Econometrics: Eviews and Risk Simulator Training Course

Introduction

Core Econometric Concepts

• Foundational principles of Econometrics
• Variables and measurement metrics
• Probability frameworks and confidence levels
• Statistical inference and percentile analysis
• Theoretical probability distributions
• Hypothesis testing and confidence intervals
• Managing asymmetry
• Kurtosis analysis
• Analysis of Variance (Anova)

Regression Analysis

• Fundamental regression concepts
• Principles of linear regression
• Methods for regression estimation
• Inferential regression techniques
• Key statistical assumptions
• Testing for assumption violations and their implications
• Identifying spurious regression
• Constructing regression models
• Variable transformation techniques
• Interpreting regression coefficients
• Linear versus non-linear regression models

Time Series Analysis

• Essential components of time series data
• Various decomposition methodologies
• Analyzing trends, cycles, and seasonal patterns
• Conducting stationarity tests
• Reading graphs and correlograms
• Performing unit root tests
• Transforming non-stationary series
• Stationary processes in econometrics
• Complex transformations within models
• Economic and time series forecasting techniques

Neural Networks

• Neural network concepts and methodologies
• Architecture and composition of neural networks
• Introduction to machine learning
• Supervised versus unsupervised learning approaches
• Machine learning versus traditional econometrics

Financial Risk Modeling

• Quantifying risk metrics
• Assessing probability of occurrence
• Applying the coefficient of variation
• Risk-adjusted capital calculations

Markov Chains and Monte Carlo Simulation

• Simulation concepts and model design
• Probability distributions and fit analysis
• Developing analytical profiles
• Handling random variables and outcomes

Project Evaluation

• Establishing project selection criteria
• Analyzing elasticity of demand
• Assessing economic feasibility
• Conducting risk breakeven analysis
• Evaluating net cash flows
• Utilizing advanced analytical tools
• Performing stress testing

Summary and Recommended Next Steps