100+ Free PRM Practice Questions

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Question 1

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Which of the following is a property of the standard normal distribution?

Mean of 0 and standard deviation of 1

Mean of 1 and standard deviation of 0

Mean of 0 and variance of 0.5

Skewness of 1 and kurtosis of 3

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2026 Statistics

Key Facts: PRM Exam

2 exams

PRM 1 + PRM 2

PRMIA

2 years

Window to complete both

PRMIA

60%

Scaled Passing Score

PRMIA

~$725

Per-Exam Fee

Bundle discount for members

300-500 hrs

Recommended Study

Both exams combined

Exam 1 waived

For CFA, CIIA, FRM holders

PRMIA exemption policy

The PRM is PRMIA's flagship two-exam designation (PRM 1 + PRM 2) covering quantitative methods, financial theory, instruments, risk models, and Basel III/ERM frameworks. Each exam is roughly 2-3 hours and costs about $725, with a 60% scaled passing score. Candidates have 2 years to pass both. CFA, CIIA, and FRM holders skip PRM Exam 1 and only sit for Exam 2. Plan on 300-500 study hours total. Expected Shortfall, Merton credit models, and Basel III capital ratios are heavily tested.

Sample PRM Practice Questions

Try these sample questions to test your PRM exam readiness. Each question includes a detailed explanation. Start the interactive quiz above for the full 100+ question experience with AI tutoring.

1Which of the following is a property of the standard normal distribution?

A.Mean of 0 and standard deviation of 1

B.Mean of 1 and standard deviation of 0

C.Mean of 0 and variance of 0.5

D.Skewness of 1 and kurtosis of 3

Explanation: The standard normal distribution has a mean of 0 and a standard deviation (and variance) of 1. It is symmetric, so its skewness is 0, and its excess kurtosis is 0 (raw kurtosis 3). Any normally distributed random variable can be standardized to N(0,1) using Z = (X - mu) / sigma.

2In an OLS regression, heteroskedasticity primarily affects which of the following?

A.The unbiasedness of the coefficient estimates

B.The standard errors of the coefficient estimates

C.The R-squared of the regression

D.The number of observations needed

Explanation: Under heteroskedasticity, OLS estimators remain unbiased and consistent but are no longer efficient (BLUE). The standard errors are biased, which invalidates t-statistics and confidence intervals. White or Huber-White robust standard errors are commonly used to correct inference.

3A GARCH(1,1) model expresses the conditional variance as sigma_t^2 = omega + alpha * epsilon_{t-1}^2 + beta * sigma_{t-1}^2. The unconditional (long-run) variance is finite only if:

A.alpha + beta < 1

B.alpha + beta = 1

C.alpha + beta > 1

D.omega = 0

Explanation: Stationarity of GARCH(1,1) requires alpha + beta < 1, ensuring the unconditional variance omega / (1 - alpha - beta) is positive and finite. When alpha + beta = 1, the process is integrated GARCH (IGARCH) and shocks have permanent effects on volatility.

4Which of the following best describes an ARIMA(1,1,1) model?

A.One autoregressive term, one moving-average term, applied to the level series

B.One autoregressive term, one differencing operation, and one moving-average term

C.One seasonal term, one trend term, and one error term

D.Three autoregressive terms with no differencing

Explanation: ARIMA(p,d,q) uses p autoregressive terms, d differencing operations, and q moving-average terms. ARIMA(1,1,1) takes the first difference of the series and fits an ARMA(1,1) model to the differenced series. Differencing is used to remove a unit root and induce stationarity.

5A risk manager wants to maximize a portfolio's expected return subject to the constraint that the portfolio weights sum to 1. The standard tool to solve this constrained optimization is:

A.Newton-Raphson root finding

B.Lagrange multipliers

C.Cholesky decomposition

D.Gauss elimination

Explanation: Lagrange multipliers convert an equality-constrained optimization into an unconstrained problem by adding the constraint multiplied by lambda to the objective. For inequality constraints, the Karush-Kuhn-Tucker (KKT) conditions generalize the approach.

6Which condition is NOT one of the Karush-Kuhn-Tucker (KKT) conditions for a constrained optimum?

A.Stationarity of the Lagrangian

B.Primal feasibility

C.Dual feasibility (lambda >= 0 for inequality constraints)

D.Strict convexity of the objective function

Explanation: The KKT conditions are stationarity, primal feasibility, dual feasibility, and complementary slackness. Strict convexity is sufficient to guarantee a unique global optimum but is not itself a KKT condition. KKT generalizes Lagrange multipliers to handle inequality constraints.

7A portfolio's daily returns are normally distributed with mean 0 and standard deviation 2%. What is the approximate one-day 95% parametric VaR per $1,000,000 of exposure?

A.$20,000

B.$32,900

C.$46,500

D.$50,000

Explanation: Parametric one-day VaR at 95% = z_0.95 * sigma * V = 1.645 * 0.02 * 1,000,000 = $32,900. Note that the 95% one-tail z-score is 1.645, not 1.96 (which is the two-tail value). At 99% confidence the z is 2.326.

8Which test detects a unit root in a time series, indicating non-stationarity?

A.Jarque-Bera test

B.Augmented Dickey-Fuller test

C.Breusch-Pagan test

D.Durbin-Watson test

Explanation: The Augmented Dickey-Fuller (ADF) test tests the null hypothesis of a unit root (non-stationarity). Jarque-Bera tests normality of residuals; Breusch-Pagan tests for heteroskedasticity; Durbin-Watson tests first-order autocorrelation.

9If two random variables X and Y have a correlation coefficient of 0, they are necessarily:

A.Independent

B.Linearly unrelated, but possibly nonlinearly dependent

C.Identically distributed

D.Both normally distributed

Explanation: Zero correlation only rules out a linear relationship. Variables can have zero correlation while being nonlinearly dependent (e.g., Y = X^2 with X symmetric around 0). Independence implies zero correlation, but the converse holds only for jointly normal variables.

10In a linear regression Y = beta0 + beta1 X + epsilon, multicollinearity refers to:

A.Non-constant variance of the error term

B.High correlation among the explanatory variables

C.Autocorrelation of the residuals

D.Non-normality of the residuals

Explanation: Multicollinearity arises when two or more explanatory variables are highly correlated, inflating the variance of coefficient estimates and making them unstable. It does not affect coefficient bias but reduces statistical power. Variance Inflation Factors (VIFs) above ~10 typically indicate a problem.

About the PRM Exam

The PRM (Professional Risk Manager) Designation from PRMIA is a two-exam credential covering the full risk-management body of knowledge: quantitative foundations, financial theory, financial instruments, risk modeling (market, credit, operational), and risk management frameworks including Basel III and ERM. Both exams must be completed within a 2-year window. CFA Charterholders, CIIA, and FRM holders are exempt from PRM Exam 1 and only need to pass Exam 2.

Questions

100 scored questions

Time Limit

Two exams (PRM 1 + PRM 2), 2-3 hrs each

Passing Score

60% scaled

Exam Fee

~$725 per exam (bundle discount for members) (PRMIA)

PRM Exam Content Outline

15%

Quantitative Foundations

Probability distributions, regression diagnostics, ARIMA and GARCH time series, optimization (Lagrange multipliers, KKT conditions), Monte Carlo methods

15%

Financial Theory

Market microstructure, Modern Portfolio Theory, efficient frontier, tangency portfolio, CAPM, APT, Fama-French multifactor models, asset pricing

20%

Financial Instruments

Bond pricing, YTM, Macaulay/modified/effective duration, convexity, OAS, MBS prepayment, options (Black-Scholes, binomial, Greeks), futures, forwards, IRS, basis swaps, CDS

25%

Risk Models

Parametric/historical/Monte Carlo VaR, Expected Shortfall (coherent), Kupiec POF and Christoffersen backtests, FRTB IMA/SA, Merton/KMV and reduced-form credit models, CVA/DVA/FVA, operational risk

15%

Risk Management Frameworks

Basel III/IV capital (CET1, leverage, LCR, NSFR, output floor), COSO 2017 ERM, ISO 31000, three lines of defense, risk appetite/tolerance/capacity, S&P ERM rating

10%

Case Studies & Best Practices

Risk failures (Barings, LTCM, JPM London Whale, Archegos), PRMIA Code of Conduct, Standards of Best Practice in Risk Management, governance lessons

How to Pass the PRM Exam

What You Need to Know

Passing score: 60% scaled
Exam length: 100 questions
Time limit: Two exams (PRM 1 + PRM 2), 2-3 hrs each
Exam fee: ~$725 per exam (bundle discount for members)

Keys to Passing

Complete 500+ practice questions
Score 80%+ consistently before scheduling
Focus on highest-weighted sections
Use our AI tutor for tough concepts

PRM Study Tips from Top Performers

1Memorize Expected Shortfall as the coherent risk measure that replaces VaR under FRTB — VaR is not subadditive

2Master Black-Scholes Greeks: delta, gamma, vega, theta, rho — and put-call parity C - P = S - PV(K)

3Learn EL = PD x LGD x EAD cold, plus Merton distance-to-default and KMV adjustments

4Know Basel III thresholds: CET1 4.5% min + 2.5% conservation buffer, leverage ratio 3% (4% for G-SIBs), LCR and NSFR both 100%, output floor 72.5%

5Memorize the 7 Basel operational-risk event types and the move from AMA to the Standardised Approach (SA) in Basel III

6Practice Kupiec POF and Christoffersen Markov backtests — both appear in VaR validation questions

7Review COSO 2017 ERM five components and the three lines of defense model for governance questions

Frequently Asked Questions

Are CFA, FRM, or CIIA holders exempt from any PRM exams?

Yes. CFA Charterholders, CIIA holders, and FRM-certified professionals are exempt from PRM Exam 1 and only need to pass PRM Exam 2 to earn the designation. The exemption recognizes overlap in quantitative, markets, and instruments coverage and significantly shortens the path to the PRM credential. Members must apply for the exemption and pay the standard exam fee for Exam 2.

How is the PRM exam structured?

The PRM is a two-exam designation: PRM Exam 1 and PRM Exam 2, each roughly 2-3 hours long and delivered via Pearson VUE. Both must be passed within a 2-year window. Each exam is multiple-choice and uses scaled scoring with a passing score around 60%. PRMIA does not publish pass rates, but candidates report PRM 2 as the more quantitative and challenging of the two.

How much does the PRM designation cost?

Each PRM exam is approximately $725 standalone, with bundle discounts available when registering for both. PRMIA members get reduced rates, and the bundle is the most cost-effective path. Total cost for non-members typically runs $1,400-$1,500 for both exams; members save several hundred dollars. Candidates exempt from Exam 1 (CFA/FRM/CIIA) pay only one exam fee.

How long should I study for the PRM?

Most candidates need 300-500 total study hours across both PRM exams. Strong quantitative backgrounds (CFA, FRM, math/finance graduate) can complete in 250-350 hours; candidates new to derivatives and risk modeling should plan 500+ hours. The two-year window typically translates to 6-12 months of part-time study with focused review on Expected Shortfall, Merton credit models, and Basel III ratios.

What is the difference between PRM and FRM?

Both are top-tier risk management credentials. The PRM (PRMIA) emphasizes practitioner frameworks, Basel/regulatory depth, and ERM, with two exams totaling ~5 hours. The FRM (GARP) is more quant- and product-heavy, with two 4-hour exams. FRM has a larger global footprint (~80,000+ holders), while PRM is recognized in regulatory and ERM-heavy roles. FRM holders can skip PRM Exam 1.

What topics are most heavily tested on the PRM?

Risk Models account for ~25% of combined PRM content, making VaR variants, Expected Shortfall (coherent risk measure replacing VaR under FRTB), Merton structural and reduced-form credit models, CVA, and operational risk frameworks the highest-yield areas. Financial Instruments adds another 20% (Black-Scholes Greeks, duration/convexity, swaps, CDS). Basel III capital ratios (CET1 4.5% + 2.5% buffer, LCR/NSFR 100%) and COSO 2017 ERM are heavily tested in frameworks.