Allah nay aap ko woh maharat di hay kay aapmushkil topics bohat aasani say samjha detay hay! Really I saw many videos on net about this topic but they not deliver clearly. Ramazan Mubarak
Thank you sir love from India ....we students from PGDM (Banking and financial servies ) , NIBM (National Institute of Bank Management) are thankful to you😍😍
Thank you so much for this valuable, informative and understable lecture. The way of teaching is outstanding and you make toughest topic so simple. Thank you Sir 🙏🙏
Sir...... Bahot aasan bhasha me aap explain krte hai.... bahot sari concepts samaz gayi hai... Please Semi log model ka pura calculation aur interpretation kaise karte hai eske upar agla video upload kro sir please
@@TJAcademyofficial Sir .... CGR kaise calculate kiya jata hai semi log model se bataiye please... Semi log model ke results ek thesis me hai.... usme CGR kaise calculate kiya hai ye smaz me nahi aa raha hai.... a: 9.76 b: 0.09 SEb: 0.009 t: 10.73 R2: 0.33 Adjusted R2: 0.92 CGR: 9.75 Ye CGR 9.75 calculate kaise kiya gaya hai ye explain kro sir please
Jazak ALLAH , my question here sir related to point 3 of stationary - Covariance, Can you please give an example of covariance which exclusively related to its own lag but not on time?
Nice explanation Sir! 1 small doubt : These 3 conditions of stationarity ensure : trend-stationary + const var & const covar. However, it is said to make the time series seasonal-stationary as well. What exactly is the reasoning as to why we have to apply statistical TS models on data that is seasonal-stationary as well? Since seasonality is already a regular pattern that'll happen consistently over a period of time, then won't the Beta coefficient be able to model it even if we don't make the TS seasonal-stationary? (if the target variable is regressed with its lagged variable )?
Respected sir, your lectures are very useful. Sir, when one independent variable is stationary at level and other independent and dependent variables are stationary at first diff what test should apply to find the relationship.
Is it constant mean and variance of the variable decides about its stationarity? Or, If mean and variance of its probability distribution remains constant, then variable is said to be stationary. Please clearify
Thank you for your message. Plz watch the below lecture to clear your all doubt regarding your question. Model Selection ruclips.net/video/OnI5sEWZ68E/видео.html
@@TJAcademyofficial sir I still have some confusion. Beta is the slope, but as you showed in the video, when we make a stationary process, it becomes similar to a horizontal line (removing trend). For a horizontal line, slope is zero, does it mean for all stationary process, slope is zero ? Am I missing out something here ?
Allah nay aap ko woh maharat di hay kay aapmushkil topics bohat aasani say samjha detay hay! Really I saw many videos on net about this topic but they not deliver clearly. Ramazan Mubarak
JazakAllah and Khair Mubarak
Thank you sir love from India ....we students from PGDM (Banking and financial servies ) , NIBM (National Institute of Bank Management) are thankful to you😍😍
Thank you respected sir. Your teaching methodology is according to level of students understanding. May God bless you with success and good health.
Many apricating from Bangladesh, May Allah give you reward
Thank you so much for this valuable, informative and understable lecture. The way of teaching is outstanding and you make toughest topic so simple.
Thank you Sir 🙏🙏
India main koi aaisa teacher kyon nahi hai aap jaisa sir
Alhumdulillah you have explained the concept in a very understanding method. Keep up the great work
Sir, I am from India, nicely explained sir....thank you sir..
Excellent teacher with excellent teaching skills and knowledge
Awesome sir. Thanks a lot for teaching this. Such a simple and precise way of teaching. Love from India....
Jazakallah Great concept.... Alhamdulillah...from India
Easily explained tough topic......I am a data scientist sir....It will help me a lot...Thanks Sir
MAshallah Sir Very helpful for me. LOve from BAHAWALPUR IUB
Great teaching style. Sir can you please guide that how to iterpret our results of regression after taking 1st difference variables
thank you sir! i really like your teaching method and full satisfied your class.
we need such types of teachers and advisors very strictly in Pakistan,
Thank you for teaching so patiently. Love from India.
My pleasure 😊
Sir well done
You are nice teacher.ur method of teaching is effective.
Meaningful explanation .. thanks !
Very well explained . Thank u so much Sir
Excellent lecture Sir and very helpful ,Thank you so much for providing such videos
My pleasure. Do share TJ Academy with friends and teachers 👍
Radhe Radhe ❤
God bless you sir, apka teaching way best hai .
Thank you Sir. You have explained it in very simple words !
My pleasure 😊
great, Much Love from india ❤️
Very easy explanation of stationarity. Thank you.
Very helpful for the future research students thnku so much sr
My man you saved me from failing thanks a lot
Thank you very much for your effort. This was very helpful.
Splendid effort by you Sir, very helpful lectures,
JazakAllah
Teaching is Marvelous...
Great Sir....
Waiting for ARDL Model...
Please watch below video for ARDL
ruclips.net/video/fO6CoG5fOzU/видео.html
Woww you made it sound so simple.Thank you!❤
Thank you for explaining so well
Thank you sir this is what exactly i was looking for so long. Thanks a lot
My pleasure
I love you man, you are so awesome... God bless you very much .. blessing from heart
Thank you very much
Sir do you have any video for Arma model, if yes please share the link, else make one please
Excellent information brother
You are the best sir
bht acha explain kia ha sir apna
Wonderful video
Ustaad ji tusi Great ho... Allah bless you
Thank you
Sir...... Bahot aasan bhasha me aap explain krte hai.... bahot sari concepts samaz gayi hai...
Please Semi log model ka pura calculation aur interpretation kaise karte hai eske upar agla video upload kro sir please
Thank you. Plz find below videos on log model
Link 1: ruclips.net/video/WqikKVUkj1Q/видео.html
Link 2
ruclips.net/video/sAM6pkK16G0/видео.html
@@TJAcademyofficial Sir .... CGR kaise calculate kiya jata hai semi log model se bataiye please...
Semi log model ke results ek thesis me hai.... usme CGR kaise calculate kiya hai ye smaz me nahi aa raha hai....
a: 9.76
b: 0.09
SEb: 0.009
t: 10.73
R2: 0.33
Adjusted R2: 0.92
CGR: 9.75
Ye CGR 9.75 calculate kaise kiya gaya hai ye explain kro sir please
Thanks ! You did explain very well 👍👍
Sir, please make a video regarding Volatility Analysis based on ARCH and GARCH model if possible.
MashaAllah sir bht zbrdst explain Kia h..Sir kindly agr apk pas notes h touu provide krden mera final exam h kch dino Mai..but tension hori h
Addicted to wach your vedios
Thanks ;). Keep watching
Sir, the criteria you have specifed for stationary are for weakly stationary, I'm a bit confused
Yes it is weakly stationary but most of the papers uses econometrics satisfy weak stationary only
Good explanation
Thank you so much sir..
I need more videos on Time series Analysis ke अंदरका सभि टपिक का
Topic bohot easy kar diya... 👍 I want to give huge round of palms . Apka ka pyara padosi bharat se
Bht shukrya aapka 🙂
@@TJAcademyofficial sir apki agli vedio mai leg word ka matlab samaj nahi aarha dicki fuller test vedio mai
Lag pichlay year ki value ko kehtay hn jesay 2019, lag 1 hay 2020 ka
Thanks... from Ankara
Jazak ALLAH , my question here sir related to point 3 of stationary - Covariance, Can you please give an example of covariance which exclusively related to its own lag but not on time?
Sir hum moving average ko kysy analysis kray written may weekly monthly quartly
Thank you sir.
Mashallah
Love from INDIA.
Great teachinh
Outstanding 😍
Sir can you please explain the difference between stochastic and Non Stationary series
Thank you.
Sir where are you kindly note lecture upload for our knowledge improvement
Thank you Sir. Please explain Stationary condition no. 3 that covariance should depend on lag, not on the basis of time?
Yes it is little confusing for me too
Nice explanation Sir!
1 small doubt :
These 3 conditions of stationarity ensure : trend-stationary + const var & const covar.
However, it is said to make the time series seasonal-stationary as well. What exactly is the reasoning as to why we have to apply statistical TS models on data that is seasonal-stationary as well?
Since seasonality is already a regular pattern that'll happen consistently over a period of time, then won't the Beta coefficient be able to model it even if we don't make the TS seasonal-stationary? (if the target variable is regressed with its lagged variable )?
Is it important to compare two series to determine if a series is stationary or non stationary
Like can we not determine this based on only one chart
Plez Send A Link of lecture that should be about the properties of OLS
Respected sir, your lectures are very useful. Sir, when one independent variable is stationary at level and other independent and dependent variables are stationary at first diff what test should apply to find the relationship.
Thank you for your message. Watch the video below for your answer.
ruclips.net/video/daE36l0p_sM/видео.html
Hi is there any econometric analysis technique to to analyse stati9nery data at 2nd order differencing?
Excellent explanation. Do you have any lectures on VAR and Structural VAR model?
Currently working on forecasting. After ARMA and ARIMA, I have plan for VAR. JazakAllah
@@TJAcademyofficial Sir, thanks very much for your swift response. I will be looking forward to your videos on VAR analysis. JazakAllah Khair.
Plz don't chage markers repeatedly it disturb the attention rest is ok
Thank you so much Sir 🙏 LOV from India
Is it constant mean and variance of the variable decides about its stationarity? Or,
If mean and variance of its probability distribution remains constant, then variable is said to be stationary.
Please clearify
thank you teacher for your efforts, can you please add English subtitles to all your videos please
Added
GOOD!
Sir in reality all the series are non stationary then what we can can do for accurate results.
Sir,
If all determinates in time series result are none stationary, am i run regression model?
Thank you for your message. Plz watch the below lecture to clear your all doubt regarding your question.
Model Selection
ruclips.net/video/OnI5sEWZ68E/видео.html
Sir please tranformation of non stationary time series or brief vedio bna dijiye sir ......please.
Sir apka teaching method sbse best .....sir please consider my request
🙏🏼🙏🏼🙏🏼
prove that ARIMA model is non stationary time series
Sir exactly Beta Ka MATLAB kya Hota he ?
Beta is a symbol which represents change in Y due to change in X. App koi or symbol bhi use krskty hm.
@@TJAcademyofficial sir I still have some confusion. Beta is the slope, but as you showed in the video, when we make a stationary process, it becomes similar to a horizontal line (removing trend). For a horizontal line, slope is zero, does it mean for all stationary process, slope is zero ? Am I missing out something here ?
P
such a great learning video sir.
Sir research k about bi video banahy
Soon InshAllah...
so nice sir
Thank you sir 🙏🙏🙏