FRM Part 2 - Book 2 - Credit Risk (Part 1/2)

After completing this reading you should be able to:

• Define credit risk and explain how it arises using examples.

• Explain the components of credit risk evaluation.

• Describe, compare and contrast various credit risk mitigants and their role in credit analysis.

• Compare and contrast quantitative and qualitative techniques of credit risk evaluation.

• Compare the credit analysis of consumers, corporations, financial institutions, and sovereigns.

• Describe quantitative measurements and factors of credit risk, including probability of default, loss given default, exposure at default, expected loss, and time horizon.

• Compare bank failure and bank insolvency.

After completing this reading you should be able to:

• Describe the quantitative, qualitative and research skills a banking credit analyst is expected to have.

• Assess the quality of various sources of information used by a credit analyst.

• Explain the CAMEL system used for evaluating the financial condition of a bank.

After completing this reading, you should be able to:

• Evaluate a bank’s economic capital relative to its level of credit risk.

• Identify and describe important factors used to calculate economic capital for credit risk: the probability of default, exposure, and loss rate.

• Define and calculate the expected loss (EL).

• Define and calculate unexpected loss (UL).

• Estimate the variance of default probability assuming a binomial distribution.

• Calculate UL for a portfolio and the risk contribution of each asset.

• Describe how economic capital is derived.

• Explain how the credit loss distribution is modeled.

• Describe challenges to quantifying credit risk.

After completing this reading you should be able to:

• Explain the key features of a good rating system.

• Describe the experts-based approaches, statistical-based models and numerical approaches to predicting default.

• Describe a rating migration matrix and calculate the probability of default, cumulative probability of default, marginal probability of default and annualized default rate.

• Describe rating agencies’ assignment methodologies for issue and issuer ratings.

• Describe the relationship between borrower rating and probability of default.

• Compare agencies’ ratings to internal experts-based rating systems.

• Distinguish between the structural approaches and the reduced-form approaches to predicting default.

• Apply the Merton model to calculate default probability and the distance to default and describe the limitations of using the Merton model.

• Describe linear discriminant analysis (LDA), define the Z-score and its usage and apply LDA to classify a sample of firms by credit quality.

• Describe the application of a logistic regression model to estimate default probability.

• Define and interpret cluster analysis and principal component analysis.

• Describe the use of a cash flow simulation model in assigning rating and default probability and explain the limitations of the model.

• Describe the application of heuristic approaches, numeric approaches and artificial neural networks in modeling default risk and define their strengths and weaknesses.

• Describe the role and management of qualitative information in assessing probability of default.

After completing this reading you should be able to:

• Using the Merton model, calculate the value of a firm’s debt and equity and the volatility of firm value.

• Explain the relationship between credit spreads, time to maturity and interest rates and calculate credit spread.

• Explain the differences between valuing senior and subordinated debt using a contingent claim approach.

• Explain, from a contingent claim perspective, the impact of stochastic interest rates on the valuation of risky bonds, equity and the risk of default.

• Compare and contrast different approaches to credit risk modeling, such as those related to the Merton model, CreditRisk+, CreditMetrics and the KMV model.

• Assess the credit risks of derivatives.

• Describe a credit derivative, credit default swap and total return swap.

• Explain how to account for credit risk exposure in valuing a swap.

After completing this reading you should be able to:

• Compare the different ways of representing credit spreads.

• Compute one credit spread given others when possible.

• Define and compute the Spread ‘01.

• Explain how default risk for a single company can be modeled as a Bernoulli trial.

• Explain the relationship between exponential and Poisson distributions.

• Define the hazard rate and use it to define probability functions for default time and conditional default probabilities.

• Calculate the unconditional default probability and the conditional default probability given the hazard rate.

• Distinguish between cumulative and marginal default probabilities.

• Calculate risk-neutral default rates from spreads.

• Describe advantages of using the CDS market to estimate hazard rates.

• Explain how a CDS spread can be used to derive a hazard rate curve.

• Explain how the default distribution is affected by the sloping of the spread curve.

• Define spread risk and its measurement using the mark-to-market and spread volatility.

After completing this reading you should be able to:

• Define and calculate default correlation for credit portfolios.

• Identify drawbacks in using the correlation-based credit portfolio framework.

• Assess the impact of correlation on a credit portfolio and its Credit VaR.

• Describe the use of a single factor model to measure portfolio credit risk, including the impact of correlation.

• Define and calculate Credit VaR.

• Describe how Credit VaR can be calculated using a simulation of joint defaults.

• Assess the effect of granularity on Credit VaR.

After completing this reading you should be able to:

• Describe common types of structured products.

• Describe tranching and the distribution of credit losses in a securitization.

• Describe a waterfall structure in a securitization.

• Identify the key participants in the securitization process and describe conflicts of interest that can arise in the process.

• Compute and evaluate one or two iterations of interim cashflows in a three-tiered securitization structure.

• Describe a simulation approach to calculating credit losses for different tranches in a securitization.

• Explain how the default probabilities and default correlations affect the credit risk in a securitization.

• Explain how default sensitivities for tranches are measured.

• Describe risk factors that impact structured products.

• Define implied correlation and describe how it can be measured.

• Identify the motivations for using structured credit products.

After completing this reading you should be able to:

• Describe counterparty risk and differentiate it from lending risk.

• Describe transactions that carry counterparty risk and explain how counterparty risk can arise in each transaction.

• Identify and describe institutions that take on significant counterparty risk.

• Describe credit exposure, credit migration, recovery, mark-to-market, replacement cost, default probability, loss given default and the recovery rate.

• Describe credit value adjustment (CVA) and compare the use of CVA and credit limits in evaluating and mitigating counterparty risk.

• Identify and describe the different ways institutions can quantify, manage and mitigate counterparty risk.

• Identify and explain the costs of an OTC derivative.

• Explain the components of the xVA term.