Potential future exposure
Potential Future Exposure (PFE) is the maximum expected credit exposure over a specified period of time calculated at some level of confidence (i.e. at a given quantile).
PFE is a measure of counterparty risk/credit risk. It is calculated by evaluating existing trades done against the possible market prices in future during the lifetime of transactions. It can be called sensitivity of risk with respect to market prices. The calculated expected maximum exposure value is not to be confused with the maximum credit exposure possible. Instead, the maximum credit exposure indicated by the PFE analysis is an upper bound on a confidence interval for future credit exposure.
Credit risk managers have traditionally remained focused on current exposure measurement (i.e., current mark-to-market exposure, plus outstanding receivables) and collateral management. The problem with this focus is that it places excessive emphasis on the present and fails to provide an acceptable indication of credit risk at some point in the future. Because losses from credit risk take a relatively long time to evolve, a more useful measure of exposure is potential exposure. Potential exposure is not like current exposure. It exists in the future and therefore represents a range or distribution of outcomes rather than a single point estimate.
Relevance
PFE is essential to bank regulation under Basel III and Dodd Frank. Fundamentally, to assess the safety of a bank's asset portfolio and the adequacy of its Tier 1 capital (and Tier 2 capital), one needs to evaluate whether it is resilient under severely stressing market moves.
Using option's strategies, it is easy for a trader to set up a "black swan" type trade that will pay a moderate money upfront, but yield catastrophic losses if the underlying securities' price moves above a certain "out of the money" strike price. This is akin to writing a large amount of insurance contracts against a rare but catastrophic risk. The vast majority of the time - and for many years running - the trader can appear to have a highly profitable strategy (even if the trade actually had negative expected value). When the rare event occurs, the person (or more likely her employer) who wrote the "insurance" (or in options terminology - the person who was "short a put or call" / "shorted volatility" / was "short gamma") sustains massive losses and may go bankrupt. These sorts of trades are behind most major collapses in the past 30 years - including much of the savings and loan crisis of the 1980s, Kidder Peabody, Enron, AIG, Lehman and even later (relatively small) losses at JP Morgan.
These crashes indirectly tax the vast majority of citizens who did not gain from the trading profits and did not choose to bear these risks. Essentially it can socialize losses while keeping profits private. This is for two main reasons. First, government directly (or indirectly) insures many retail deposits (to prevent bank runs and to promote savings), and many quasi-government agencies (ex : FNMA, Freddie Mac) have de facto government backing. Second, even when a major firm does not have government insured deposits, it can be "systemically important" (such as AIG) - its failure would potentially cause panic, destroy market liquidity, and precipitate a crash and potential widespread economic contraction / depression. (This is the reasoning behind "too big to fail".)
For these reasons, regulation needs to evaluate and respond to potential future risks. PFE is one important measure in this regard.
Expected Exposure
The Expected Exposure (EE) is defined similarly to the PFE, except that the average is used instead of a specific quantile.
The EE represents the estimated average loss at a specific future point of time that a lender would suffer from if the borrower (counterparty) fully defaults on his debt (i.e. if the Loss Given Default (LGD) was 100%).
External links
- Online Calculators for EE and PFE - QuantCalc, Online Financial Math Calculator