard to learn when being interrupted every 5 min. So I downloaded it, and watched offline
Try adblock. will blow your mind
Skip to the end and replay.. no more ads
Top' s my professor's lectures by a mile and a 1/2!!!
Thanks
This lecture is by far the best. Thank you Sir. You broke the topic to its simplest form. I have found most of the processes difficult to grasp before now , even my lecturers were unable to give me what I needed. You have set me free from the shackles of this course. I am a research student and once again, THANK YOU SIR. Sigh!
thanks
This is a great video ...you people know how to explain time series ... simple but sure you have explained in few minutes what my lecturer struggled to explain in two weeks
this is beautiful..sir, this is amongst one of the best explanation which i have seen till now..thank you too much!!
Thanks
i loved your presentation sir!
You took your time, explained in a clear and practical manner.
thank you for this video
Well-done! Very professional, informative, with a lot of contents, and answers almost every possible questions. In the future videos, please also explain specific letters. For example, if you say that "p". or t, or u, or whatever, please explain that those specific letters refer to. Thanks a lot. I took a lot of useful notes.
Y = a + bX is univariate analysis. Multivariate always refers to the dependent variables. So if we are forecasting/estimating one dependent variable then it is always univariate. If we have more than one independent variables, then it is called a multiple regression to be precise
Y = a+bX is multivariate analysis. That equation tries to predict the variation in Y(var 1) using the variation in X(var 2) hence multivariate. Univariate refers to variation of a single variable(and not comparing it to anything else)
Thanks for taking so much pain and patience in explaining the concepts. I know it is not easy to explain these abstract concepts. Great work. Excellent video on time series and modeling.
Thanks
The best explanation of time series. It's totally worth the 53 mins. However I have a doubt, when he said about the error in the MA method. Equation what you meant was: xty = slope*xt + intercept. and the error = xty - xt. Kindly correct me if I am wrong.
Thanks
@@AnalyticsUniversity ? correct or no
I just want to say thank you for this video. Very well explained . Very thorough and understandable .
thanks
You save my ass for my Bachelor Thesis. Thank you very much !
Very good lecture; not waste of time and not seen the lecturer but the content.
Thank you
very good and clear explanations! Out of all tutorials, this was the best to understand the time series models! Can you share the data set?
Best explanation of ARMA I've seen. Thank you.
Thanks
You are such a helpful professor. Your videos have helped me much. Thank you
Thanks for making this video tutorial. Many of my doubts are now clear.
I am new to time series, your video was helpful, it had all the concepts in one place and it was an hour well spent. However I don't think differencing and differentiating are the same thing. Differencing is the process of taking a difference of series from itself as various lags. I am not sure if its about taking a derivative (like you hinted) ...
what an incredible tutorial! Please keep posting many more. Thanks and God bless you.
thanks
Thank you so much sir. Your explanation has taught me enough about the time series model. Thank so much from Bhutan.
thanks
Very Well explained. Found this video too useful after searching through different websites. Thanks....
Good video. Nice clear explanations. I am taking time series/forecasting class and have tests coming up soon and this was a good summary of concepts. We use SAS in this class, I wish we used R as it is much easier
This tutorial is so good! Many thanks and gratulations for this perfect work! Time series can now handled easy ;)
Thanks
best tutorial on time series, so far.
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Indeed a very informative video on time series and forecasting. One video contained all information that I needed in order to start practising time series on datasets. Thanks a lot.
this was the best video on you tube of time series!! I from Perú, thanks!!
Thanks
Great conceptual explanation of time series. I particularly loved the questions you raised and responded to. They are vital to understanding the concept yet so rarely appear in other sources. Thank you.
thanks
This is so well explained in a practical and clear manner. Thank you so much, this really made the concepts hit home, and I can read supplemental material on this with much better context and understanding. Thank you for taking the time to make this video and may God bless you.
thanks
millions thanks sir, this lecture is worthy for ones who don't have access to formal class
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One of the best video for learning econometrics basics... Thankyou soomuch.
It is very nice presentation style. It help students to understand what main points should be understood.
Best time series video ever.
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fundamentally clear timeseries concept🙌
Much appreciated efforts has been made to provide robust understanding of the subject matter. Just few questions: 1) If we just look into a variable in an isolation (i.e stock price) etc on the basis of historical trend, its quite possible that this trend will not gonna happen in the future time period. For this problem, I've seen many people working on the elimination of trend. So, if we are able to remove trend, then still can it be possible to forecast a variable (stock price) ?
the best explanation of time series but too many ads in one video.
A very easy and simple way of time series concepts explanation.. Great job
The best help i have ever got on youtube. Thanks a lot.
Ohhhh... hey, there's a video in these ads!
Just chilling, this is a great video kids.
Excellent tutorial. The instructor did a great great job. Kudos!
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this is really a good explanation of time series analysis for beginners .i learn a lot from this video..thank u very much sir
Very good and helpful video for understanding Time series 👌
Thank you so much sir!! So far the best video on time series
Ek number. Best & crystal clear explanations. Keep up the good work.
Amazing clarity of concept with good explanation!!
This is the best explanation provided for Time series model. Thank you so much sharing it. Can you kindly provide any practical application in retail sector using R studio.
Thanks
nicely explained... cleared few of my concepts... Thanks for making this video.
Thanks a lot ur explanation is crisp and clear.
thanks
Thanks
Please please please declare your values. Is beta a constant? integer? real? is Phi a constant? It would be helpful to use proper mathematical notation to make it clear!
Very easy to grasp and very well explained. Thanks a lot for the video!!
Enjoyed the first 30 minutes and got concepts of time-series clear. After 30 minutes it was not very clear for me to understand. Thanks
best explanation for time series .. Thank you very much sir
Thank you for this great introduction in time series forecasting theory.
great video to summarize on timer series modeling with good intuitions and good pace of lectures...
thanks
Thanks a lot it is really useful knowledge which I used to do my time series project
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Great work mate! easy to understand
Great Video :)
1) What should we do if the residual is not random and has pattern.
2) Can you please share the dataset and ppt.
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This is superb. I always tried to study the concept separately and never understood a bit. Look forward to more coaching. How do I continue?
Hello Sir,
I have a question about forecasting. Should plan corrections be determined during forecasting? Or is it not necessary to determine them? Why is there an extrapolation? An extrapolation is absolutely necessary.
best ts video ever found on youtube
madhu kumar thanks
thank you so much for explaining this so clearly! It's much much appreciated!
THANKS
Super video! I applauded for $2.00 👏
Appreciate!
The example explained in the video is based on quarterly data. I want to ask one thing that can we use same time series analysis for annual data?
This video is very helpful. I learned a lot. Thank you for sharing!
Quite thoroughly explained. Thank you!
thanks for watching. Wish you a happy new year in advance!
Great explanation by Dr Ray...
this is possible the most elaborated tutorial I have come across. Thank you Sir !!
Very good sir
Hello sir
I want to thank you so much for this video
the effort you put into this video incredible. it is so easy to follow and understand
Thank you for my bottom of my heart
thanks
While explaining the White Noise series you said if the series is white noise then we will not use any time series forecasting but in Moving Average model you said the error term is a white noise.
Can you please explain this, I am but confused, regarding the use of Time series forecasting model when we have a white noise process .
I too likes your teaching approach it good I need another video haw to intreethe data to Stata
Good introduction, thanks for sharing !
I usually use Minitab to analyze data. I wanted to know in which situations is convenient using the seasonal model or the non-seasonal
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This is very good wow! But what about statationary? Can u say something about that?
Sir, Your way of teaching awesome
Its a great video to learn the basics of Time series
G R A C I A S mil desde COLOMBIA. It works perfectly with animal production. I do something similar using percentage. Thanks in advance!!!
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Please look into what seems a mistake to me at 30:10 it is differencing not differentiating. The difference between values for a lag.
Yes, you are right! I have mispronounced 'differencing' and 'differentiating' in many place.
Really nicely explained... Thank you so much sir 😄
Very nice explanation. I appreciate your kind effort.
At 32:04 you have mentioned that differencing is actually differentiating. Isn't it actually subtracting with the order of the backward shift operator? Say first order differencing is actually yt - yt-1.
You teach very well. Thank you.
Parameters Estimation:Yule walker,mom,max likelihood
Very enlightening..thanks a lot
thanks
For a particular dataset, i found (p=0, i=1, q=2) and (p=0, i=1, q=3). In both cases i shifted the predicted values by -1 timeperiod.(what i predicted for feb, i conisdered it for jan). Doing so i got testing accuracy of 99% (MAPE-mean abs percetage err).
What went wrong with this scenario because 99% seems way to good to be correct for any scenario.
Very informative
Thank you sir
thanks