Econometrics: Eviews and Risk Simulator

• Basic understanding of econometrics

Audience

• Economists
• Statisticians

Econometrics is the application of economic data and statistical methods to provide quantitative analysis of economic phenomena.

This instructor-led, live training (online or onsite) is aimed at anyone who wishes to learn and master the fundamentals of econometric analysis and modeling.

By the end of this training, participants will be able to:

• Learn and understand the fundamentals of econometrics.
• Utilize Eviews and risk simulators.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction

General Econometrics Concept

• Understanding the basic concepts of Econometrics
• Understanding variables and measures
• Overview of probability and confident level
• Statistical interference and percentiles
• Theoretical probability distributions
• Significance test and confidence interval method
• Working with Asymmetry
• Kurtosis
• Anova

Regression Analysis

• Concepts of regression
• Understanding linear regression
• Regression estimation
• Regression interference
• Understanding statistical assumptions
• Violation of assumptions and implications testing
• Understanding spurious regression
• Understanding regression models
• Transforming variables
• Interpreting coefficients
• Linear and non-linear regression models

Time Series Analysis

• Components of time series
• Different decomposition methods
• Understanding trends, cycles, and seasonality
• Performing stationarity tests
• Interpreting graphs and correlogram
• Performing unit root test
• Transforming non-stationary time series
• Stationary processes
• Understanding complex transformations in the model
• Economic and time series forecasting

Neural Networks

• Understanding neural network concepts and methodology
• Neural network composition
• Overview of machine learning
• Supervised vs. unsupervised learning
• Machine learning vs. econometrics

Financial Risk Modeling

• Measuring risks
• Occurrence probability
• Understanding the coefficient of variation
• Risk adjustment capital

Markov Chain and Montecarlo Simulation

• Understanding the concept of simulation and model
• Distribution of fits and probability
• Creating profiles
• Random and outcome variables

Evaluating a Project

• Defining project selection criteria
• Understanding the elasticity of demand
• Project economic feasibility
• Risk breakeven analysis
• Understanding the net flow
• Using analytical tools
• Stress analysis

Summary and Next Steps