How to estimate arch model - eviews tutorial complete

In this time series tutorial, I will teach you how to estimate arch model - eviews tutorial, complete, step-by-step. Know the basics of arch modeling eviews! Time series arch model easy explanation! On my previous eviews tutorial, we focused on estimating and forecasting the mean equation. In this tutorial, we will focus on modeling the variance. How? I will show you how how to estimate arch models in eviews. ARCH stands for Autoregressive conditional heteroskedasticity, and we are interested in estimating ARCH models because it allows us to model periods of higher volatility in our series. Let's begin with our arch model example step by step!

✅ Objective of the video: by watching this tutorial you will learn how to estimate arch models in eviews. We will use real data, and test whether ARCH componenents exist, and how to add the ARCH components to the model. ARCH models allow us to model financial time series that exhibit time-varying volatility and volatility clustering.

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🎬 Watch my second ARCH tutorial: Common mistakes to avoid when estimating ARCH models

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🕘 Timestamps:
🎬 In this video the following analysis is performed:
👋 Introduction 0:00
📊ARCH models Overview 0:46
📊Volatility Clustering 1:53
📊 ARCH models considerations 3:20
📊 ARCH models formalities 4:16
📊 Steps to estimate ARCH models 7:25
📊 Part 1: Step 1. Stationarity 8:15
📊 How to Generate Returns series 9:36
📊 Part 1: Step 2. Mean Equation 11:17
📊 Part 2: Step 1. ARCH Effects 13:24
📊 How to determine ARCH order 15:36
📊 How to estimate ARCH model 18:46
📊Model Diagnostics 21:32
📊Make Garch Variance 24:40
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JDEconomics

[JDEconomics]

Hello Everyone! Thanks for your support!

✅ Buy the material of the video: Slides+EViews workfile with instructions and results:

📈 Download the dataset for free and replicate the content of the video:

✅ Visit my website to see all my FREE tutorials:
www.jdeconomics.com

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Thanks a lot for your support!
JD Economics.

[MuhammadAmir-ppwn]

Excellent work. For me very helpful in learning and understanding the concept with practical example.

[AnanthAliasRohithBhatP]

very well explained. wonderful. thanks for sharing this knowledge

[wizshah]

at 11:33 please explain what do you mean by "non-stationary in levels" and "stationary in differences"?

[AhmedMohammed-gnbq]

Thanks so much sir. I really appreciate your all videos.

[dudiaharon]

Thanks for the great videos! Are you planning to upload any video about Panel regressions? I hope you will! your explantions are simply excellent!

[vinsontechnologies]

Hi, thanks so much for sharing this material, very informative indeed. May I ask, if there are still lags after estimating the equation, what is the next step. Thanks again.

[vikram]

Thank You Sir. For sharing the video. Can you please share Video on Multivariate GARCH MODEL, Spill Over Effect or DCC garch

[Hassan_MM.]

Thanks 👍
But Question is :
5:01 How Errors are Normally Distributed, If Heterocadasticity Exists i.e Errors Variance is not Constant or is Increasing ?
Or is it Better to Switch to Some other Distribution

[Loem]

Thank you, very informative. Can you do some videos related to GARCH and ARDL Models too.

[asfiabinteosman]

Sir thank you so much for sharing with us. I really appreciate it. I have a question. When you checked with 1 lag the result was appropriate• Again when you checked with lag 2; again result was approprite. So why you selected ARCH (2 ) over ARCH (1 ) ls there any specific reason or you selected it randomly

[georgebragues]

Great tutorial. One question: do all the variables in the mean equation have to be stationary? Or can the dependent variable be non-stationary, while having a lagged version of that variable on the right side of the equation as a control for the auto-correlation present in the dependent variable?

[danielefraietta]

Hi Juan! Great video! Please keep up with this. Just wondering, will you be treating multivariate garch models (VECH and BEKK)?

[moeinheidariyeh]

if you want to watch the garch video too go to that video that involves arch too.

[michaelasare]

So Modelling ARCH is simply accounting for Heteroskedasticity in the model?

[krishnaiyer]

WHAT IS THIS BACKCAST PARAMETER ROLE? WHAT IT DOES? WHY IT DOES? AND PRACTICAL SIG IN MODELLING? MEANING AND INTERPRETATION PLEASE?

[cssunita]

Sir my correlogram shows ar and ma 16 as significant. Can this be taken for further calculation?

[kanchandatta]

mean equation of TSXt ? or Returns? I think it should be Retruns. please rectify me.

[shubhamgarg]

Good evening sir, I need your help in garch model. I have emailed you the same. If you can it will be my pleasure. If you have computed these arch values in your video also kindly provide me the value so i can understood properly.

[shaydenrobinsonmcse]

If your data does not show any arch effects does that mean you cannot estimate an arch model from it?