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FRM Part II practice questions

30 free exam-style questions across every topic area, each with the answer and the reasoning behind it.

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30 questions, 5 for each topic area, written in the style of the FRM® Part II exam. Pick an answer before you open the explanation; the reasoning matters more than the letter. Topics follow the published topic weights.

Market Risk Measurement & Management

20% of the exam

VaR and ES estimation, backtesting, EVT, GARCH, copulas, FRTB.

Question 1

A portfolio has a 1-day 99% VaR of $2.5m. Assuming i.i.d. returns, the 10-day 99% VaR is closest to:

VaR(1) = $2.5m · T = 10
  1. A$7.9m
  2. B$25.0m
  3. C$2.5m
  4. D$5.0m
Show the answer

A. $7.9m

√10 ≈ 3.162, so 2.5 × 3.162 ≈ $7.9m. Square-root-of-time scaling requires independent, identically distributed returns.

Curriculum area: Market Risk — VaR Measurement

Question 2

A bank’s 99% 1-day VaR model produced 9 exceptions in 250 trading days. This most likely indicates:

Expected exceptions = 0.01 × 250 = 2.5
  1. AThe model overstates risk
  2. BThe model is well calibrated
  3. CThe model understates risk
  4. DNothing without expected shortfall data
Show the answer

C. The model understates risk

Nine breaches against 2.5 expected is far more than chance would suggest — the model understates risk. It sits at the top of the Basel yellow zone (5–9 exceptions); ten or more would be red.

Curriculum area: Market Risk — Backtesting VaR

Question 3

Breaches of a VaR model cluster in a single stressed week rather than occurring evenly. The most appropriate test is:

  1. AKupiec's unconditional coverage test
  2. BChristoffersen's conditional coverage test
  3. CA Jarque–Bera normality test
  4. DA Dickey–Fuller unit root test
Show the answer

B. Christoffersen's conditional coverage test

Kupiec tests only the number of exceptions. Christoffersen adds an independence test, which is what detects clustering.

Curriculum area: Market Risk — Backtesting VaR

Question 4

In extreme value theory using the peaks-over-threshold approach, a positive shape parameter ξ indicates:

  1. ATails thinner than the normal distribution
  2. BTails fatter than the normal distribution
  3. CA bounded loss distribution
  4. DThat the threshold was set too low
Show the answer

B. Tails fatter than the normal distribution

A positive ξ corresponds to the Fréchet domain — heavy tails, decaying more slowly than the normal distribution.

Curriculum area: Market Risk — Extreme Value Theory

Question 5

The Gaussian copula was widely criticised after 2008 primarily because it:

  1. ACannot join different marginal distributions
  2. BExhibits zero tail dependence
  3. CRequires equal marginals for all variables
  4. DCannot be calibrated to market data
Show the answer

B. Exhibits zero tail dependence

The Gaussian copula implies assets become independent in the extreme tail, exactly the opposite of observed crisis behaviour. Student t copulas admit tail dependence.

Curriculum area: Market Risk — Correlation and Copulas

Credit Risk Measurement & Management

20% of the exam

Merton and reduced-form models, credit VaR, counterparty risk, CVA, CDOs.

Question 6

Under the Merton model, an increase in the volatility of the firm’s assets will:

  1. AIncrease equity value and decrease default probability
  2. BIncrease equity value and increase default probability
  3. CDecrease equity value and increase default probability
  4. DLeave equity value unchanged
Show the answer

B. Increase equity value and increase default probability

Equity is a call on the firm's assets, so higher asset volatility raises its value. It simultaneously raises the probability the assets fall below the debt.

Curriculum area: Credit Risk — Structural Default Models

Question 7

Holding individual default probabilities constant, an increase in default correlation across a credit portfolio will:

  1. AIncrease expected loss and increase credit VaR
  2. BLeave expected loss unchanged and increase credit VaR
  3. CIncrease expected loss and leave credit VaR unchanged
  4. DReduce both measures
Show the answer

B. Leave expected loss unchanged and increase credit VaR

Expected loss depends only on individual PDs. Correlation fattens the tail of the loss distribution, which is what credit VaR measures.

Curriculum area: Credit Risk — Portfolio Credit Risk

Question 8

A bank buys credit protection on a sovereign from a bank domiciled in that same sovereign. This is a clear example of:

  1. ARight-way risk
  2. BWrong-way risk
  3. CBasis risk
  4. DSettlement risk
Show the answer

B. Wrong-way risk

The protection seller is most likely to default precisely when the protection is needed, so exposure and counterparty credit quality move adversely together.

Curriculum area: Credit Risk — Counterparty Risk and CVA

Question 9

In a CDO structure, an increase in default correlation across the collateral pool will most likely:

  1. ABenefit the equity tranche and harm the senior tranche
  2. BHarm the equity tranche and benefit the senior tranche
  3. CBenefit both tranches
  4. DHave no effect on either tranche
Show the answer

A. Benefit the equity tranche and harm the senior tranche

Higher correlation raises the probability of zero losses (helping equity) and of very large losses (harming senior). Senior tranches are effectively short correlation.

Curriculum area: Credit Risk — Structured Credit and CDOs

Question 10

Which mechanism most directly reduces counterparty credit exposure without changing the underlying trades?

  1. AIncreasing the notional
  2. BClose-out netting and collateral agreements
  3. CExtending the maturity
  4. DWidening the credit spread charged
Show the answer

B. Close-out netting and collateral agreements

Netting offsets positive and negative exposures to the same counterparty, and collateral covers the residual. Neither alters the trades themselves.

Curriculum area: Credit Risk — Netting, Collateral and Margining

Operational Risk & Resilience

20% of the exam

RCSA and loss data, model risk, cyber, third parties, financial crime, Basel.

Question 11

In a loss distribution approach, operational loss frequency is most commonly modelled with:

  1. AA lognormal distribution
  2. BA Poisson distribution
  3. CA generalised Pareto distribution
  4. DA Student t distribution
Show the answer

B. A Poisson distribution

Frequency is a count over a fixed period, which the Poisson distribution describes. Severity is typically lognormal, with a Pareto tail.

Curriculum area: Operational Risk — Modelling Loss Distributions

Question 12

A firm’s risk management function both designs the control framework and performs the independent assurance review of it. This most directly compromises:

  1. AThe first line of defence
  2. BThe separation of the second and third lines of defence
  3. CThe board's risk appetite statement
  4. DThe RCSA process only
Show the answer

B. The separation of the second and third lines of defence

Independent assurance belongs to internal audit, the third line. A function cannot independently assure the controls it designed.

Curriculum area: Operational Risk — Three Lines of Defence

Question 13

A model validated successfully on historical data fails badly in a new market regime. This is best classified as a failure of:

  1. AImplementation accuracy
  2. BConceptual soundness
  3. CData quality controls
  4. DChange management
Show the answer

B. Conceptual soundness

The model was built and coded correctly but rests on assumptions that do not hold in the new regime — a conceptual soundness failure.

Curriculum area: Operational Risk — Model Risk Management

Question 14

A firm outsources a critical process to a third party that suffers an outage. Regulatory accountability for the disruption rests with:

  1. AThe third party alone
  2. BThe firm, which cannot outsource accountability
  3. CBoth parties equally by default
  4. DNeither, if the contract contains a force majeure clause
Show the answer

B. The firm, which cannot outsource accountability

Outsourcing an activity never outsources the accountability. The firm remains responsible for the resilience of its critical services.

Curriculum area: Operational Risk — Third-Party and Outsourcing Risk

Question 15

Internal loss data alone is generally insufficient for operational risk capital because it:

  1. AIs not audited
  2. BIs too sparse in the tail to estimate extreme severity
  3. COverstates high-frequency low-severity events
  4. DCannot be used under Basel rules
Show the answer

B. Is too sparse in the tail to estimate extreme severity

A single firm rarely experiences enough extreme events to estimate the tail, so external data and scenario analysis supplement internal data.

Curriculum area: Operational Risk — Loss Data Collection

Liquidity & Treasury Risk

15% of the exam

Funding vs market liquidity, LVaR, transfer pricing, IRRBB, LCR and NSFR.

Question 16

A position worth $50m has a VaR of $2m and a bid–ask spread of 0.40%. Liquidity-adjusted VaR using the exogenous spread approach is closest to:

V $50m · VaR $2m · spread 0.40%
  1. A$2.00m
  2. B$2.10m
  3. C$2.20m
  4. D$4.00m
Show the answer

B. $2.10m

LVaR = VaR + ½ × spread × V = 2m + 0.5 × 0.004 × 50m = 2m + 0.1m = $2.10m.

Curriculum area: Liquidity Risk — Liquidity-Adjusted VaR

Question 17

The liquidity coverage ratio requires a bank to hold high-quality liquid assets sufficient to cover net cash outflows over:

  1. A5 days
  2. B30 days
  3. C90 days
  4. DOne year
Show the answer

B. 30 days

The LCR is a 30-day stressed horizon. The NSFR is the one-year structural measure.

Curriculum area: Liquidity Risk — Basel Liquidity Framework

Question 18

A fund forced to sell assets to meet redemptions depresses prices, triggering further redemptions and further sales. This is best described as:

  1. ABasis risk
  2. BA liquidity spiral
  3. CWrong-way risk
  4. DRegulatory arbitrage
Show the answer

B. A liquidity spiral

Funding pressure forces sales, which worsens market liquidity, which worsens funding pressure — the self-reinforcing liquidity spiral.

Curriculum area: Liquidity Risk — Funding versus Market Liquidity

Question 19

Without funds transfer pricing, a bank’s long-dated lending business will most likely appear:

  1. ALess profitable than it is, because liquidity cost is over-allocated
  2. BMore profitable than it is, because liquidity cost is not charged to it
  3. CCorrectly priced, since liquidity cost is a central function
  4. DUnaffected, since FTP is an accounting convention only
Show the answer

B. More profitable than it is, because liquidity cost is not charged to it

FTP charges business lines for the liquidity they consume. Without it, long-dated lending appears artificially profitable at the centre's expense.

Curriculum area: Liquidity Risk — Transfer Pricing

Question 20

Which asset receives no haircut in the LCR high-quality liquid asset calculation?

  1. ALevel 1 assets
  2. BLevel 2A assets
  3. CLevel 2B assets
  4. DAll HQLA receive the same haircut
Show the answer

A. Level 1 assets

Level 1 assets — cash, central bank reserves and qualifying sovereign debt — are counted at full value. Level 2A and 2B take haircuts and are capped.

Curriculum area: Liquidity Risk — Basel Liquidity Framework

Risk & Investment Management

15% of the exam

Factor theory, risk budgeting, attribution, hedge funds, illiquid assets.

Question 21

A small allocation to an asset with high volatility and high correlation to the rest of the portfolio can dominate the risk budget. The measure that reveals this is:

  1. AThe position weight
  2. BMarginal contribution to risk
  3. CThe Sharpe ratio of the position
  4. DThe position's standalone volatility
Show the answer

B. Marginal contribution to risk

Marginal contribution to risk accounts for both the volatility and the correlation with the existing portfolio, which a weight or standalone volatility cannot.

Curriculum area: Risk and Investment Management — Risk Budgeting

Question 22

When a hedge fund joins an index, the index provider adds the fund’s prior track record. The resulting distortion is:

  1. ASurvivorship bias
  2. BBackfill bias
  3. CSelection bias in the risk-free rate
  4. DSmoothing bias
Show the answer

B. Backfill bias

Backfill bias arises because funds tend to join after a strong period, so the added history inflates reported index performance.

Curriculum area: Risk and Investment Management — Hedge Fund Indices

Question 23

Reported returns on an illiquid private portfolio display strong positive autocorrelation. Unsmoothing the series will:

  1. ALower the estimated volatility and raise the Sharpe ratio
  2. BRaise the estimated volatility and lower the Sharpe ratio
  3. CLeave volatility unchanged but raise correlation
  4. DLower both volatility and correlation
Show the answer

B. Raise the estimated volatility and lower the Sharpe ratio

Smoothing understates true volatility and correlation. Correcting for it raises volatility, which reduces the Sharpe ratio.

Curriculum area: Risk and Investment Management — Illiquid Assets

Question 24

Factor theory holds that assets earn a risk premium because they:

  1. ABelong to a particular asset class
  2. BPerform poorly in bad times
  3. CHave high historical volatility
  4. DAre held by institutional investors
Show the answer

B. Perform poorly in bad times

Premia compensate exposure to bad times, not asset labels. Two differently labelled assets with the same factor exposure should earn similar returns.

Curriculum area: Risk and Investment Management — Factor Theory

Question 25

A manager reports strong alpha, but a factor regression shows most of the excess return is explained by a persistent value tilt. The appropriate conclusion is that the return reflects:

  1. AGenuine manager skill
  2. BSystematic factor exposure available more cheaply
  3. CA backtesting error
  4. DSurvivorship bias in the benchmark
Show the answer

B. Systematic factor exposure available more cheaply

Return attributable to a known factor is beta, not alpha, and can be obtained through cheaper systematic implementations.

Curriculum area: Risk and Investment Management — Factor Theory

Current Issues in Financial Markets

10% of the exam

This cycle's readings — AI in finance, climate risk, digital assets, bank stress.

Question 26

The Current Issues topic differs from every other FRM topic area because it:

  1. AIs not examined
  2. BIs replaced substantially each exam cycle
  3. CContains only quantitative material
  4. DCarries the largest weight in Part II
Show the answer

B. Is replaced substantially each exam cycle

The reading list rotates each year, so prior-year materials are unreliable. GARP publishes the current list directly.

Curriculum area: Current Issues in Financial Markets — Scope

Question 27

The principal supervisory concern with machine learning models used in credit decisions is:

  1. ATheir computational cost
  2. BLimited explainability and the resulting model governance gap
  3. CTheir inability to handle large datasets
  4. DThat they cannot be backtested
Show the answer

B. Limited explainability and the resulting model governance gap

Supervisors expect firms to explain credit decisions. Opaque models create a governance problem: who validates a model nobody fully understands.

Curriculum area: Current Issues — AI and Machine Learning in Finance

Question 28

A scenario describing rapid, well-signalled decarbonisation policy is best characterised as:

  1. AHigh physical risk and low transition risk
  2. BLow physical risk and high transition risk
  3. CHigh physical and high transition risk
  4. DLow physical and low transition risk
Show the answer

B. Low physical risk and high transition risk

Fast policy action raises transition risk for exposed sectors while limiting the warming that drives physical risk. The scenarios deliberately trade the two off.

Curriculum area: Current Issues — Climate and Transition Risk

Question 29

The 2023 US regional banking stress is best explained by the interaction of:

  1. ACredit losses on commercial loans and inadequate provisions
  2. BUnrealised duration losses and concentrated, digitally mobile uninsured deposits
  3. COperational failures in payment systems
  4. DCounterparty defaults in the derivatives market
Show the answer

B. Unrealised duration losses and concentrated, digitally mobile uninsured deposits

Held-to-maturity portfolios carried large unrealised losses while a concentrated uninsured deposit base withdrew faster than liquidity rules assumed.

Curriculum area: Current Issues — Post-2023 Banking Stress

Question 30

A key financial stability concern with fiat-referenced stablecoins is that they:

  1. ACannot be transferred across borders
  2. BAre subject to run dynamics if reserve quality or redemption is doubted
  3. CPay a variable interest rate to holders
  4. DAre always fully insured by deposit schemes
Show the answer

B. Are subject to run dynamics if reserve quality or redemption is doubted

A stablecoin is a redeemable claim on a reserve pool. Doubt about reserve quality or redemption capacity produces classic run dynamics.

Curriculum area: Current Issues — Digital Assets and Stablecoins

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These are original practice questions in the style of the exam, not official questions. CFA® and FRM® are registered trademarks of their respective owners; GroundLearn is not affiliated with CFA Institute or GARP.

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