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Zerohedge, This Is What Happens When A Mega Bank Is Caught Red-Handed, here. Durden is really good at this.
Which brings up three important questions:
- Now that the “trading desk” that was responsible for up to 25% of JPM’s net income has been effectively closed, how will Jamie Dimon succeed in creating recurring profits in line with historical average and future expectations?
- What will happen to the other “VaRs” once they too are exposed, either after the loss is uncovered, or when regulators actually dare to do their job for once and truly dig through the banks’ books?
- Which other bank has a huge and heretofore undisclosed multi-billion derivative “easter egg” on its books?
For Question 3 we may have a suggestion.
DealBreaker, Matt Levine, You Say “Voldemort” Like That’s A Bad Thing, here. Levine plays who’s the narc:
What is going on here? Like, for one thing: who narc’ed on him? And why? The most sensible account as always comes from Lisa Pollack; her take is basically that (1) a bunch of hedge funds are betting that the skew between spreads on the individual names in the CDX.IG.NA.9 (which names they are long) and spreads on the actual index (which they are short) will converge, (2) Iksil recently got massively long the index, blowing out that skew and losing them money on a mark-to-market basis, and (3) the hedge funds are mad and sad and going to the press to embarrass and/or regulate JPMorgan out of this market? This seems fine except that except it’s hard to see the hedge funds making money on an actual skew trade; Markit shows a -12bps skew and my sense is that after bid/ask you just can’t make a living on 12bps of convergence.
There’s a part of me that wants the narc to be JPMorgan itself, calling attention to its brilliant risk management, spooky nicknames, and ability to move markets with one flick of a London-based Frenchman. Also perhaps to provide a platform for its anti-regulatory case.
Levine seems to get a handle on the moment and the Lisa Pollack reference seems valuable long term.
But realistically, the press has been bad, with Bloomberg going so far as to say “Neither Iksil nor JPMorgan have been accused of wrongdoing,” which, ouch! So maybe it’s other banks, jealous of how good JPMorgan’s hedging is, calling attention to the Very Important Issue of how un-Volckery and maybe-market-manipulative it is?
If so I feel like they’re … doing kind of a weak job? I will be surprised if anyone gets worked up about the market manipulation angle given that (1) the losers are eeeeevil hedge funds and (2) it’s having a fairly small effect on the market for one off-the-run CDX index. And for the Volcker Rule angle … I am serenely untroubled by JPMorgan risking $100bn on US investment grade credit, and everyone else is similarly untroubled given that there’s no real evidence that this trade (arguably a hedge, arguably long-term, etc.) would actually violate the Volcker Rule. Regardless of how you get there, though, if your model of bank regulation prohibits JPMorgan from risking $100bn on diversifid US investment grade credit, your model is wrong.
If I were writing the anti-JPMorgan PR campaign here I might come at it differently. If you take these reports at face value – and you can’t entirely; I don’t believe that JPM is long all this credit risk unhedged and neither does anyone who talked to the Journal or Bloomberg – then JPMorgan has invested $100bn of its huuuuge but finite balance sheet in US corporate credit via this trade. Unlike its loans, this extension of credit is unfunded, but still – JPMorgan is not exactly short of cash, as they’d be the first to tell you, and they can always get more if they need it. So it’s reasonable to think that JPMorgan’s ability to extend credit is finite and that is due to capital, not funding. But that $100bn of credit risk has been extended not to the 121 actual businesses in the CDX.IG.NA.9 index, many of whom probably also have too much cash but some of whom could presumably use the money to like Build A Factory or Hire Some Workers or Buy An Instagram or whatever. Instead it’s being extended to … well, indirectly, to eeeeevil hedge funds who are short the credits and churlish enough to complain about it to the press. If you’re a regulator or politician whose complaint about banks is that they aren’t doing enough lending to support the real economy, news that 5% of JPMorgan’s balance sheet is in the form of synthetic corporate lending that doesn’t actually go to those corporates might be enough to get you mad.
Trading environment seems a little more toxic than usual. Levine gives it all a gritty early 70s Popeye Doyle, French Connection feel.
Ft.com/alphaville, Lisa Pollack, Hedge funds and the Whale, credit index edition, here. Lisa Pollack is publishing this reasonably early, 6 Apr. Look at the charts in “A graphical investigation” toward the end of the piece to get some sense of how the IG9 market has moved and on what volumes.
Zerohedge, Behind ‘The Iksil Trade’ – IG9 Tranches Explained, here.
So what was once a 3%-7% tranche is now roughly a 2.4% – 6.4% tranche.
So if you sell protection on this tranche, you need further cumulative defaults of 2.4% before you make any payments, and then you make payments until 6.4% of the notional has had losses. If there is a 0% recovery on each default, you could have 3 defaults before having to make any payment (each name is 1/125 or 0.8%). If recovery was 40% then you have no payments until the 6th default.
The big question is, what do you get paid on this tranche? 20 points up-front and 500 bps running. So if you sell $1 billion of this tranche, you receive $200 million up front and $50 million per annum. In a relatively tight credit spread environment, this is a lot of money. If you use the upfront payment to “defease” losses, the $1 billion of exposure has a maximum loss of $800 million, and would require 4 defaults at 0% recovery before actually having a loss, and more realistically, would only take a loss on the 8th default with a 40% recovery. Suddenly the trade seems less scary, as least to me.
But how do people come up with a number of a “100 billion”? That comes down to “deltas”. The delta on this tranche is about 7.5 times. So if someone wanted to take this risk, without delta (just sell the tranche and not have a “correlation” bet), every $1 billion would create $7.5 billion of index trading.
You could sell this “no delta” and the buyer would pay you for the tranche, but then have to go and sell 7.5 times that amount of index out to the market so they could manage their “correlation” risk – a giant model based book. Some dealers are very good at tranches, but are weak at trading the underlying index. In those cases, you might sell the tranche “with delta” and sell the index position yourself because you can get better execution that way. So you sell the tranche and buy 7.5 times the index from the correlation desk (the with delta trade). Then you sell the straight index into the market. It would explain why you are seen as a seller of index when the real trade is actually being a seller of the tranche.
Morgan Stanley, 2012 Handbook of Credit Derivatives and Structured Credit Strategies, here. 250+ page doc on credit derivatives via Levine at DealBreaker. I’ll take a look at it today.
Ft.com/alphaville, Lisa Pollack, The mystery of Morgan Stanley’s footnote unravels Part 1, here. Part 2, here. MS reduced exposure to Italy by $3.4bn while benefiting from a positive hit to net revenue of $600m. How did that work? Alternative Termination Event clauses – just like they teach in the CVA courses.
Advanced Trading, Deutsche Bank Shaves Trade Latency Down to 1.25 Microseconds, 15 mar 2011, here. They report:
“This is a bit of a revolution, since it’s breaking a barrier from previously doing a couple of hundreds of microseconds and then 80 microseconds which is the normal software-based Ultra products’ latency,” said Roth. “That is the market standard and now we’re getting into the low-single digit microseconds. That has never been done before,” he said.
Deutsche Bank deployed the patent-pending card in its lab in the first quarter. As of Monday, the first client was ready to begin testing it. “The trade comes into the card, the card does the protocol translation and risk checks” explained Roth. “We’re bypassing the PC and doing everything in hardware,” explained Roth, who runs the global product development team for equity trading.
The Ultra solution will appeal to the bank’s sponsored access clients who are facing new market access regulations from the Securities and Exchange Commission (SEC) to ban naked access by requiring pre-trade risk checks. Right now, the product is live in Nasdaq’s data center in Cartaret, New Jersey, and it will soon rollout to Direct Edge, Bats and then NYSE Arca. When it gets to Europe, the London Stock Exchange, NYSE Euronext and Xetra will be the main ones where latency really matters, said Roth.
Though other Wall Street firms are working with hardware-based solutions, and in some cases, they are working with vendors in the space, Roth believes that Deutsche Bank has the competitive edge. “Our solution is so far the lowest latency we are aware of that works close to 1 microsecond because we work with standard hardware components,” said Roth.
“If you look at the time horizon, we think we have an edge,” says Roth. “Our vision is that hardware will proliferate in this space over the next 15 to 24 months,” said Roth. “This is going to be the standard in low latency trading and more speed is going to be adopted in algorithms,” he predicted.
However, latency has become such a marketing buzzword in the electronic trading industry, that the concept can vary based on how it’s measured. Deutsche Bank measures the latency from wire-to-wire, when the message hits the card and when the message leaves the card,” said Roth, adding, “There is no ambiguity.” In this type of work, the bank uses a high resolution, oscilloscope that connects to the chip.
But 1.25 is just the start, he said, adding, “Getting the latency below one, is actually a tuning exercise.” Roth said he’s “confident” that the bank can get the latency below one microsecond. “This is about engineering. You can do these things if you are really focused and have the right engineering skills available,” he said. “It’s also about applying new techniques to the financial markets,” he continued. While a lot of proprietary trading firms and hedge funds are excited about this, Deutsche Bank is also one of the first firms to use low latency access in algorithms for the buy side, he said.
1) The SEC’s 15c3-5 Market Access Rule and CFTC’s advisory recommendations for DMA will rekindle the latency wars.
Just around the corner looms the SEC’s Market Access Rule to ban naked access. No longer will participating firms have unfettered direct market access while broker’s (virtually) look the other way as orders flow into the market with little or no checks or balances. I’m sure it was a profitable enterprise for the broker community to allow this direct channel for those willing to pay a little extra.
Brokers compete on the range of services they offer. They attract client’s order flow by offering better fill rates, better prices, increased liquidity, etc. The SEC’s rule 15c3-5 which mandates pre-trade risk checks does not really inhibit the level of service brokers can provide, but it does ensure everyone pay a latency tax for checking credit limits, and order constraints (quantity and price) brokers must enforce.
As a result, a groundswell is occurring. Pre-trade risk is fast becoming the next latency battleground. While some are scrambling, others such as Morgan Stanley are announcing achievements of microsecond latency. I am sure others will follow with revamped pre-trade risk modules as they leverage multi-core hardware to achieve parallelism in their architecture. A renewed emphasis onFPGA, hardware acceleration has also surfaced. FPGA technology has been readily available for a number of years, it’s success has primarily been in appliance oriented technology for ticker plants and messaging such as Exegy and Solace where it’s an embedded component. An Aite report on Capital Markets Technology spending puts FPGA low on the list of IT spend for infrastructure investments. I think this is primarily due to the fear, uncertainty and doubt surrounding the direct use of non-commodity hardware. From an IT manager’s viewpoint, a series of difficult questions arises regarding FPGA… “complex, non-standard development, handling long-term maintenance, support, diagnosing failures” and lack of experienced talent to hire. Challenging questions and likely the reason for its lackluster success.
Low-Latency.com, FPGA Momentum Accelerates!, 9 Aug 2011, here. They report:
The answer is: quite a lot, judging by various news releases coming my way of late. Here are some highlights:
- Deutsche Bank’s Autobahn equities electronic trading business recently expanded its μltra FPGA products to the US, to provide pre-trade compliance and risk checks in its co-located trading apps at NYSE, NYSE Arca, Nasdaq, Direct Edge and Bats. The claimed performance of the risk checks are 1.35 microseconds for OUCH messages and 1.75 microseconds for FIX messages.
- Nomura extended its NXT execution platform to Direct Edge’s co-lo centre at Equinix in Secaucus, NJ. And it’s claiming latencies of under 1.8 microseconds for fixed-length exchange protocols and 2.8 microseconds for FIX.
- Fixnetix introduced its iX-eCute trading gateway, offering latencies as low as 740 nanoseconds wire-to-wire, with 20+ pre-trade risk checks in less than 100 nanoseconds.
- Burstream rolled out its managed market data service at Nasdaq’s co-lo and Telx’s proximity centre in Chicago, leveraging data feed handling and order book generation technology from NovaSparks.
- TS Associates updated its Application Tap precision time card to make more use of FPGAs for transferring data to host memory, reducing its performance overhead.
- Impulse Accelerated Technologies introduced an FPGA development kit for 10gE ITCH/OUCH protocol handling, allowing CPU/kernel bypass to application memory space.
- Maxeler introduced MaxNode10G, a platform designed for wire-speed processing of multiple 10 gigabit network data streams.
Wallstreetandtech.com, Capital Markets Outlook 2012, here. They report:
Bank of America Merrill Lynch recently announced BofAML Express, an ultralow-latency market access and risk control platform for U.S. equities that provides embedded risk controls with sub-10 microseconds of wire-to-wire latency. Morgan Stanley is using software to shave latency from its compliant direct-market-access platform, Speedway 3.0, which is live with at least five exchanges, including NYSE, ARCA, Nasdaq, BATS and the two Direct Edge exchange platforms.
And Deutsche Bank is employing field-programmable gate array (FPGA)-based devices to lower latency for its risk checks. The platform, known as ultra FPGA, runs from Deutsche Bank’s cabinets at exchange data centers. Latency-monitoring service Correlix RaceTeam recently measured ultra FPGA’s pre-trade risk management gateway latency at 1.35 microseconds for messages sent to Nasdaq and at 1.75 microseconds for FIX messages.
Nomura, which went live in July 2010 with its ultralow-latency market access product, NXT Direct, also has turned to FPGA technology for its pre-trade compliance and risk checks. The bank says the platform offers risk-filtered, wire-to-wire direct connectivity in less than 1.8 microseconds for fixed-length exchange protocols and less than 2.8 microseconds for FIX protocols.
Industry Leaders: Deutsche Bank, Morgan Stanley, Bank of America Merrill Lynch and Lime Brokerage have adopted aggressive strategies to provide low-latency pre-trade risk controls and market access.
Technology Providers: High-performance cloud infrastructure providers include BT Radianz, Thesys Technologies, SunGard Capital Markets, NYSE Technologies, Equinix, EMC, Options IT and VMware. FPGA providers include ACTIVFinancial, Impulse Accelerated Technologies, Altera, Xilinx and Novasparks.