2 - Credit Risk Measurement & Management Flashcards
Define credit risk and explain how it arises using examples.
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Explain the components of credit risk evaluation.
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Describe, compare, and contrast various credit risk mitigants and their role in credit analysis.
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Compare and contrast quantitative and qualitative techniques of credit risk evaluation.
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Compare the credit analysis of consumers, corporations, financial institutions, and sovereigns.
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Describe quantitative measurements and factors of credit risk, including probability of default, loss given default, exposure at default, expected loss, and time horizon.
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Compare bank failure and bank insolvency.
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Describe the quantitative, qualitative, and research skills a banking credit analyst is expected to have.
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Assess the quality of various sources of information used by a credit analyst.
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Explain the capital adequacy, asset quality, management, earnings, and liquidity (CAMEL) system used for evaluating the financial condition of a bank.
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Evaluate a bank’s economic capital relative to its level of credit risk.
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Identify and describe important factors used to calculate economic capital for credit risk: probability of default, exposure, and loss rate.
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Define and calculate expected loss (EL).
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Define and calculate unexpected loss (UL).
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Estimate the variance of default probability assuming a binomial distribution.
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Calculate UL for a portfolio and the UL contribution of each asset.
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Describe how economic capital is derived.
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Explain how the credit loss distribution is modeled.
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Describe challenges to quantifying credit risk.
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Explain the key features of a good rating system.
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Describe the experts-based approaches, statistical-based models, and numerical approaches to predicting default.
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Describe a rating migration matrix and calculate the probability of default, cumulative probability of default, marginal probability of default, and annualized default rate.
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Describe rating agencies’ assignment methodologies for issue and issuer ratings.
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Describe the relationship between borrower rating and probability of default.
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Compare agencies’ ratings to internal experts-based rating systems.
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Distinguish between the structural approaches and the reduced-form approaches to predicting default.
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Apply the Merton model to calculate default probability and the distance to default and describe the limitations of using the Merton model.
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Describe linear discriminant analysis (LDA), define the Z-score and its usage, and apply LDA to classify a sample of firms by credit quality.
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Describe the application of a logistic regression model to estimate default probability.
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Define and Interpret cluster analysis and principal component analysis.
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Describe the use of a cash flow simulation model in assigning ratings and default probabilities and explain the limitations of the model.
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Describe the application of heuristic approaches, numeric approaches, and artificial neural networks in modeling default risk and define their strengths and weaknesses.
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Describe the role and management of qualitative information in assessing probability of default.
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Using the Merton model, calculate the value of a firm’s debt and equity and the volatility of firm value.
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Explain the relationship between credit spreads, time to maturity, and interest rates and calculate credit spread.
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Explain the differences between valuing senior and subordinated debt using a contingent claim approach.
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Explain, from a contingent claim perspective, the impact of stochastic interest rates on the valuation of risky bonds, equity, and the risk of default.
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Compare and contrast different approaches to credit risk modeling, such as those related to the Merton model, CreditRisk+, CreditMetrics, and the KMV model.
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Assess the credit risks of derivatives.
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Describe a credit derivative, credit default swap, and total return swap.
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Explain how to account for credit risk exposure in valuing a swap.
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Compare the different ways of representing credit spreads.
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Compute one credit spread given others when possible.
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Define and compute the Spread ‘01.
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Explain how default risk for a single company can be modeled as a Bernoulli trial.
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Explain the relationship between exponential and Poisson distributions.
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Define the hazard rate and use it to define probability functions for default time and conditional default probabilities.
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Calculate the unconditional default probability and the conditional default probability given the hazard rate.
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Distinguish between cumulative and marginal default probabilities.
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Calculate risk-neutral default rates from spreads.
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Describe advantages of using the CDS market to estimate hazard rates.
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Explain how a CDS spread can be used to derive a hazard rate curve.
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Explain how the default distribution is affected by the sloping of the spread curve.
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Define spread risk and its measurement using the mark-to-market and spread volatility.
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Define and calculate default correlation for credit portfolios.
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Identify drawbacks in using the correlation-based credit portfolio framework.
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Assess the impact of correlation on a credit portfolio and its Credit VaR.
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Describe the use of the single-factor model to measure portfolio credit risk, including the impact of correlation.
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Define and calculate Credit VaR.
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Describe how Credit VaR can be calculated using a simulation of joint defaults.
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Assess the effect of granularity on Credit VaR.
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Describe common types of structured products.
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Describe tranching and the distribution of credit losses in a securitization.
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Describe a waterfall structure in a securitization.
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