FRM Exam Part II · Derivatives

Counterparty Risk and Credit Exposure Metrics: EE, PFE and EPE

Updated 11 October 2026 · Fact-checked

Counterparty credit risk is the risk that an OTC derivative counterparty defaults while the contract has positive value to you. Exposure metrics measure that value over time: current exposure is today's positive value, EE is the average future positive value, PFE is a high percentile of it, and EPE is the time-average of EE.

Understand Counterparty Risk and Credit Exposure Metrics

Counterparty credit risk (CCR) is the risk that your counterparty defaults before the final settlement of a transaction's cash flows. It is different from a loan. In a loan, you know the amount lent. In an OTC derivative, the amount you could lose changes with market prices and can be positive or negative.

This gives exposure its key feature: it is floored at zero. If the contract is worth +USD 5 million to you and the counterparty defaults, you lose up to that value (before recovery). If it is worth -USD 5 million to you, you still owe it, so you do not gain from the default. So exposure = max(V, 0), where V is the market value of the netting set to you.

Because future values are uncertain, we need several measures. Current exposure (CE) is max(V, 0) today. It is known, but it says nothing about the future. Expected exposure (EE) at a future date t is the average of the positive exposure across all simulated scenarios at t. Potential future exposure (PFE) at date t is a high percentile (for example 95% or 99%) of the exposure distribution at t. It is a worst-case style measure used for limits.

To get one number, you average EE over time. Expected positive exposure (EPE) is the time-weighted average of EE over a period, usually one year. Effective EE is EE forced to be non-decreasing over time (the running maximum), and effective EPE is the time-average of effective EE over the first year, or until the longest-maturity netting-set contract matures if that is sooner. Basel uses effective EPE, multiplied by alpha (set at 1.4 in the regulatory framework), to get exposure at default in the internal model method.

Keep the roles clear. EE and EPE are averages and feed pricing and capital (CVA and EAD). PFE is a tail measure and feeds credit limits. Exposure profiles also depend on product: for example, a swap profile rises then falls as payments are made and maturity nears.

Key formulas to remember

Exposure of a netting set: Exposure = max(V, 0); V is the net market value to you. Floored at zero because you cannot gain from a counterparty default.
Current exposure: CE = max(V₀, 0); Today's replacement cost, ignoring collateral unless stated.
Expected exposure: EE(t) = E[max(V(t), 0)]; Mean of the positive part, not max of the mean. Includes the zeros from negative scenarios.
Potential future exposure: PFE(t) = the α-percentile of max(V(t), 0); α is typically 95% or 99%. Compare with VaR, but PFE looks at the positive side only and at future dates.
Expected positive exposure: EPE = Σ EE(tₖ) × Δtₖ ÷ T; Time-weighted average of EE over [0, T]. With equal time steps it is the simple average of EE.
Effective EE: Effective EE(tₖ) = max(Effective EE(tₖ₋₁), EE(tₖ)); Non-decreasing profile. Captures rollover of short-dated trades.
Effective EPE: Effective EPE = Σ Effective EE(tₖ) × Δtₖ over the first year (or to maturity if shorter) ÷ the length of that period; Average over one year, or until the longest-maturity contract in the netting set matures if that is sooner.
Regulatory EAD (internal model method): EAD = α × Effective EPE, with α = 1.4; Alpha is the regulatory default; supervisors may allow banks to estimate their own, subject to a floor.

How to solve Counterparty Risk and Credit Exposure Metrics questions

Use this method for any question on CE, EE, PFE, EPE or effective EPE.

1Identify what is asked: a single-date measure (CE, EE, PFE) or a time-average (EPE, effective EPE).
2Work at the netting-set level. Net the trade values first if a netting agreement applies, then take max(V, 0).
3For EE, average the positive exposures across scenarios, counting negative scenarios as zero. Divide by the total number of scenarios.
4For PFE, sort the positive exposures and read the required percentile. State the confidence level.
5For EPE, average EE across the time points, weighting by time step if steps are unequal.
6For effective EPE, first build effective EE as a running maximum, then average over the first year only.
7If asked for EAD, multiply effective EPE by 1.4 unless the question gives a different alpha.
8Check the answer: at high percentiles (for example 95% or 99%), PFE is normally above EE at the same date. Effective EPE is at least EPE when both are measured over the same time horizon and grid.

Quickest way: Positive part, then average or percentile

When to use it: Use this when a question gives a table of scenario values or an EE profile and asks for one metric.

Replace every negative value with zero.
Single date, average wanted: add the values and divide by the number of scenarios.
Single date, high percentile wanted: rank values and pick the percentile.
Profile over time, EPE wanted: average the EE values (equal steps).
Effective EPE wanted: carry forward the highest EE so far, then average.
Eliminate options where a high-percentile PFE (95% or 99%) is below EE, or where effective EPE is below EPE over the same horizon and grid.

Common mistakes in Counterparty Risk and Credit Exposure Metrics

Computing EE as max(average V, 0) instead of average of max(V, 0).
The two look alike, and averaging first feels natural.
Fix: Floor each scenario at zero first, then average. Because max(V, 0) is convex (an option-like payoff), EE is always greater than or equal to max(mean V, 0).
Confusing EE with PFE.
Both are future exposure measures from the same distribution.
Fix: EE is the mean of positive exposure. PFE is a high percentile. At high confidence levels such as 95% or 99%, PFE is normally above EE at the same date. At a low percentile, or with a long right tail, PFE can be below EE.
Using the plain EE profile for effective EPE.
Students forget that effective EE is non-decreasing.
Fix: Take the running maximum of EE before averaging. Where EE falls, hold the earlier higher value.
Averaging effective EE over the full life of the trade.
EPE is often taught over the trade life.
Fix: Effective EPE uses the first year, or the maturity of the longest contract in the netting set if shorter.
Forgetting the alpha multiplier when computing regulatory EAD.
The EPE calculation feels like the final step.
Fix: EAD = 1.4 × effective EPE under the regulatory default. Write it as the last step.
Treating a negative mark-to-market as a negative exposure that offsets gains with other counterparties.
Confusion between netting within one legally enforceable netting set and across counterparties.
Fix: Netting applies only within a netting set with an enforceable agreement. Across counterparties, each exposure is floored at zero separately.

Worked examples

Example 1

A bank simulates the value of a swap netting set at one date in five equally likely scenarios (USD million): -4, -1, 2, 6, 10. Compute the EE and the 80th-percentile PFE, taking the percentile as the value of the sorted positive exposures at the 80% rank.

Show the solution

Floor each value at zero: 0, 0, 2, 6, 10.
EE = (0 + 0 + 2 + 6 + 10) ÷ 5 = 18 ÷ 5 = 3.6.
Sort exposures: 0, 0, 2, 6, 10. With five equally likely scenarios, the 80% rank is the fourth value, which is 6.
So PFE at 80% = 6, which is above EE of 3.6, as expected.

Answer: EE = USD 3.6 million; 80% PFE = USD 6 million.

Example 2

A netting set has EE at four quarterly dates over one year (USD million): 3, 5, 4, 2. Compute EPE, effective EE, effective EPE and regulatory EAD with alpha = 1.4.

Show the solution

EPE = (3 + 5 + 4 + 2) ÷ 4 = 14 ÷ 4 = 3.5.
Effective EE as running maximum: 3, 5, max(5, 4) = 5, max(5, 2) = 5.
Effective EPE = (3 + 5 + 5 + 5) ÷ 4 = 18 ÷ 4 = 4.5.
EAD = 1.4 × 4.5 = 6.3.

Answer: EPE = USD 3.5 million; effective EPE = USD 4.5 million; EAD = USD 6.3 million.

Exam tips

Write the zero floor on every scenario first. Most wrong options come from skipping it.
Check ordering: at 95% or 99%, PFE is normally above EE, and effective EPE is at least EPE over the same horizon and grid. Use it to remove options fast.
Know which measure serves which purpose: PFE for limits, EE and EPE for pricing and CVA, effective EPE for regulatory EAD.
Read whether the question asks for a time-average over one year or over the life of the trade.
Remember alpha = 1.4 for the regulatory default, and apply it to effective EPE, not to EE.

Practice questions from Derivatives

Counterparty Risk and Credit Exposure Metrics: frequently asked questions

What is the difference between expected exposure and potential future exposure?

EE is the average of positive exposure at a future date across scenarios. PFE is a high percentile of that same distribution, such as 95% or 99%. PFE shows a plausible worst case and EE shows the typical case, so at high confidence levels PFE is normally above EE.

How do I calculate expected positive exposure?

Compute EE at each time point, then take the time-weighted average over the period. With equal time steps, it is the simple average of the EE values. Remember that EE itself is the average of max(V, 0) across scenarios.

Why does effective EPE use a non-decreasing EE?

Short-dated trades in a netting set are usually rolled over, so exposure to the counterparty does not really fall when an early trade matures. Using a running maximum reflects that rollover risk and gives a more conservative exposure figure.

Is current exposure enough to measure counterparty risk?

No. Current exposure is today's replacement cost only. It ignores how values can move before default, so you also need EE, PFE and EPE to capture future exposure.