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Econometrics#2: Econometrics Modeling and Analysis in EViews

Learn Multivariate Modeling, Autocorrelation Techniques, VAR and ARCH Modeling, Unit Root and CoIntegration Testing
Rating: 3.4 out of 53.4 (57 ratings)
3,611 students
Created by Smart Coders Hub
Last updated 1/2019
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • The course works across multiple software packages such as Eviews, MS Office, PDF writers, and Paint.
  • This course aims to provide basic to intermediate skills on implementing Econometrics/Predictive modelling concepts using Eviews software.
  • Learn Univariate and Multivariate Modeling
  • Learn Autocorrelation Techniques
  • Master VAR Modeling
  • Learn Stationarity and Unit Root Testing. Also, master CoIntegration Testing
  • Master Volatility & ARCH Modeling

Requirements

  • Prior knowledge of Quantitative Methods AND Econometric techniques, MS Office and Paint is desired.
  • Understanding of Data Analysis and VBA toolpack in MS Excel will be useful
  • A Computer with Internet

Description

Please note that, We have divided the "Econometrics" course in to TWO parts as follows:

  1. Econometrics#1:  Regression Modeling, Statistics with EViews

  2. Econometrics#2: Econometrics Modeling and Analysis in EViews

This is the Second part and will cover Multivariate Modeling, Autocorrelation Techniques, VAR Modeling, Stationarity and Unit Root Testing, CoIntegration Testing and Volatility & ARCH Modeling.

This course aims to provide basic to intermediate skills on implementing Econometrics/Predictive modelling concepts using Eviews software. Whilst its important to develop understanding of econometrics/quantitative modelling concepts, its equally important to be able to implement it using suitable software packages. This course fills the gap between understanding the concepts and implementing them practically. The course works across multiple software packages such as Eviews, MS Office, PDF writers, and Paint. Econometric modeling course aims to provide quantitative/econometric modelling skills typically/specifically in Finance sector. Quantitative methods and predictive modelling concepts could be extensively used in understanding the financial markets movements, and studying tests and effects. The course picks theoretical and practical datasets for econometrics/quantitative/predictive analysis. Implementations are done using Eviews software. Observations, interpretations, predictions and conclusions are explained then and there on the examples as we proceed through the training. The course also emphasizes on the regression models, and AIMS to also cover Auto-Correlation, Co-Integration and ARCH (Auto Regressive Conditional Heteroscedasticity) models.

 Essential skillsets – Prior knowledge of Quantitative methods and MS Office, Paint

 Desired skillsets — Understanding of Data Analysis and VBA toolpack in MS Excel will be useful

The course works across multiple software packages such as Eviews, MS Office, PDF writers, and Paint.

Who this course is for:

  • Students
  • Quantitative and Econometrics Modellers, Financial markets professionals

Course content

7 sections • 125 lectures • 17h 7m total length

  • Preview11:11
  • Preview10:00
  • Understanding and Implementing Correlogram
    07:34
  • Correlogram Analysis
    07:32
  • Correlogram Analysis Continues
    06:27
  • Estimation Output Analysis and Interpretation
    11:35
  • Interpretation of the ARMA Model
    05:35
  • Interpretation of the ARMA Model Continues
    09:33
  • Correlogram Estimation of Output Model
    08:03
  • Correlogram Estimation of ARMA Model
    10:44
  • More on ARMA Model
    10:48
  • Correlogram and Estimation Output for ARMA Model
    12:04

  • Need of Multivariate Modelling
    07:51
  • Basic Theory Multivariate Modelling
    06:51
  • Generating Estimation Outputs
    08:04
  • Generating Estimation Outputs Continues
    05:18
  • Interpretations of Estimation Output
    08:16
  • Interpretations Cost Of Debt
    06:38
  • Scatter Plots Example
    10:15
  • Indices and Commodities
    07:34
  • Estimations Outputs
    07:57
  • Interpretations and Scatter Plots
    10:24
  • Generating Estimation Outputs Example 3
    10:40
  • More on GE Outputs Example 3
    11:16
  • Interpretations of Example 3
    11:17
  • Interpretations of Example 3 Continues
    07:26

  • Durbin Watson
    07:16
  • Durbin Watson Continues
    07:58
  • Residual Diagnostics
    04:58
  • DW Analysis
    06:38
  • Estimation output and DW interpretations
    10:27
  • OLS Equation and Estimation Output
    08:30
  • OLS Equation and Estimation Output Continue
    07:07
  • Example of Gold and BSE Index
    07:47
  • Example of Gold and BSE Index Continue
    07:25
  • DW Calculated
    08:20
  • Example of Forex and Index
    08:03
  • Example of Forex and Index Continue
    08:39
  • Multi Asset Analysis
    11:07
  • Correlation Matrix
    10:08
  • Estimation Output Interpretation
    10:03
  • Breusch Godfrey Test
    05:00
  • Importing Data
    08:37
  • Steps Of Breusch
    10:57
  • Steps Of Breusch Continue
    11:03
  • Correlogram and LM test
    10:03
  • Correlogram and LM test Continue
    05:17
  • OLS Estimation Equation
    08:57
  • Estimation Output and Correlogram
    08:54
  • DW analysis
    07:21

  • VAR Modelling Theory
    06:56
  • Generating the VAR Estimates
    10:42
  • Generating the VAR Estimates Continues
    06:45
  • Block Significance and Impulse Response Tests
    06:29
  • Impulse Response Tests Implementation in Eviews
    07:38
  • Variance Decomposition
    05:52
  • Lag Exclusion Tests and Implementation in Eviews
    06:38
  • Interpretation of VAR Modelling
    08:27
  • Granger Causality Tests
    06:01
  • Interpretation of Impulse Response
    06:16
  • More on Impulse Response
    06:46
  • Interpretation of Variance Decomposition
    06:24
  • Interpretation of Variance Decomposition Continues
    07:31
  • Interpretation of VAR Models
    06:52
  • Lag Length Criteria
    05:02
  • Interpretation of Granger Causality Lag Execution
    10:31
  • Interpretations of Variance Decomposition’s
    10:51
  • VAR Modelling Lag Length Criteria
    10:11
  • VAR Modelling Lag Length Criteria Continues
    06:06
  • Interpretations Using Impulse Response
    09:43

  • Theory on Stationarity and Unit Root Testing
    10:54
  • Generating Unit Root Test Output in Eviews
    07:41
  • Dickey Fuller test For URT
    03:25
  • Generating Unit Roots Estimation Output
    05:27
  • Generating Unit Roots Estimation Output Continues
    06:28
  • Root Testing for Stock and Index
    07:15
  • Generating and Interpreting Unit Roots
    10:30
  • Generating and Interpreting Unit Roots Continues
    08:50
  • Generating and Interpreting Unit Roots Intercept
    08:05
  • Interpreting Unit Roots Trend
    07:19
  • Example of Interpreting Unit Roots
    07:26
  • More on Interpreting Unit Roots
    06:44

  • Cointegration Testing Techniques
    07:11
  • Implementing Johannes Integration Technique Using Eviews
    07:28
  • More on Johannes Integration Technique
    06:41
  • Johanssen Technique Theory
    08:56
  • Johanssen Technique Theory Continues
    06:27
  • Example of Johanssen Technique Theory
    04:35
  • Generating and Testing Model Relationship
    10:45
  • Outputs for Eigenvalue and Trace Tests
    09:54
  • More on Trace Test and Eigenvalue
    06:35
  • Generating and Testing Cointegrating Relationships
    10:52

  • Introduction to Volatility and ARCH Modelling
    07:17
  • Volatility and Leverage Effects
    07:17
  • ARCH Modelling Theory
    07:37
  • Generating ARCH Model
    10:23
  • Testing for ARCH Effects Across Time Series
    09:55
  • Testing ARCH Effects in Commodities
    08:32
  • Testing ARCH Effects in Commodities Continues
    07:32
  • Objective and Equation for ARCH Effects
    08:00
  • Testing for other Commodities and Swiss Franc
    06:02
  • More on other Commodities and Swiss Franc
    07:50
  • Theory on Garch Model
    12:29
  • Garch Model Estimation in Eviews
    08:32
  • Generating GARCH Model
    07:47
  • Volatility Spikes
    07:32
  • Interpretations of GARCH Parameters
    05:23
  • Multiaseet Analysis
    06:37
  • GARCH Estimation Output - Swiss France
    07:02
  • Estimation Outputs and Interpretations
    10:07
  • More on Interpretations
    09:13
  • Working on EGARCH Modeling
    10:00
  • Generating EGARCH Estimation Output in Eviews
    08:34
  • HDCAP - EGARCH Parameters
    10:17
  • Forex Generating EGARCH Models
    12:31
  • More on EGARCH Models
    08:49
  • Interpretations - ARCH Effect and EGARCH Model
    03:12
  • Interpretation of EGARCH Estimation Outputs - GBP
    10:45
  • Interpretations of EGARCH Estimation Output of AUD
    11:06
  • Interpretations of EGARCH Estimation Comparative Study
    05:47
  • Swiss Franc and Gas
    09:53
  • Swiss Franc and Gas Continues
    06:57
  • Swiss Franc and EGARCH Model
    07:32
  • Comparison Swiss Franc and Gas
    07:56
  • More on Comparison Swiss Franc
    06:19

Instructor

Smart Coders Hub
Learn Data Science from the Expert
Smart Coders Hub
  • 3.4 Instructor Rating
  • 1,032 Reviews
  • 44,643 Students
  • 11 Courses

I am a passionate coder and a data scientist. I love teaching. I love sharing knowledge with students and enthusiastic learners. I believe any one can code. If you are passionate about learning, you will learn it. I keep learning from my work and keep teaching students. I love travelling. Its always a great feeling to see your students successful. I have lived those moments. I am obsessed with data and passionate about teaching and sharing those knowledge. Come and join me in this journey.

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