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Matt Levine, Bloomberg, Firm Sues to Stop CFTC From Calling It a Bunch of Cheaters. here.
Eventually, though, IDCH and Nasdaq convinced Jefferies to trade the contract, starting in 2010. This worked because Jefferies did not have a significant incumbent OTC swap business to protect, so it was open to exchange-based trading, and also because Jefferies was dumb and didn’t realize the contract was terrible. It missed the same thing that IDCH and Nasdaq missed, and just believed IDCH and Nasdaq when they said that the futures and swaps were equivalent.
Meanwhile, folks at DRW Investments also started trading the contract, because they were smart and saw that Jefferies were dumb. Basically, Jefferies took one side of a bunch of these contracts (receiving fixed), and DRW took the other on all of them (paying fixed)paid fixed on all of those contracts. The contracts were systematically mispriced: The fixed payer systematically should have paid more than it would under an equivalent swap, but since Jefferies believed that the futures and swaps were identical, it was willing to do the trades at the same rate as an equivalent swap. So DRW obliged (and, one assumes, entered into offsetting swaps, hedging out the interest rate risk and just pocketing the mispricing).
Rama Cont, Radu Paul Mondescu, and Yuhua Yu, SSRN, Central Clearing of Interest Rate Swaps: A Comparison of Offerings, here.
Abstract:Regulatory changes have motivated the development of a variety of solutions for the clearing of interest rate swaps. Margin payments associated with clearing lead to modifications in cash flows which result in differences in the valuation between cleared and non-cleared swaps. We propose a framework for computing these differences and show that they lead to two types of modifications in contract value: a convexity effect and a “Net Present Value” (NPV) effect, which can be significant for long-dated swaps. As a result, modifications in contract design are required in order for a centrally cleared interest rate swap to be economically equivalent to its uncleared counterpart. Among the currently available offerings for cleared interest rate swaps, three offerings are shown to be economically equivalent to their uncleared counterparts – the “Price Alignment Interest” method used by LCH. Clearnet and CME, as well as a new adjustment method used by the Eris Exchange – while a fourth method, used in the IDCG swap futures contract, is shown to lead to substantial deviations in valuation with respect to a non-cleared interest rate swap. Using a Hull-White model calibrated to the market data as of December 2010, we find the difference between the IDCG futures swap rate and the corresponding uncleared swap rate to be around 18 basis points for a 10 year contract and about 60 basis points for a 30 year contract. An interest rate environment with higher volatility will result in larger differences.
The Jefferies Group shows that fixed income isn’t necessarily for everyone. The revenue that the investment bank generated from trading bonds, currencies and commodities slumped 85 percent, to just $33 million, in the three months to September. That’s a far bigger drop than its larger rivals across Wall Street are expecting. As a relative newcomer, Jefferies appears to be struggling with volatility. The same may prove true for others that are downsizing their fixed-income businesses.
DRW Trading Group (DRW) is a principal trading organization. This means that all of our trading is for our own account and risk, and all of our methods, systems and applications are solely for our own use. Unlike hedge funds, brokerage firms and banks, DRW has no customers, clients, investors or third party funds. Our trading spans a wide range of asset classes, instruments, geographies and trading venues, with a focus on trading listed, centrally-cleared instruments.
Founded in 1992, our mission is to empower a team of exceptional individuals to identify and capture trading opportunities in the global markets by leveraging and integrating technology, risk management and quantitative research. With that spirit, DRW has embraced the integration of trading and technology by devoting extensive time, capital and resources to develop fast, precise and reliable infrastructure and applications. DRW has a flexible and entrepreneurial culture that cultivates creativity and practicality.
DRW is headquartered in Chicago and has offices in New York and London. DRW employs over 400 people worldwide from many different disciplines and backgrounds.
Trefis, NYSE, NASDAQ Aim For A Bigger Piece of the ETF Market, here.
Part of the NYSE Euronext (NYSE:NYX), NYSE Arca, a leading bourse for exchange traded products, is going to launch a program that aims to improve the liquidity of lightly traded exchange funds. The exchange received the necessary regulatory approval from the SEC this month, reports Bloomberg. 
With this move, the company seems to be trying to protect its dominance in the ETF segment from NASDAQ OMX (NASDAQ:NDAQ). According to the firm’s latest report, the exchange leads the exchange traded products (ETPs) market of which ETFs are the biggest chunk with a market share of 20.4% in May 2013. 
This dominance was challenged by NASDAQ a couple of months ago when it re-launched its PSX platform into a marketplace solely dedicated to exchange traded funds (ETFs) and launched its own liquidity program to gain market share in this segment. 
Matt Levine, DealBreaker, Nobody’s Happy With CFTC’s Plan To Only Micromanage Swaps Trading Strategy A Little, May 2013, here.
Are you as puzzled as I am by the mild brouhaha over the CFTC’s new swap execution facility rules? Basically the rules require that most swaps be traded on pseudo-exchange-y-type things called “swap execution facilities,” which are run either by an order-book system or a “request for quote” system. The RFQ system would require anyone wanting to trade to send an RFQ to at least 3 (2 for “an initial phase-in period”) potential counterparties. The original proposal was for that to be five counterparties. The revised proposal has caused a striking amount of rage, as various people have confused themselves into thinking that of course it’s obvious that every transaction should be an auction among five potential counterparties. Presumably few of those people orient their daily life that way. I don’t, anyway; I get lunch at Chipotle every day because it’s next door to Dealbreaker HQ.1
Got some time before I have to go tend the fantasy bball team mired in the middle of the dogpile. This a generalized two exchange trade crossing model. The generalization to more than two exchanges is straightforward.
Here, in the DynaPie Latency Model Figure (below), we have represented two colo installations. The first colo contains Exchange EX1, Gateway GW1, and Client Server CL1. The second colo similarly contains an exchange, gateway, and Client server (EX2, GW2, CL2). The Client Servers run the relevant exchange protocols to perform order execution via respective broker dealer gateways and solicit current market data from each exchange locally. To simplify the analysis we assume all latency is accounted for in the links, and for example, the portion of the gateway latency not accounted for in the link latency is negligible. The market data and client to gateway Link latency, represented by the variable L, is equal to a constant C. We assume the latency for any link within the colo is a constant. If you worry about this, you can assume C is the longest latency measured on average over a sufficiently large sampling period of all links within a single colo installation. The client, via the colo gateways, has two order entry options. CL1 can send a new order (wlg any other message) to EX1 via GW1 or send a new order to EX2 via GW1. CL2 has symmetric corresponding order options via GW2. The latency to submit a new order within the colo is C as previously discussed. The latency cost to submit a new order from GW1 to EX2 is ax+b, where a and b are constants and x is proportional to the minimal transmission line latency connecting GW1 and EX2. Similarly the latency between GW2 and EX1 is ax+b (we assume the same transmission lines, nics, and switch connecting the gateways and exchanges). Finally, the latency between the two client servers is represented as dy+e where d and e are constants and y is proportional to the minimal transmission line latency connecting CL1 and CL2.
The trading pits apparently favored by Mr. Cuban and the Themis Trading folks back in the day looked like this here. These were popular places, see the cash registers arranged around the pit, you can see them in the movie. Over the years the exchanges moved trading from crowded urban Wall Street pits to less crowded and more spacious Weehawken, Carteret, and Mahwah locations. The cash registers moved to these colo locations but the crowds of people haven’t materialized in these locations far away from Wall Street. Maybe Mr. Cuban would be more comfortable with more people involved working the cash registers, like in the olden days. Here at Mercer County Cash Registers, we aim to bring the cash registers back to the people who cannot make it to Weehawken, Carteret, or Mahwah. Here’s what we will do.
Look at these slides from NYSE Euronext, here. The maps on pages 17, 18 and 19 show the speed of light latencies from Mahwah, Carteret, and Weehawken. If your cash register is coloed in Weehawken, for example, your local order/ack time might be 100 mics but 1000 mics to Mahwah. 280 mics of the Mahwah roundtrip time is speed of light latency for the 26 mile distance. If my Weehawken cash register is looking to hit an order in Mahwah, I am 280 mics behind the guy coloed in Mahwah. Paramus looks like a good place to trade, sort of equidistant between the matching engines in Mahwah and Weehawken. In Paramus I am only 140 mics behind the cash register coloed in Mahwah. On the other hand, Montclair looks good for crossing Mahwah with Carteret. Then again maybe using the golden ratio is better for cash register location. Maybe the best location varies over time depending on the respective order volumes. Seems like there are times when having a cash register coloed with the local exchange is just fine but other times it would be handy if the cash register was in another location. You might be able to look at the trade logs to determine the optimal dynamic location for cash register placement throughout the day.
This is a short movie about an ice cream truck, here. Ice cream trucks have ice cream and cash registers inside them, and you drive them around selling ice cream. First of all kids like ice cream and we can get the ice cream to the children, so that’s a win right there. Now if we put our MCCR cash register in the freezer of the ice cream truck we can use overclocked new parts in building the cash register. Think of putting bunch of Haswell chips in the cash register and maybe one of those integrated radios from Justin Rattner as well. The freezer will keep the ice cream delicious and the overclocked Haswell chips from melting. Then we drive the ice cream truck to special locations known to be popular with the children and with known latencies to various matching engines. We can make children happy and trade optimally as well. The MCCR cash register needs to take ice cream coupons from the local Penny Saver newspaper as well as processing ETF orders and cancels. Hey, here is what we can do at Mercer Country Cash Register – kids you can send in orders for your ice cream on the internet. If your plans change you can cancel your orders. If we can get an ice cream truck to hit your order you get your ice cream. It’s all good, everyone’s happy, we get people next to the cash registers and those people get ice cream. MCCR is going to hire recently laid off math and science teachers exclusively to drive the ice cream trucks. Help the kids with their homework while they enjoy Soft Serve! Think globally and act locally with Mercer County Cash Register.
Kenneth Rogoff, Business Insider,These 3 Things Keep Pushing Interest Rates Lower And Lower, here. Long UST until Euro sorts itself out and a bunch of Germans and Japanese start to spend to check off their bucket list items.
How long can today’s record-low, major-currency interest rates persist? Ten-year interest rates in the United States, the United Kingdom, and Germany have all been hovering around the once unthinkable 1.5% mark. In Japan, the ten-year rate has drifted to below 0.8%. Global investors are apparently willing to accept these extraordinarily low rates, even though they do not appear to compensate for expected inflation. Indeed, the rate on inflation-adjusted US Treasury bills (so-called “TIPS”) is now negative up to 15 years.
Is this extraordinary situation stable? In the very near term, certainly; indeed, interest rates could still fall further. Over the longer term, however, this situation is definitely not stable.
Cardiff Garcia, alphaville, The decline of “real money” trading, here. HFT, EMM, an ETFs grow market volumes in past 10 years. Accounting for these structural growth factors real money trading at decade low levels. The CS Trading strategy links look interesting. The July 2012 CS Chartbook has interesting data, for example: global bid ask spreads, US Equity market share, and intraday vol for S&P500.
Something to keep in mind as the global risk asset rally — which appears driven by some combination of better-than-expected-but-not-that-awesome US macro data and… talking from European policymakers — continues.
Kurt Eichenwald, Vanity Fair, Microsoft’s Lost Decade, here. Big is bad.
Once upon a time, Microsoft dominated the tech industry; indeed, it was the wealthiest corporation in the world. But since 2000, as Apple, Google, and Facebook whizzed by, it has fallen flat in every arena it entered: e-books, music, search, social networking, etc., etc. Talking to former and current Microsoft executives, Kurt Eichenwald finds the fingers pointing at C.E.O. Steve Ballmer, Bill Gates’s successor, as the man who led them astray.
Reuters, Are Big Banks’ Glory Days Gone for Good? here. More big is bad.
NEW YORK – The summer of 2012 may be remembered as the time when regulation, scandals and a protracted slow-growth economy finally caught up with big American banks.
Gordon’s Tech, Mountain Lion – my experience, here. Lion is bad.
I’ve never installed an OS on its debut. I generally wait 5-6 months for the .4 release.
This time was different. I really don’t like Lion (Apple removed it rather quickly from the App Store, didn’t they?). I also have a MacBook Air that I really don’t rely on — so I could sacrifice it.
Notes so far …
ars technica, Google Fiber to arrive this fall; $70 for gigabit service, here. Lose the TV, just get me the gbps and I’ll buy an android pad or something.
Google fiber, here. Fast is good.
Business Insider, Google Fiber Is The Most Disruptive Thing The Company’s Done Since Gmail, here. Google might be good.
Matt Levine, DealBreaker, Tim Geithner Dealt With Libor Manipulation By Writing Strongly Worded Letters And Then Lending Billions Of Dollars At Libor-Based Rates, here. Move Levine up a notch on the “shines out like a shaft of gold when all about is dark” list. Other than Levine, Pollack, and maybe Salmon I cannot find many folks writing sensibly about Libor. Yves Smith and Robert Reich may have jumped the shark on Libor. Taibbi and Tyler Durden get a pass because they are Taibbi and Tyler Durden and you can kind of separate out the noise and still get a signal.
- Nobody really has ever been all that troubled by the fact that banks manipulated Libor to make themselves look like they could borrow in 2007-2008, while everyone is at least acting all shocked shocked that banks manipulated Libor to juice derivatives profits, but that contrast is awkward because in a certain light those are the same activity, so everyone has to look all horrified by stuff they were obviously cool with four years ago.
- Everybody knew that banks understated Libor in 2007-2008. Like, you could compare Libor to market borrowing rates and CDS and stuff, and people did, and noticed it was wrong. Also remember that Barclays, while they were manipulating Libor, were also emailing all their clients every day to remind them that Libor was being manipulated.
- The effect/harm/liability of Libor manipulation has to be determined in expectation and if everyone knew it was being manipulated then they were presumably charging a higher spread to Libor when dealing with banks.
Nicola Cetorelli, Federal Reserve Bank of New York, Introducing a Series on the Evolution of Banks and Financial Intermediation, here.
It used to be simple: Asked how to describe financial intermediation, you would just mention the word “bank.” Then things got complicated. As a result of innovation and legal and regulatory changes, financial intermediation has evolved in a way that invites us to question whether it revolves around banks anymore. The centerpiece of modern intermediation is the advent and growth of asset securitization: loans do not need to reside on the originator’s balance sheet until maturity any longer, but they can instead be packaged into securities and sold to investors. With securitization, banks’ balance sheets get replaced by a longer and more complex credit intermediation chain (Pozsar, Adrian, Ashcraft, and Boesky 2010). This evolution literally changes the picture of intermediation, as the figure below suggests. From a bank-centered system, we go to one where multiple entities interact with one another along the sequential steps of the chain, and concomitantly we hear increasingly of shadow banking, defined recently by the Financial Stability Board as a system of “credit intermediation involving entities and activities outside the regular banking system.”
Business Insider, The Most Powerful Nerds On Wall Street, here. Exhibit 1 of why World of MOOCs would just work. Think of a cross between Zynga Farmville, The Sims, and articles like the Most Powerful Nerds on Wall Street.
LIBOR EXPERT: The Fed Has Destroyed LIBOR, here.
That’s why, he argued, the old way of monetary financing—and with it, LIBOR fixings—has been destroyed in the wake of the financial crisis.
“It didn’t seize up [during the crisis]. It ceased to exist,” he told Business Insider.
Understanding what he means takes some understanding of how LIBOR works and what its fixing affects and is affected by.
Lisa Pollack, Alphaville, More damn lies and Libor statistics, here.
With Libor, it’s going to be mightily hard to prove the link between a specific bank’s actions and economic harm to a person or entity. Particularly since many entities will have lost on one side and received a benefit on the other, from any (successfully) manipulated rate.
For example, take a pension fund that invested in mortgage-backed securities, receiving a spread over 6-month USD Libor. Now say that same fund also had an interest rate swap whereby it paid a spread over 3-month USD Libor to a bank and received a fixed rate. Net-net on the benchmark alone: fund receives 6-month USD Libor and fund pays 3-month USD Libor.
If some group of banks managed to manipulate Libor higher or lower on the relevant reset dates, the pension fund may have a net benefit or net loss from said manipulation, depending on the relative size of the MBS to the interest rate swap and their relative fixed spreads above Libor.
To top it off, from which bank does the pension fund claim damages if indeed there was a net loss? A single bank cannot alone have anything other than a negligible effect on the ultimate benchmark, to which several other banks contribute, and outliers are removed before formation.
Yves Smith. naked capitalism, Libor Scandal Apologist Avinash Persaud Displays Inability to Do Math, here. Yves has no doubts, she smells blood.
Nothing like putting your foot in mouth in public and chewing.
Avinash Persaud, who is listed at VoxEU as “Chairman, Intelligence Capital Limited; Emeritus Professor, Gresham College; Senior Fellow, London Business School,” put up a “nothing to see here” post on the Libor scandal.
Advanced Trading, Buy-Side Traders Find Liquidity in Dark Pools, here.
Despite any heightened concern, however, in the current low-volume environment, buy-side traders appear to be using dark pools more than ever. With U.S. equity volumes averaging around 6.8 billion shares per day, down 14 percent from Q1 2011, traders at asset management firms and hedge funds are seeking liquidity in dark pools. “With volatility where it is, volume in dark pools picks up,” explains Kellner. “The lower the volatility, the more passive people are going to be, and the more likely there will be more trading in dark pools.”
Dark pools accounted for 13 percent of U.S. equity volume in March, according to estimates by Tabb Group. Typically, dark pool market share has been 10 percent to 12 percent of equity volume, but in January this year, it hit a high of 14 percent, according to Cheyenne Morgan, a senior analyst at Tabb Group who tracks equity volume for dark and lit markets. “People continue to use them and are more comfortable trading in the dark,” she says. “That’s the reason for the higher market share.”
But coupled with the growing volume of internalized trades — which occur when brokers match orders on sales trading desks or via algorithms before routing them to trading venues — the growth of dark pools is stoking a long-simmering controversy over transparency into executions. Nearly one-third of U.S. equity flow was traded away from exchanges during the first quarter of 2012, estimates Tabb Group. And Tabb Group founder and CEO Larry Tabb says buy-side traders are turning to internalizers — big brokers that match trades internally — and dark pools much earlier in the trading process.
Wall Street & Technology, Dangers of the Dark? here.
Yesterday, Tabb Group released some statistics on U.S. equity volumes that should raise some eyebrows as to why order flow is going underground. According to the market research and advisory firm, 32.96 percent of US equities trading volume — or nearly one third— is traded away from the primary exchanges. Due to an error, the firm originally reported that 37 percent of US equities trading volume was traded off-exchange, suggesting that internalization had reached a new high.
But today, Tabb Group corrected the error. “This did not represent a historic high. Nevertheless, the error does not invalidate the concerns expressed in our comments about the rise in off-exchange trading,” noted co-founder and CEO Larry Tabb in a statement.
But the surprising part is that dark pools only make up about 13 percent of U.S. equity volume. The rest (19. 3 percent) is being executed through internalization — a practice whereby brokers match the orders internally on their own trading desks — before the orders are sent to dark pools or exchanges, according to Tabb.
In February, off-exchange trading was 34 percent of U.S. equity volume (including both internalization and dark pools) , so that has dropped to about 33 percent in March, By comparison, in 2008 internalization and dark pools totaled 15 percent, according to the market research and advisory firm.
We already knew that for the past few years, buy-side institutions have preferred to execute in dark pools first before going to the public markets. Dark pools are private, electronic networks that match buy and sell orders — to avoid market impact, preserve anonymity and execute at the midpoint of the bid-ask spread. But what’s behind the increase in internalization?
Petrella and Anoli, Internalization in European Equity Markets Following the Adoption of the EU Mifid Directive, 2007, here.
This paper uses order flow and limit order book data in order to estimate the internalization rate (i.e., the portion of the total order flow that could be internalized), to estimate the internalization expected revenues, and to investigate the main factors affecting both the internalization rate and the magnitude of internalization revenues. To simulate the systematic internalization activity we collected detailed order flow data for 57 liquid stocks traded on the Italian Stock Exchange, which is a currently concentrated market. To be internalized, an order should jointly satisfy the following two requirements (expressly requested by the Level 1 law text). First, the quantity of the order should not be greater than the estimated standard market size (SMS). Second, the price limit of the order should be compatible with immediate execution by a systematic internalizer in respect of the best execution principle. Based on this procedure we identify internalized orders and compute estimates of internalization rate, gross trading revenues, spread revenues and positioning revenues on a per stock per day basis and on a per internalizer firm per day basis.
Our main findings relate to (i.) the relationship between internalization rates and stocks turnover; (ii.) the size and variability of internalization trading revenues; (iii.) the value of the inventories for an internalizer firm.
Bissel, NYT Sunday Book Review, Neal Stephenson’s Novel of Computer Viruses and Welsh Terrorists, here. Like a a big slab of Buttah.
Let us say that novelists are like unannounced visitors. While Norman Mailer and Saul Bellow pound manfully on the door, Jonathan Franzen and Zadie Smith knock politely, little preparing you for the emotional ferociousness with which they plan on making themselves at home. Neal Stephenson, on the other hand, shows up smelling vaguely of weed, with a bunch of suitcases. Maybe he can crash for a couple of days? Two weeks later he is still there. And you cannot get rid of him. Not because he is unpleasant but because he is so interesting. Then one morning you wake up and find him gone. You are relieved, a little, but you also miss him. And you wish he’d left behind whatever it was he was smoking, because anything that allows a human being to write six 1,000-page novels in 12 years is worth the health and imprisonment risk.
High Frequency Traders, Packet Processing in High Frequency Trading, here.
HFT: The low-latency space is moving very quickly. How is it possible to ensure that solutions are future-proof?
Eric: Our technology has a number of benefits that can be used to ensure we are always up to date. First of all, we have a portable solution which runs on all the industry leading multi-core platforms. As those platforms become quicker and more powerful we will automatically benefit. There is also a trend in the industry for increasing numbers of cores. When we have more cores we will be able to distribute the packets to a larger number of cores, which means that within a latency budget we will be able to manage a larger bandwidth. This means that when the number of transactions increases we will be able to allocate them to more cores. Our technology can be implemented on a single processor board but also be extended over several boards if you need more cores to process the packets. Regarding networking features, we will be able to use more processing capability to implement more sophisticated features while also keeping the latency budget at the same level. Thanks to technology improvements we will have more processor cycles and we will be able to do more. We are very well positioned to benefit from processor technology improvement and fulfil future HFT requirements.
Funny; solutions that are ensured to be future-proof. This is why we can’t have nice things and also explains why there are Credit Default Swaps and the Bellagio.
DeLong, MARTIN WOLF: PANIC HAS BECOME ALL TOO RATIONAL, here.
Suppose that in June 2007 you had been told that the UK 10-year bond would be yielding 1.54 per cent, the US Treasury 10-year 1.47 per cent and the German 10-year 1.17 per cent on June 1 2012. Suppose, too, you had been told that official short rates varied from zero in the US and Japan to 1 per cent in the eurozone. What would you think? You would think the world economy was in a depression. You would have been wrong if you had meant something like the 1930s. But you would have been right about the forces at work: the west is in a contained depression; worse, forces for another downswing are building, above all in the eurozone. Meanwhile, policy makers are making huge errors.
Naked Capitalism, The Real Bombshell in the MF Global Post Mortem, here.
But the real stunner comes early in the report, and the media write ups thus far seem to have missed it completely. Recall that the trade that felled MF Global was one directed by Corzine, and has been depicted as a repo-to-maturity trade, in which the maturity of the repo matched that of the underlying asset exactly. That in turn allowed the trade to be treated as off balance sheet, which was helpful in presenting the firm’s results to ratings agencies and analysts.
The bet that commentators focused on was that the European governments would not default before the maturity of the short-term trades, and the transactions allegedly would have worked out had MF Global survived. (Note that press commentary has focused on an Italian bond). The problem has been widely described as one of short-term price moves, namely, that Corzine and other managers allegedly did not know that if the price of the maturing bonds it bought fell more than 5%, it would have to post more collateral, and that adverse price moves triggered the liquidity crisis.
It turns out this description of the trade isn’t accurate. It never was a real repo to maturity, as in maturity match funded externally. The funding was two days shorter than the maturity of the asset. But, no joke, MF Global dressed that up internally and somehow got accountants and regulators to buy off on this bogus characterization. And even worse, this scheme produced book profits at the expense of liquidity, the real scarce commodity at the firm: