Econometrics: Eviews and Risk Simulator Training Course

Introduction

General Econometrics Concept

• Comprehending the basic concepts of Econometrics.
• Understanding variables and measurements.
• Overview of probability and confidence levels.
• Statistical inference and percentiles.
• Theoretical probability distributions.
• Significance testing and confidence interval methods.
• Working with asymmetry.
• Kurtosis.
• ANOVA.

Regression Analysis

• Concepts of regression.
• Understanding linear regression.
• Regression estimation.
• Regression inference.
• Understanding statistical assumptions.
• Violation of assumptions and implication 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 correlograms.
• Performing unit root tests.
• 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 modeling.
• 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