Inventory Aging is a rather innocuous looking member of the band of (now) seven metrics that, under the Volcker rule, banking entities with significant trading assets and liabilities are required to calculate daily and report monthly.
As written, the metric description seems straightforward enough:
Inventory Aging generally describes a schedule of the trading desk’s aggregate assets and liabilities and the amount of time that those assets and liabilities have been held. [It] should measure the age profile of the trading desk’s assets and liabilities and must include two schedules, an asset- aging schedule and a liability-aging schedule.
The graphic below broadly outlines the processes of asset/liability tagging, matching, sorting and netting of trades involved in generating an inventory aging schedule.
Today’s Senate Sub-committee hearing on last year’s credit derivatives trading loss at JP Morgan’s CIO office makes, in some segments, for riveting Q&A. The Senate sub-committee report released yesterday (as well as JPM’s own internal report) also makes for very compelling reading.
Both reports, and the sub-committee hearing, highlight some very specific control and reporting issues that are unlikely to be unique to JPM. The hearing also was (somewhat) critical of the Office of the Comptroller of the Currency’s (OCC) oversight. It would seem more likely than less that regulatory oversight of these issues will see increased focus and scrutiny across the industry.
Below, we list nine (9) possible implications. Using our schematic of key post-DFA process and data flows within OTC derivatives infrastructure, we also highlight the functional areas we believe may see such increased regulatory oversight scrutiny as a consequence.
Dealer firms will be well served to consider conducting current state analyses and (more…)
The OTC derivatives clearing mandate is upon us.
We will be running a series of Prezis called the “Making lemonade from lemons” series. This series, like our similarly titled whitepaper, will be looking beyond compliance to the Dodd-Frank Act (DFA), and examining the opportunities for competitive advantage that the challenges of the DFA present.
The Prezi is best viewed in full screen mode (for normal sighted folk),
and may also be found on the Prezis and Case Studies tab on our Whitepapers and Case Studies page.
The Tabb Group – in a 2011 presentation to the Commodity Futures Trading Commission’s (CFTC) Technical Advisory Committee – estimates that the largest US OTC derivatives dealers will spend a total of $1.8B on Dodd Frank (DFA) related technology costs; with the top eight spending over $1.5B.
An August 2012 update to a 2010 S&P analyst report puts its annualized estimate of DFA-related technology and related expenses for the top eight US banks at $2.0/$2.5B.
Throw in the profound and fundamental changes the regulations have wrought on OTC derivatives market structure, business models, terms of competition and future earnings expectations – and that’s a lot of chucked lemons.
This new Acuity Derivatives client report From Regulatory Compliance to Technological Advantage (making lemonade…) seeks to show that given the fundamental nature of changes to the OTC derivatives industry and also the high technology costs involved; that the deployment of this technology spend should not be viewed solely in the context of sunk compliance costs, but in the context of investing for competitive technology advantage.
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.
For Swap Dealers (SD) and Major Swap Participants (MSP), Friday October 12, 2012 was the effective date for which compliance to the swap public and regulatory reporting rules of the Dodd-Frank Act is required (for interest rate and credit swaps). Many financial institutions have implemented solutions to support these requirements. We published a note (downloadable here) providing an overview of the technical complexities that a reporting solution would need to resolve. Some of these complexities emerge from the following:
“The storm starts, when the drops start dropping
When the drops stop dropping then the storm starts stopping.”
― Dr. Seuss, Oh Say Can You Say?
“Pray don’t talk to me about the weather, Mr. Worthing. Whenever people talk to me about the weather, I always feel quite certain that they mean something else. And that makes me so nervous.”
– Oscar Wilde, The Importance of Being Earnest, Act 1
We will talk about weathermen and the predictions they make. And we will mean something entirely different. By weathermen, we will mean the models in a bank and the predictions they make or the hypotheses they form. And for the realism of Dr. Seuss’ drops dropping, we will substitute the realism of P&L.. More specifically, we will talk about P&L attribution (PLA) and the role it plays in helping us use the realism of P&L to test the hypotheses posed by our various risk models – which actually is its primary purpose in life.
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.
One thing is for certain, they will have less secrets.
Regulatory oversight will ensure that, even if the current zeal lasts only 3 years (assuming a political shift in attitude 1 year out and 2 years of starvation budgets to thin out current muscular oversight).
Secrets are not necessarily the conspiracies of derivatives cabals in the shadows but the knowledge that we practitioners have about improvements that can be made in the technology infrastructure and business process that supports this complex activity.
With regulators not only focused on supervision against the backdrop of current and anticipated rules on the books, but also pushing for best practice as they have observed it on their journeys poking around the infrastructure of market leaders in the industry and also now sharing notes with other regulators; there is a lot of sunshine coming the way of regulated entities.
However, that sunshine is an opportunity to rethink and rebuild some of this infrastructure, process and the strategy around how these things will evolve.