The Volcker Rule mandates that banking entities cease proprietary trading, subject to certain exceptions for “permitted activities” including market making and risk-mitigating hedging.
The 17 quantitative metrics are grouped into 5 metrics groups (as listed to the left)
Each metrics group variously seeks to establish that a bank’s risk taking appetite, revenue profile, trading inventory and origination are all consistent with that of a market maker providing liquidity and hedging any residual risks incurred in the provision of this service.
Risk Management: the 4 metrics in this group try to establish that the bank’s trading units retain risk that is not in excess of the size and type required to provide intermediation/market making services to customers.
Sources of Revenue: the 5 metrics in this group try to establish that the bank’s trading units’ revenues are earned primarily from customer revenues (fees, commissions and bid-offer spreads) and not from price movements of retained principal positions.
Revenue-to-Risk: the 4 metrics in this group try to establish that the revenue earned per unit of risk taken by a bank’s trading units exhibits a consistent mean and low volatility.
Customer Flow: the 3 metrics in this group try to establish that a bank’s trading units’ trade activity is primarily originated by customers of the bank’s market making desks.
Fees & Commissions: the single metric in this group tries to establish that a bank routinely earns fees, commissions or/and spreads from its trading activity as opposed to paying these, and so being primarily a provider of liquidity not a consumer of it.
Implementing a Volcker metrics framework will require inputs from Trade Capture, Curve Marking, Risk and VaR and pulls together two themes we have previously blogged on: P&L Attribution, and Risk Factor Classification.
The Risk Management group of metrics will require outputs from VaR and Sensitivities generation and their respective limits (and for Sensitivities generation – a substantiation of the risk factors used may require visibility into the Risk Factor classification process or framework in place). This metrics group also relies on P&L Attribution to match P&L to VaR in the calculation of VaR Exceedance (a process very similar to the P&L slicing and normalization required for VaR Backtesting).
Source of Revenue metrics (and by extension Revenue-to-Risk and Fees and Commissions metrics) will depend very heavily on P&L Attribution. Spread P&L as a metric also introduces a new attribution measure that requires the marking of bid/offer spreads and the attribution of P&L due to this.
Customer Flow metrics will depend on the capture of trade metadata that helps enrich the data view of trading inventory held.
We have put together a note on implementing a Volcker metrics framework and its impact on some the areas outlined above. While the final Volcker rule is not expected to be published before year end (assuming of course that November does not bring existential interruptions to its implementation) , the potential scope of its impact is significant and the resulting book of work is likely to be substantial (and the current compliance deadline remains July 2014); and so we recommend that firms start to scope the size of the work that this would mean to their infrastructure and operational capacity.