Potential Future Exposure (PFE) is a standard risk metric for managing business unit counterparty credit risk but there is debate on how it should be calculated. The debate has been whether to use one of many historical ("physical") measures (one per calibration setup), or one of many risk-neutral measures (one per numeraire). However, we argue that limits should be based on the bank's own risk appetite provided that this is consistent with regulatory backtesting and that whichever measure is used it should behave (in a sense made precise) like a historical measure. Backtesting is only required by regulators for banks with IMM approval but we expect that similar methods are part of limit maintenance generally. We provide three methods for computing the bank price of risk from readily available business unit data, i.e. business unit budgets (rate of return) and limits (e.g. exposure percentiles). Hence we define and propose a Risk Appetite Measure, A, for PFE and suggest that this is uniquely consistent with the bank's Risk Appetite Framework as required by sound governance.

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Alignment of financial market incentives and carbon emissions disincentives is key to limiting global warming (Bednar, Obersteiner, Baklanov, Thomson, Wagner, Geden, Allen, and Hall 2021). Regulators and standards bodies have made a start by requiring some carbon-related disclosures

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Wrong way risk (WWR) is a consideration for regulatory capital for credit valuation adjustment (CVA). WWR is also of interest for pricing and accounting and in these cases must include funding as well as exposure and default in CVA and FVA calculation. Here we introduce a model independent approach to WWR for regulatory CVA and also for accounting CVA and FVA. This model independent approach is extremely simple: we just re-write the CVA and FVA integral expressions in terms of their components and then calibrate these components. This provides transparency between component calibration and CVA/FVA effect because there is no model interpretation in between. Including funding in WWR means that there are now two WWR terms rather than the usual one. Using a regulatory inspired calibration from MAR50 we investigate WWR effects for vanilla interest rate swaps and show that the WWR effects for FVA are significantly more material than for CVA. This model independent approach can also be used to compare any WWR model by simply calibrating to it for a portfolio and counterparty, to demonstrate the effects of the model under investigation in terms of components of CVA/FVA calculations. arXiv:2003.03403v1 [q-fin.PR]