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Fouque and Langsam, Cambridge University Press, 2013, Handbook on Systematic Risk, here.
The Handbook on Systemic Risk, written by experts in the field, provides researchers with an introduction to the multifaceted aspects of systemic risks facing the global financial markets. The Handbook explores the multidisciplinary approaches to analyzing this risk, the data requirements for further research, and the recommendations being made to avert financial crisis. The Handbook is designed to encourage new researchers to investigate a topic with immense societal implications as well as to provide, for those already actively involved within their own academic discipline, an introduction to the research being undertaken in other disciplines. Each chapter in the Handbook will provide researchers with a superior introduction to the field and with references to more advanced research articles. It is the hope of the editors that this Handbook will stimulate greater interdisciplinary academic research on the critically important topic of systemic risk in the global financial markets.
Duffie and Pan, An Overview of Value at Risk, 1997, here.
Redline Pre-Trade Risk Checks, here.
The Securities and Exchange Commission Rule 15c3-5 – Risk Management Controls for Brokers or Dealers with Market Access mandates that broker-dealers implement risk management controls and supervisory procedures to ensure compliance with all regulatory requirements in connection with market access. While these measures will help to provide protection to the markets, the additional thresholds built into the execution process have the potential of creating unwanted latency in trading systems.
SEC, Risk Management Controls for Brokers or Dealers with Market Access, Final Rule, here.
SUMMARY: TheSecuritiesandExchangeCommission(“Commission”or“SEC”)isadopting new Rule 15c3-5 under the Securities Exchange Act of 1934 (“Exchange Act”). Rule 15c3-5 will require brokers or dealers with access to trading securities directly on an exchange or alternative trading system (“ATS”), including those providing sponsored or direct market access to customers or other persons, and broker-dealer operators of an ATS that provide access to trading securities directly on their ATS to a person other than a broker or dealer, to establish, document, and maintain a system of risk management controls and supervisory procedures that, among other things, are reasonably designed to (1) systematically limit the financial exposure of the broker or dealer that could arise as a result of market access, and (2) ensure compliance with all regulatory requirements that are applicable in connection with market access. The required financial risk management controls and supervisory procedures must be reasonably designed to prevent the entry of orders that exceed appropriate pre-set credit or capital thresholds, or that appear to be erroneous. The regulatory risk management controls and supervisory procedures must also be reasonably designed to prevent the entry of orders unless there has been compliance with all regulatory requirements that must be satisfied on a pre-order entry basis, prevent the entry of orders that the broker or dealer or customer is restricted from trading, restrict marketaccess technology and systems to authorized persons, and assure appropriate surveillance personnel receive immediate post-trade execution reports.
The financial and regulatory risk management controls and supervisory procedures required by Rule 15c3-5 must be under the direct and exclusive control of the broker or dealer with market access, with limited exceptions specified in the Rule that permit reasonable allocation of certain controls and procedures to another registered broker or dealer that, based on its position in the transaction and relationship with the ultimate customer, can more effectively implement them. In addition, a broker or dealer with market access will be required to establish, document, and maintain a system for regularly reviewing the effectiveness of the risk management controls and supervisory procedures and for promptly addressing any issues. Among other things, the broker or dealer will be required to review, no less frequently than annually, the business activity of the broker or dealer in connection with market access to assure the overall effectiveness of such risk management controls and supervisory procedures and document that review. The review will be required to be conducted in accordance with written procedures and will be required to be documented. In addition, the Chief Executive Officer (or equivalent officer) of the broker or dealer will be required, on an annual basis, to certify that the risk management controls and supervisory procedures comply with Rule 15c3-5, and that the regular review described above has been conducted.
FTEN, Per-Trade Risk: The Final Countdown, here.
Last November, the seC laid down the gauntlet to the sell side by making broker-dealers expressly responsible for their own and their clients’ pre-trade risk management systems and processes. the move had been widely anticipated, but the seC took a crucial further step. by securing a mid-January publication date in the Federal register, it set a deadline for compliance of 14 July, giving the industry just six months to get its pre-trade risk house in order
Bradley Keoun, Bloomberg, JPMorgan Silence on Risk Model Spurs Calls for Disclosure, here. Is it me or does Mr. Keoun have trouble taking a hint?
The skewed comparisons can leave investors guessing about whether the potential for loss is rising or falling, according to risk analysts. Adding to the muddle, some bankers including JPMorgan Chief Executive Officer Jamie Dimon have told investors not to rely too much on VaR, calling it just one part of their effort to manage risks at the biggest lenders.
Ok there it is, in Mr. Keoun’s reporter notebook. Unless Mr. Dimon is somehow trying to trick people, this should have cleared things up. I think Mr. Dimon should be even more straight forward. Something like:
“VaR is for reporting to regulatory bodies after-the-fact because the real models are too local market specific and too difficult to master in a short period of time.” and
“VaR cannot precisely track the market valuation fluctuations so it is not useful for running many hedged derivative books but we take VaR seriously for after-the-fact macro Regulatory Reporting” and
” No sane person runs front office P&L and Risk on an inventory of CDX and standard tranches with VaR model, ever, no exceptions”
but it still might not be clear enough.
SEC Chairman Mary Schapiro told a Congressional panel last month that her agency is scrutinizing the banks’ disclosures about the change in VaR models for its chief investment office, which invests the banks’ excess cash. The Federal Reserve and Office of the Comptroller of the Currency are examining why the change was made and whether it’s a sign of weakness in risk- management practices.
They’re asking because JPMorgan changed its calculation methods on Jan. 15 for the CIO as the unit was grappling with how to unwind stakes held by Bruno Iksil. The U.K.-based executive was dubbed “The London Whale” after his trades became so big that they distorted prices in an illiquid market, making it hard to get out of the positions.
So someone wants to know why the VaR got changed. Oh I don’t know, you think it could be because the old VaR didn’t match the market movement against JPM (that the London Whale positions induced without any historical precident)?
Not once in the three years before JPMorgan’s trading loss did the bank disclose a change in any risk models for specific trading desks, according to data compiled by Bloomberg.
JPMorgan isn’t alone in tweaking its risk models behind the scenes or employing discretion to calculate the figure. Goldman Sachs Group Inc. (GS) and Citigroup also make changes to their VaR models regularly, people with knowledge of the matter said.
When calculating VaR for an asset without a complete pricing history, traders and risk managers have to choose a “proxy” — an asset whose price moves are believed to be similar to those of the asset being modeled.
“The choice of proxy is a subjective judgment,” said Allen, now a consultant based in New York.
This is a total word to your mother moment.
Maybe Mr. Keoun is an economist?
Taleb, Prolog to his book due out Q4, here. Black Swan was a pretty good read. I expect no less from Antifragile.
Wired, Vint Cerf: We Knew What We Were Unleashing on the World, here.
Vint Cerf invented the protocol that rules them all: TCP/IP. Most people have never heard of it. But it describes the fundamental architecture of the internet, and it made possible Wi-Fi, Ethernet, LANs, the World Wide Web, e-mail, FTP, 3G/4G — as well as all of the inventions built upon those inventions.
Cerf did that in 1973. For most of you that’s probably 20 years before you even knew what the internet was. That’s why he’s known as the father of the internet and earned himself a Presidential Medal of Freedom. Cerf didn’t stop there — he went on to co-found the Internet Society (ISOC) and served as president of ICANN, the organization which operates the domain naming system.
PC Mag, Intel’s Ivy Bridge: 10 Things You Need to Know, here.
More overclockable. Supporting version 1.3 of Intel’s Extreme Memory Profile, real-time core ratio changes, and improved overrides for processing, graphics, and memory functions, Ivy Bridge offers options for tweaking your system’s performance over and above what you can get from either Sandy Bridge or Sandy Bridge Extreme CPUs. In our testing, we had no trouble pushing the Core i7-3770K from 3.5GHz to 4.6GHz using a stock fan and heat sink; with time, determination, and more aggressive cooling, you should have no trouble doing even better. You will, however, need a motherboard with the Z75 Express or Z77 Express chipset.
Slashdot, C/C++ Back On Top of the Programming Heap? here. Hammer Principle, Browse the Programming Language Rankings, here. How about the principle “This is a mainstream language” 14 out of 15 respondents picked Haskell over Standard ML.
Anna Gelpern puts it well: “for the small but committed contingent of pari passu pointy heads, this is WorldCupOlympicMarchMadnessSuperBowl.” I’m one of the contingent, and I’ve been actively enjoying myself reading various appeals and amici briefs in the case of Elliott Associates vs Argentina. (Technically, it’s not Elliott Associates but rather NML, an Elliott sub-fund, but make no mistake: this is very much a fight between Argentina and the most famous vulture fund in the world.)
Elliott, which is run by the billionaire Republican activist Paul Singer, has suffered a rare and public loss with respect to its Argentina strategy. It bought up Argentine debt around the time the country defaulted, and then refused to enter into the country’s bond exchange, taking its chances in U.S. court instead. That, in hindsight, was a mistake: Argentina’s new bonds, turbo-charged with GDP warrants, performed extremely well. While its defaulted debt has gone absolutely nowhere.
When Elliott started litigating its defaulted debt a decade ago, it quite explicitly told the judge in the U.S. Southern District, Thomas Griesa, that it wouldn’t wheel out the most notorious and legally dubious weapon in its arsenal: the pari passu argument it used to devastating effect against Peru in 2000. In 2003, indeed, Argentina’s lawyers asked the court for a declaration that the argument was legally bonkers; the only reason that Griesa didn’t provide that declaration was that Elliott Associates — in line with all the other holdout creditors — said that it had no intention of making the argument, “at any time in the near or distant future”.
In fact, Elliott was just playing the waiting game — waiting, that is, for 91% of the other creditors to go away, persuaded by Argentina to accept its exchange offer. And then, after a decent amount of time — five years — it suddenly decided that it was going to attempt to use its rather odd pari passu argument after all.
Waiting that long held dangers, since it smells of what lawyers call “laches” — unreasonable delay in making a claim. But it was also quite smart, since at that point Elliott had been fighting Argentina in front of Judge Griesa for a decade, and Griesa was officially Fed Up with the whole thing and just wanted to make it go away.
Griesa’s orders (here here here) are notable for their lack of legal reasoning: Griesa is throwing his hands in the air, here, and basically punting the whole issue up to the appeals court. Each one is very short, certainly in comparison to the long, compelling, and clearly-argued amici briefs, let alone Argentina’s masterful, 84-page response. After reading that, and the briefs from the Justice Department and The Clearing House , it’s basically impossible to see how Griesa’s order can possibly be upheld on appeal.
Naked Capitalism, The Hidden Bank Time Bomb: Interest Rate Risk, here.
At the Atlantic Economy Summit in Washington last month, Sheila Bair fielded a question about the just-released results of the latest bank stress tests. The former FDIC chief took pains to point out that they were an improvement over earlier iterations by virtue of keying off a truly dire economic scenario, but then ticked off a number of ways in which they fell short. One was in that they focused solely on credit risk, when historically, adverse interest rate moves have proven very effective in decimating the banking sector. Witness phase one of the savings and loan crisis, in which hasty deregulation and gimmickry in the early 1980s set up the crisis later in the decade, or the derivatives wipeout of 1994, in which an unexpected 25 basis point Fed funds increase created bigger losses than the 1987 crash, or the losses on US bond portfolios in 1997 and 1998, which among other things nearly wiped out Lehman.
The perils of interest rate risk have largely receded from memory since the US has been in a long-term disinflationary trend since 1983. But with rates at zero, we have nowhere to go but up from here.
Chris Whalen, in his latest newsletter, argues that this risk is even nastier than it might appear. One way of mitigating interest rate risk is by holding shorter-dated instruments. The reason is that the more back-weighted your payments are, the more exposure you have to changes in interest rates.
Investors measure this sensitivity via duration. There are somewhat different ways to measure it. One is the weighted average of payments. That gives you a result than under most circumstances is very close to the price sensitivity of a bond to interest rate changes. At “normal” interest rates, a current coupon bond of just under 10 years will have a 10% sensitivity to interest rate changes.
But, as Whalen points out, this all goes haywire when interest rates are super low. So much of the value is in the repayment of principal and so little in the intervening interest payments that it pushes duration out and increases interest rate risk disproportionately. That effect may be further compounded by the fact that banks are desperate for yield and with the yield curve flatish, they are likely to be extending the maturity of their assets.’And of course, anyone holding mortgages will see them extend, since refis will halt and home sales will probably be depressed, since higher interest rates mean more expensive mortgages, which all other things being equal, means lower home prices.
Bloomberg, JPMorgan Trader Iksil Fuels Prop-Trading Debate With Bets, here. London Whale needs some P from Series 9 Investment Grade CDX. Can Bloomberg and some prominent officials help fix the situation?
Zerohedge, From Bruno Iksil’s Personal Profile: Enjoys “Walking Over Water” And Being “Humble”, here. Oh, so the London Whale is shorting tranches of series 9 CDX in $100bn quantities.That starts to make sense given all the hysteria. So they make the purchases at the corporate-level to hedge SCDO exposure that is not actively traded by the desk. Maybe Bruno is the one who needs the the Maxeler FPGA Supercomputer Credit batch at JPM (see Credit Derivatives, Flynn’s Architectural Case for Maxeler in 2012?, and Street FP Due Diligence 3: Epic Yet?) to run in 238 seconds. How do you tag that? London Whale needs Mammoth Supercomputer to Stay Afloat? Too much, right? I still suspect that the entire JPM credit batch (as described) completes in less than a minute on a low-end Mac Pro even with the Gaussian Copula positions. Sort of more like “Bruno uses iPhone to Track Purchases.” (see Business Insider, Financial Post, Wall Street Journal blog, Sober Look, New York Times Dealbook, Financial Times Alphaville, blogrunner)
Zerohedge, 31 Dec 2011 Notional Amt. of Derivative Contracts Top 25 Comm. Banks, here. Didn’t MS carry derivative inventory in the past?
One Div Zero: tentative add to our heroes list – James Iry “If cars were built like software then…well, I don’t know squat about building cars so who knows. It might be kinda cool. But probably not.” A Brief and Incomplete and Mostly Wrong History of Programming Languages
Zerohedge on the CDS market trade volume distribution and a proposal for CDS indicies to be exchange traded, here.
Kamakura Corporation, Risk management tools and Jarrow is involved somehow look at the research and blogs, here.
Cloud Computing get reviewed by US DOE, Argonne, and Lawrence Berkeley and gets a grade of meh, here from Clusterstock.
Salmon on Udacity, here. Stanford AI professor starts up online University UDACITY. Agreed this looks like it could grow. An AI course at Stanford gets 100K worldwide enrollment? wow. I would like to hear why the notion that Stanford, Harvard, Ptown, or Oxford should brand this is an obviously bad idea.
HPCWire Russell Fish @ Venray Technologies has an embedded Microprocessor in DRAM play, here. Problem is apart from Mortgages I doubt much Street P&L/Risk analytics is intrinsically memory bandwidth starved as opposed to processing starved. Super good at creating pipeline bubbles though.
So, a major broker-dealer gets a 2011 industry award for running their overnight Risk and P&L credit derivative batch though a 1000 node CPU grid and some FPGAs in 238 seconds (in 2008 the same computation and same broker-dealer but presumably different CDS inventory took 8 hours, a great success). Then some blog posting claims that this same credit derivative batch could be run with some optimized C++ code on a $2500 Mac Pro in under 2 seconds IEEE 754 double precision tied out to the precision of the inputs. What’s going on? Does the credit derivative batch require a $1,000,000 CPU grid, FPGAs, and 238 seconds or one $2,500 MacPro, some optimized code, and 2 seconds?
It’s the MacPro + 2 seconds very likely, let’s think how this could be wrong:
A. The disclosed data is materially wrong or we have misinterpreted it egregiously. The unusual event in all this is the public disclosure of the broker-dealer’s runtime experience and the code they were running. It is exceedingly rare to see such a public disclosure. That said, the 8 hour production credit derivative batch at a broker-dealer in 2008 is not the least-bit surprising. The disclosure itself tells you the production code was once bloated enough to be optimized from 8 hours to 4 minutes. You think they nailed the code optimization on an absolute basis when the 4 minutes result was enough to get a 2011 industry award, really? The part about the production infrastructure being a supercomputer with thousands of grid CPUs and FPGAs, while consistent with other production processes we have seen and heard of running on the Street, is the part you really have to hope is not true.
B. The several hundred thousand position credit derivative batch could be Synthetic CDO tranches and standard tranches and require slightly more complicated computation than the batch of default swaps assumed in the previous analysis. But all the correlation traders (folks that trade CDOs and tranches) we know in 2011 were back to trading vanilla credit derivatives and bonds. The credit derivative batch with active risk flowing through in 2011 is the default swap batch (you can include index protection like CDX and ITRX in this batch as well). Who is going to spend three years improving the overnight process on a correlation credit derivative book that is managed part time by a junior trader with instructions to take on zero risk? No one.
C. The ISDA code just analyzed is not likely to be the same as the 2011 award winning production credit derivative batch code. In fact, we know portions of the production credit derivative batch were translated into FPGA circuitry, so the code is real different, right? Well over the last decade of CDS trading most of the broker-dealers evolved to the same quantitative methodology for valuing default swaps. Standards for converting upfront fees to spreads (ISDA) and unwind fees (Bloomberg’s CDSW screen) have influenced broker-dealer CDS valuation methodology. We do not personally know exactly what quantitative analytics each one of the of the broker-dealers runs in 2011, but Jarrow-Turnbull default arrival and Brent’s method for credit curve cooking covers a non-trivial subset of the broker-dealers. The ISDA code is not likely to be vastly different from the production code the other broker-dealers use in terms of quantitative method. Of course, in any shop there could be some undisclosed quantitative tweaks included in production and the MacPro + 2 seconds analysis case would be exposed in that event.
D. The computational performance analysis just presented could be flawed. We have only thought about this since seeing the Computerworld UK article and spent a couple weekends working out the estimate details. We could have made a mistake or missed something. But even if we are off by a factor of 100 in our estimates (we are not) its still $2500 + MacPro + 200 seconds versus $1,000,000 + 1000 CPU+ FPGAs+238 seconds.
Dominic O’Kane has/had his own web based calculator based on his 2008 book Modeling Single-name and Multi-name Credit Derivatives which is in turn based on a very good Lehman research report O’Kane published with Stuart Turnbull in 2003, Valuation of Credit Default Swaps.
Hull and White 2003 on Valuation of a CDO and an nth to Default CDS Without Monte Carlo Simulation. If there is a broker dealer running a PDE solver on their Credit Derivative inventory for daily P&L, find out who the head of quantitative research is there and bow before that guy because he has achieved Steve Jobs-level marketing skills.
Matlab CDS pricer, here.
BionicTurtle has a YouTube video of how to run a CDS valuation on a spreadsheet, here. Appears to be the tip of iceberg of You Tube videos explaining Credit Derivatives
Many companies are trying novel chip technologies to accelerate specialized kinds of computing jobs. But there’s signs that something a bit more radical, backed by technology vendors such as Maxeler Technologies, is also winning converts.
The London-based company was formed to commercialize a technology known by the phrase dataflow, a concept discussed since the 1970s that represents a sharp break from the fundamental design used in most computers and microprocessor chips inside them.
Clark at Wall Street Journal, here. Odd lead in – bringing 1970s concepts to you today – does it run APL? Alright I’m gonna bite, lets see what the FPGA technology bet is with Maxeler. Wonder what the dataflow folks Arvind , Culler, and Iannucci are doing these days? Oh, Arvind’s doing Mobile phone ecosystems for Nokia; Culler’s doing Electricity generation in Berkeley; Iannucci’s doing some digital radio stuff at RAI. Arvind’s 2005 ISCA talk slides from his home page seems like a good place to start. Lets figure out why dataflow is going to be a good technology bet in 2012 for pricing several 100K default swaps off a bunch of cooked credit curves.