About this paper
Profit & Loss Attribution (PLA) in a bank provides a critical product control function of decomposing and analyzing actual booked Profit & Loss (P&L) and its variance, especially in the context of testing three hypotheses posed by the bank’s risk models:
I. Change in the mark-to-market value of its positions are materially determined by changes to a specified set of variables and parameters (i.e. risk factors) and the expected change is quantified by the sensitivities obtained to these risk factors from its models;
II. There is a specified % probability that the value of its positions will lose more than its VAR number over any given interval equal to the VAR holding period;
III. The cost of insuring its aggregate positions against the risk of counterparty Z defaulting is not expected to exceed the cumulative sum of the CVA fees charged to its trading desks for originating exposure to counterparty Z.
This paper examines the practice of PLA production, analysis & reporting within banks.
- In the first 3 sections, we describe and review this practice in the context of PLA used as a metric to calibrate the risk hypotheses posed by risk models (see above) – highlighting the issues that should be of concern to senior management and regulators alike. We also primarily focus on the attribution of derivatives P&L.
- And then in the last section and in the appendix, we outline a checklist of questions on policy, governance and metrics that can be used to benchmark and govern the bank’s capacity to produce, analyze, monitor and report PLA.
- Along the way, we develop and enumerate a set of useful axioms that provide a breadcrumb trail of good practice in PLA production and use. These axioms are tagged to indicate where they present opportunities or/and risks.
To obtain a courtesy download of the whitepaper please submit a request below.
A download link to the paper will be provided.