FRM (Financial Risk Manager) Credit Risk Measurement and Management (Part II) Syllabus

Credit Risk Measurement and Management (Part II) syllabus — full chapter and topic list

Expand any chapter to see its topics and sub-topics. This is the whole examinable outline for Credit Risk Measurement and Management (Part II) in FRM (Financial Risk Manager), not a summary of it.

1. 1

   Credit Risk Fundamentals and Default

   4 topics

   • Credit Analysis Principles
     • The five Cs of credit
     • Counterparty credit assessment
   • Default Probability Estimation
     • Structural models (Merton model)
     • Reduced-form and intensity models
   • Credit Spreads and Risk-Neutral Default
     • Spread-implied default probabilities
     • Real-world vs. risk-neutral measures
   • Credit Scoring and Rating Systems
     • Internal rating models
     • Rating migration and validation
2. 2

   Counterparty Credit Risk

   4 topics

   • Counterparty Risk Metrics
     • Current and potential future exposure
     • Expected exposure and EPE
   • Credit Valuation Adjustment (CVA)
     • Unilateral and bilateral CVA
     • Debit valuation adjustment (DVA)
     • Wrong-way risk
   • Mitigating Counterparty Risk
     • Netting and collateral agreements
     • Central clearing and CCPs
   • The xVA Family
     • FVA, MVA, and KVA overview
3. 3

   Portfolio Credit Risk and Securitization

   4 topics

   • Credit Portfolio Models
     • CreditMetrics framework
     • Default correlation modeling
   • Credit Derivatives
     • Credit default swaps pricing
     • CDS indices and basket products
   • Structured Credit Products
     • CDO tranches and attachment points
     • Correlation and tranche sensitivity
   • Securitization Risk
     • Cash flow waterfalls and credit enhancement

Credit Risk Measurement and Management (Part II) flashcards for FRM (Financial Risk Manager)

18 of 51 cards from the Credit Risk Measurement and Management (Part II) deck — real questions with worked answers.

1. What are the three broad components a credit analyst evaluates when assessing a borrower's creditworthiness?

   The willingness to repay (character/intent), the capacity to repay (ability from cash flows), and the cushion against loss (collateral and capital). Together these frame whether default is likely and how much would be recovered.

2. List the "Five Cs of Credit" used in qualitative credit analysis.

   Character (reputation/willingness to repay), Capacity (ability to generate cash flow to service debt), Capital (the borrower's own equity/net worth at stake), Collateral (assets pledged to secure the loan), and Conditions (economic/industry environment and loan terms).

3. In the Five Cs, what does "Capacity" specifically measure?

   Capacity measures the borrower's ability to repay from operating cash flows, typically assessed through income, cash-flow coverage ratios, leverage, and the stability/sufficiency of earnings relative to debt service.

4. In the Five Cs, distinguish "Capital" from "Collateral."

   Capital is the borrower's own equity or net worth invested (skin in the game, reducing incentive to default); Collateral is specific assets pledged that the lender can seize on default to recover losses. Capital reduces PD-related incentives; collateral reduces LGD.

5. What is counterparty credit risk, and how does it differ from traditional lending credit risk?

   Counterparty credit risk is the risk that a counterparty to a bilateral derivative or financing contract defaults before settling, when the contract has positive value to the surviving party. Unlike a loan, the exposure is bilateral and stochastic — it varies with market factors and can be positive or negative over time.

6. Define Probability of Default (PD).

   PD is the likelihood that a borrower or counterparty fails to meet its contractual obligations (defaults) over a specified time horizon, usually expressed as a probability over one year (or a cumulative horizon).

7. Name the two broad families of quantitative models used to estimate default probability.

   Structural models (e.g., Merton model), which derive default from the firm's asset value and capital structure; and reduced-form (intensity) models, which treat default as an exogenous random event governed by a hazard/intensity process calibrated to market data.

8. What is the core economic insight of Merton's structural model of default?

   A firm defaults when the market value of its assets falls below the face value of its debt at maturity. Equity is modeled as a call option on the firm's assets struck at the debt's face value, and risky debt equals risk-free debt minus a put option on the assets.

9. In the Merton model, how is equity valued, and what does that imply for debt?

   Equity is a European call option on firm assets $V$ with strike equal to debt face value $K$ at maturity $T$. Holding risky debt is equivalent to holding risk-free debt and writing a put on the firm's assets: $D_0 = K e^{-rT} - \text{Put}(V_0, K, T)$.

10. In the Merton model, write the risk-neutral probability of default at maturity in terms of the standard normal CDF.

    $$PD = N(-d_2), \quad d_2 = \frac{\ln(V_0/K) + \left(r - \tfrac{1}{2}\sigma_V^{2}\right)T}{\sigma_V \sqrt{T}}$$ where $V_0$ is current asset value, $K$ the debt face value, $\sigma_V$ asset volatility, $r$ the risk-free rate, and $N(\cdot)$ the standard normal CDF.

11. In the Merton model, what is the "distance to default" and how is it interpreted?

    Distance to default is the number of standard deviations the firm's asset value is above the default point: $DD = d_2 = \dfrac{\ln(V_0/K) + (r - \tfrac{1}{2}\sigma_V^{2})T}{\sigma_V \sqrt{T}}$. A larger $DD$ means default is farther away; $PD = N(-DD)$.

12. Why are a firm's asset value $V$ and asset volatility $\sigma_V$ problematic in the Merton model, and how are they obtained?

    $V$ and $\sigma_V$ are not directly observable. They are backed out (e.g., via the KMV approach) from observable equity value and equity volatility using the option pricing relationship and the link $\sigma_E E = N(d_1)\,\sigma_V V$, solving the two equations simultaneously.

13. State two key limitations of the Merton structural model.

    (1) It assumes default can occur only at debt maturity and a simple single-zero-coupon capital structure, ignoring early default and complex debt; (2) firm asset value and volatility are unobservable, and the model tends to understate short-horizon default probabilities and credit spreads.

14. How do reduced-form (intensity) models treat the timing of default?

    Default arrives as the first jump of a Poisson-type process with a hazard rate (intensity) $\lambda$. Default is exogenous and unpredictable rather than triggered by asset value crossing a barrier; intensities are calibrated to market prices (bond spreads, CDS).

15. In a reduced-form model with constant hazard rate $\lambda$, write the survival probability and the default probability over horizon $t$.

    Survival probability: $P(\tau > t) = e^{-\lambda t}$. Cumulative default probability: $PD(t) = 1 - e^{-\lambda t}$. The instantaneous probability of default given survival is $\lambda\, dt$.

16. Contrast the conceptual nature of default in structural vs. reduced-form models.

    Structural models make default endogenous and predictable — driven by the firm's asset value relative to debt, with economic interpretation. Reduced-form models make default exogenous and inaccessible (a surprise jump) — calibrated to market data, easier to fit spreads but with less structural/economic meaning.

17. What is a credit spread, and what does it compensate investors for?

    A credit spread is the yield premium of a risky bond over the comparable risk-free rate. It compensates investors primarily for expected default loss (PD × LGD), plus risk premia for default-risk uncertainty, liquidity, and taxes.

18. Give the standard approximation linking the credit spread, risk-neutral PD, and recovery.

    $$s \approx \lambda \times LGD = \lambda \times (1 - R)$$ where $s$ is the continuously-compounded credit spread, $\lambda$ the risk-neutral default intensity, $R$ the recovery rate, and $LGD = 1-R$ the loss given default.

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