The Volcker metric known as inventory aging… and thoughts of Whisky

Posted by on Aug 1, 2014 in Classification, Conferences, Dodd Frank, Modeling, Regulatory, Risk, TSAM, Volcker | 0 comments

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.

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Senate committee hearing on JPM loss – possible industry implications on derivatives infrastructure

Posted by on Mar 15, 2013 in Classification, Derivatives Infrastructure, Regulatory, Risk, Volcker | 0 comments

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

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It’s March 11th. Do you know where your collateral is?

Posted by on Mar 11, 2013 in Dodd Frank, Noteworthy, Regulatory, Whitepaper and Downloads | 0 comments

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.

First Prezi in our series is focused on Clearing and Collateral.

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.

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Making premium lemonade (exhibit A) – JP Morgan adopts single trading platform

Posted by on Jan 7, 2013 in Dodd Frank, Reference | 0 comments

In today’s FT, JP Morgan announces its derivatives trading re-engineering effort – 3 years in the making, and baking.

Is this what everyone else means when they say preparing for regulatory compliance?

Probably not.

But this is what competitive differentiation looks like for JPM, so far (apparently):

– 4 technology program pillars (and 24 workstreams) of a strategic re-engineering effort (sponsor: J. Dimon).

  • Core trading platforms rationalization – rationalize application footprint, share pipes and plumbing between what’s left, plug into the same critical platforms;
  • Derivatives clearing, operations and STP workflow upgrades
  • Back Office systems upgrades
  • Critical Platforms re-engineering – where a lot of the neater stuff’s been percolating. Athena (which sounds like the single platform the FT is referring to – the shared risk, valuation and trade management platform with its common object store, DAG, node ranked calculations, and event-driven recalc), at least one (Python based) derivatives DSL, a global model library (with FPGA optimizations on several models).

– Market making rationalization – one primary market maker for each asset class regardless of eventual risk owner.

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