The course will be divided into 4 main sections:

Section 1: Introduction

• The importance of risk measurement and management (for a financial institution, for supervisory authorities).
• The trade-off between returns and risk.
• Volatility: Definition. Methods of measurement (imputed volatility, volatility from historical data). Distributions of Changes in Financial Variables. The Constant Volatility Assumption and other models measuring it (GARCH). Predict future volatility using these models.
• Correlations: Definitions. Measuring correlation with different models (simple, GARCH).

Section 2: Market Risk

• Individual and cumulative risk management.
• The “Greek letters”. Their interpretation and measurement.
• Risk Metrics. Value-at-Risk. Definition. Its relation to Expected Shortfall. The choice of parameters to calculate VaR. Marginal VaR, Incremental VaR and Component VaR. Back-testing. Stress-testing.
• The method of historical simulation. Accuracy of the method. Extensions (observation weighting, volatility update integration, bootstrap method).
• The model building approach for VaR (model building approach). Description of the methodology. Linear model. Weaknesses of the linear model. Quadratic model. Monte Carlo simulation.

Section 3: Credit Risk

• Credit ratings (from independent houses and internal).Το Ζ-score του Altman.
• Altman’s Z-score.
• Bankruptcy probabilities based on historical data.
• Bankruptcy recovery rates.
• Differences in estimated default probabilities from historical data and bonds. Possible explanations for the differences.
• Credit VaR (description, method of calculation, calculation using Vasicek’s model).
• Credit derivatives (description, function, use, valuation).

Section 4: Liquidity Risk and Interest Rate Risk

• Definition of liquidity risk.
• Problems created by liquidity risk in a credit institution.
• Exchange Agreements (Swaps).
• “Black Holes” of liquidity.
• Definition of interest rate risk.
• The relationship between interest rate risk and liquidity risk.
• Dealing with interest rate risk.