Value at Risk (VaR) and Expected Shortfall Applications Training Course

Introduction
In an increasingly volatile global financial environment, the ability to quantify and manage risk exposure is essential for the stability and profitability of financial institutions. The Value at Risk (VaR) and Expected Shortfall Applications Training Course is designed to provide risk professionals, asset managers, and financial analysts with in-depth knowledge and practical expertise in implementing two of the most widely adopted risk measures: VaR and Expected Shortfall (ES). This course explores their theoretical foundations, practical applications, and regulatory relevance, particularly under Basel III/IV and FRTB frameworks.

Conducted over five comprehensive days, the training emphasizes hands-on modeling, backtesting, and interpretation of VaR and ES in both trading and banking book environments. Participants will use statistical techniques, simulation methods, and real-world data to understand the limitations, assumptions, and decision-making implications of these metrics. The course equips participants with actionable tools to enhance risk-based capital allocation, stress testing frameworks, and performance assessment across various asset classes.

Duration: 5 days

Target Audience:

  • Risk management professionals in banks and investment firms
  • Financial analysts and quantitative modelers
  • Portfolio and asset managers
  • Treasury and trading desk staff
  • Supervisory and regulatory agency personnel

Course Objectives:

  • Understand the theoretical and statistical foundations of VaR and Expected Shortfall
  • Apply parametric, historical, and simulation-based VaR and ES models
  • Conduct backtesting and model validation to ensure reliability
  • Integrate VaR and ES into capital allocation, performance measurement, and reporting
  • Align risk models with regulatory standards, including Basel and FRTB

Course Modules

  1. Introduction to Value at Risk (VaR) and Expected Shortfall
  • Overview and significance of risk quantification
  • Comparing VaR and Expected Shortfall as risk measures
  • Regulatory context: Basel III/IV, FRTB, and IFRS implications
  • Strengths, limitations, and practical use cases
  • Risk metrics across banking, trading, and investment environments
  1. Statistical Foundations and Risk Factor Modeling
  • Key probability distributions in risk modeling
  • Mean-variance analysis and portfolio statistics
  • Correlation, covariance, and copula techniques
  • Time series analysis and volatility clustering
  • Normality assumptions and fat tails in financial data
  1. Parametric and Historical VaR Techniques
  • Variance-covariance (delta-normal) approach
  • Assumptions, strengths, and drawbacks of closed-form VaR
  • Historical simulation methods using rolling windows
  • Risk horizon adjustments and time scaling
  • Application to fixed income, equity, and FX portfolios
  1. Monte Carlo Simulation for VaR and ES
  • Concept of stochastic modeling in risk estimation
  • Steps in building Monte Carlo simulations
  • Path dependency and convergence techniques
  • Non-linear exposure modeling and option pricing
  • Comparing simulated VaR vs. historical and parametric results
  1. Expected Shortfall (Conditional VaR) Applications
  • Motivation for using Expected Shortfall over VaR
  • Tail risk and loss distribution truncation
  • Computing ES under different approaches
  • Integration into risk-adjusted performance frameworks
  • Regulatory transition to ES under FRTB
  1. Backtesting and Model Validation
  • Importance of backtesting for model credibility
  • Kupiec and Christoffersen tests for VaR accuracy
  • Stress testing and scenario-based validation
  • Model governance and documentation requirements
  • Identifying and correcting model deficiencies
  1. Capital Allocation and Performance Assessment
  • Linking VaR/ES to economic and regulatory capital
  • Risk-based pricing and portfolio optimization
  • Performance measurement: RAROC, EVA, and Sharpe ratios
  • Internal capital adequacy (ICAAP) and reporting integration
  • Use of VaR/ES in incentive and risk governance structures
  1. Practical Case Studies and Risk Reporting
  • VaR/ES modeling using Python, R, or Excel
  • Real-world examples from investment banks and asset managers
  • Interpreting risk reports and dashboards for decision-makers
  • Designing custom risk limit frameworks based on VaR/ES
  • Final group exercise: develop and present a VaR/ES model and report

CERTIFICATION

  • Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

  • Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

  • Airport pick up and accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com

 

Value At Risk (var) And Expected Shortfall Applications Training Course in North Macedonia
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