Thursday, January 5, 2017

Manage Smile Risk with the SABR Model of Stochastic Volatility

Manage Smile Risk with the SABR Model of Stochastic Volatility
FINCAD Analytics Suite 2009 for Excel and FINCAD Analytics Suite 2009 for Developers expand FINCAD's coverage to price and hedge interest rate derivatives consistent with the market smile dynamics by adding pricing functions using the SABR model of stochastic volatility.
To evaluate the lastest version of FINCAD Analytics Suite for free, contact a FINCAD Representative


The seemingly simple task of pricing and hedging a swaption can become challenging if a volatility smile/skew is present in the market data - defined as a non-constant Black volatility as a function of the exercise rate of the swaption. This is due to the fact that one needs a model consistent with the entire volatility surface.

One of the first successful models to address this need is Dupire's local volatility model [3] which can be self-consistently calibrated to the entire volatility surface. However, as discussed in [4], the dynamic behavior predicted by Dupire's local volatility model is opposite to the behavior empirically observed in interest rate markets. Specifically, Dupire's local volatility model predicts that when the underlying forward rate decreases, the smile shifts to higher prices and when the underlying forward rate increases, that the smile shifts to lower prices.

The Stochastic Alpha Beta Rho (SABR) model is a model of stochastic volatility introduced by Hagan et. al. [4] as an attempt to model the volatility surface and to capture the empirically observed dynamic behavior of the smile.

Besides pricing and hedging the derivatives, another appealing application is to construct the "volatility cube" (vol cube)[1], which is a representation of swaption market data characterized by three parameters: option maturity, swap tenor and exercise rate (or strike). Some parts of the vol cube can be populated by data easily obtained from the market, such as at-the-money (ATM) swaption vols and the Black volatilities for caplets (floorlets) (which can be thought of as one-period swaptions). The rest of the vol cube can be determined by interpolation with the help of the SABR model [1].
The SABR model has gained widespread use due to its tractable pricing, ability to capture both the correct shape of the smile, as well as the correct dynamics of the volatility smile. It also gives practitioners the flexibility to use their intuition regarding market dynamics. For an in depth introduction to the SABR model, consult [4], [5].

FINCAD Analytics Suite 2009 provides functions to value swaptions and interest rate caplets/floorlets along with the functionality to calibrate the SABR model with swaption or caplet/floorlet volatilities.

Pricing Interest Rate Derivatives

Caplets and swaptions are essentially options on the underlying interest rate and forward swap rate, respectively. The SABR model assumes that the underlying rate f follows the stochastic differential equations
Stochastic differental equations
Hagan et. al derived the celebrated asymptotic formula for the effective Black volatility in the SABR model [4],

The beauty of the SABR model is that the prices of caplets or swaptions are given by the Black formula with a modified volatility given in Equation (3) as long as the model parameters are in hand. FINCAD Analytics Suite 2009 provides functions to value caplets/floorlets and swaptions in the SABR model:
aaCaplet_SABR calculates the price and risk statistics of a caplet/floorlet.
aaSwaption_SABR calculates the fair strike and risk statistics of a swaption.
aaSwaption_SABR_fs calculates the fair strike and risk statistics of a swaption and allows free-style user inputs.


With a suitable set of SABR parameters in hand, pricing simply reduces to a calculation of the effective Black volatility, via Equation (3), to use in the Black formula. The bulk of the effort, therefore, comes down to choosing the "best" set of SABR parameters. The SABR parameters in Equation (1) can be determined by calibration to caplet/floorlet or swaption market data. The procedure will be slightly different for swaption calibration since ATM vol is more important than non-ATM vols.
It is empirically seen that the two parameters ρ and β have similar effects on the vol smile in that they both control the amount of skewness. Mathematically, (sometimes referred to as the "skewness" parameter) is a constant elasticity of variance (CEV) exponent (see [2]). β = 1 corresponds to a stochastic lognormal model and β = 0 corresponds to a stochastic normal model.
There are two methods used for determining β, both of which stem from the analytical form of the ATM vols in the SABR model, calculated by setting the strike rate k in Equation (3) to equal the forward rate f
Strike Rate K
The skewness parameter can be determined by performing linear regression on the log-log plot of historical par swap rates versus ATM vols [4] given by Equation (4).
Alternatively, β can be chosen by the practitioner by appealing to their market intuition. This may seem like an ad-hoc method to choose β, however by investigating Equation (4), specifically the behavior of the ATM vol as a function of β

This approximate equation describes the so-called "backbone", defined as the curve followed by the ATM vol as a function of the par swap rate. As the par swap rate changes, this curve represents how these changes affect the ATM vol. Notice that in the stochastic lognormal model, where β = 1 the backbone is flat. Financially this corresponds to a constant level of overall forward swap rates as the par swap rate changes. Some practitioners use this model since it represents a common model used throughout finance and they believe that the flat backbone "best represents their market" [4]. Nevertheless, the parameter β is usually chosen exogenously, and not via calibration.
Calibration of SABR parameters to swaption data proceed differently than the two other instrument classes (options and caplets/floorlets) in that when calibrating to swaptions, the parameter α is not determined by calibration, instead it is determined by the Equation (4). Given αATM, β, ρ and ν, Equation (4) can be inverted to give a cubic equation whose roots yield the value of α, meaning that the parameter α is chosen so that the ATM vols seen in the market are reproduced exactly. This is not done for caplets because caplets ATM data is not a widely quoted number - it may or may not exist in the marketplace. Swaption market data, on the other hand, is typically only quoted as ATM vols, so this must be taken into account during calibration.
FINCAD Analytics Suite 2009 provides functions to calibrate the SABR model to caplets/floorlets or swaptions data:
aaCalibrateCaplets_SABR calibrates the SABR model to caplet/floorlets.
aaCalibrateSwaptions_SABR calibrates the SABR model to swaptions.

Volatility Cube

As mentioned before, vol cube is a representation of swaption market data characterized by three parameters: option maturity, swap tenor and exercise rate (or strike). Market data can be used to directly populate two of the "faces" of the vol cube as follows.
First, the at-the-money (ATM) swaption vols can populate the ATM slice (defined by the condition that the exercise rate is the par swap rate).
Second, rate caps and floors can be used to populate the slice containing the smallest swap tenor. To achieve this, the caps (floors) must first be stripped to produce the Black volatility of the constituent caplets (floorlets) (this step can be achieved by using the FINCAD function aaVol_Crv2_Rcap_BL). The resulting series of caplets/floorlets can be thought of as one-period swaptions with a swap tenor equal to the frequency of the cap/floor.
With one more piece of information, we can construct the entire vol cube. In order to be able to use the function aaCalibrateSwaptions_SABR, we need more than just the ATM swaption market quotes. According to [1] there are two methods to determine non-ATM swaption vols. The method advocated by FINCAD is to apply the same smile shape as seen in the caplet data to the swaption vols. Numerically, this means that one calculates the difference between the furthest out-of-the-money OTM) and in-the-money (ITM) caplet vols and applies this difference to the swaption ATM vol to produce the corresponding non-ATM vols. For instance, suppose the par swap rate is 6%, and we see the following market caplet vols.
Strike Black Vol
2% 21.5%
4% 16.7%
6% 14.4%
8% 16.1%
10% 15.0%
The skew can be characterized by two numbers δ2% ≡ α2% - αATM = 7.1% and δ10% ≡ α10% - αATM = 0.6%. To produce the swaption data, simply apply these skewness shifts to the swaption data. A non-ATM swaption vol is approximated as α = αATM + δi. In the above scenario, with a 10Yx10Y swaption with an ATM vol of 11%, the two data points to use in the calibration are α2% = 11% + δ2% = 18.1% and α10% = 11% + δ10% = 11.6%. According to [1] this procedure is "not just 'parallel shifting' the caplet smile to longer swap tenors, but we are, on the contrary, calculating the implied cap smile in the surface instead". The FINCAD function aaCalibrateSwaptions_SABR will fix α by requiring the calibration to reproduce the ATM volatility exactly, and the other parameters by the usual minimization procedure. This method can therefore be used to interpolate in all the dimensions of the vol cube.
Screen shot of the inputs to aaCaplet_SABR for the calculations
Figure 1: Screen shot of the inputs to aaCaplet_SABR for the calculations

Example: Pricing a Caplet

In this example, we calculate the fair value and all risk statistics for a caplet using the SABR model. We use the FINCAD function aaCaplet_SABR for our calculations. Figure 1 shows the inputs for this function.
Given the inputs in Figure 1, we find the fair value of the caplet is 0:361, which was calculated with the function aaCaplet_SABR. The other risk statistics are shown in Figure 2.
Screen shot of the outputs from aaCaplet_SABR
Figure 2: Screen shot of the outputs from aaCaplet_SABR


FINCAD Analytics Suite 2009 provides functions to compute prices and all risk statistics for caplets/floorlets and swaptions using the SABR model. It also provides a function to calibrate the SABR model to market caplets/floorlets or swaptions data, which enable users to construct the volatility cube.
To evaluate the lastest version of FINCAD Analytics Suite for free, contact a FINCAD Representative


[1] Banking, SEB Merchant (2008), SEB's VolCube, Research Paper.
[2]Cox, J. (1975), Notes on Option Pricing 1: Constant Elasticity of Variance Diffusions, Working Paper, Stanford University.
[3]Dupire, B. (1994), Pricing with a Smile, Risk, 7(1): pp. 18-20.
[4] Hagan, Patrick S., Kumar, D., Lesniewski, A. S., and Woodward, D. E. (September 2002), Managing smile risk, Wilmott, pp. 84-108.
[5] Option Pricing with the SABR Model of Stochastic Volatility (2008), Math Reference Document, FINCAD.

Wednesday, January 4, 2017

No One Questioned This Hedge Fund’s Madoff-Like Returns

No One Questioned This Hedge Fund’s Madoff-Like Returns

  • Red flags abounded while hedge fund claimed 17% annual gains
  • Platinum was embroiled in rogue trades, Florida Ponzi scheme
In the years before Mark Nordlicht was arrested for what’s alleged to be one of the biggest investment frauds since Bernie Madoff’s, U.S. authorities had plenty of reasons to suspect something might have been fishy about his hedge fund, Platinum Partners.
As far back as 2007, Bank of Montreal accused Nordlicht of helping a rogue trader, costing it more than $500 million. Three years later, when the Securities and Exchange Commission was investigating what it called a “scheme to profit from the imminent deaths of terminally ill patients,” the agency discovered that Platinum had funded the deals. And in 2011, a Florida lawyer who confessed to running a $1.2 billion Ponzi scheme testified that Nordlicht, his biggest funder, lied to help him lure new investors.
Nordlicht exits federal court in Brooklyn on Dec. 19.
Photographer: Michael Nagle/Bloomberg
And then there were the remarkable profits: 17 percent annually on average from 2003 through 2015, with no down years. The returns were almost as smooth as the fake gains that Madoff claimed year after year, as measured by a popular metric called the Sharpe ratio.
But until Murray Huberfeld, who founded Platinum with Nordlicht, was caught up in a New York City municipal-corruption probe in June, no one at the fund had been charged with wrongdoing. Within weeks of Huberfeld’s arrest, federal agents raided Platinum’s midtown Manhattan office. On Dec. 19, Nordlicht and six others were arrested in what the government called a $1 billion fraud. Nordlicht and Huberfeld have pleaded not guilty, and Platinum’s main fund is being wound down after filing for bankruptcy. Montieth Illingworth, a spokesman for Platinum, declined to comment.

Smooth Returns

That Platinum was able to avoid scrutiny for so long illustrates flaws in the post-Madoff regulatory regime. While the SEC says it now conducts “risk-based examinations” of funds that have suspiciously smooth returns, the agency didn’t do a thorough on-site audit of Platinum until 2015, according to a person with knowledge of the matter. Judy Burns, an SEC spokeswoman, declined to comment.
“The returns alone make no sense,” said Joelle Scott, who investigates money managers as senior vice president at Corporate Resolutions Inc. in New York. “This isn’t a Madoff thing where it was hard to find. This was a glaring, documented history of bad behavior.”
The fund’s presentations for investors touted its top-tier auditors and “independent valuations” by an experienced consultant. But those gatekeepers relied on Platinum to provide information about its investments. The valuation consultant says the firm never visited the California oil fields that supposedly accounted for much of Platinum’s assets. Even a simple check of public records would have revealed they were barely producing oil.
Nordlicht, 48, a second-generation commodities trader, started Platinum in 2003 with seed money from Huberfeld, a penny-stock trader from Brooklyn whose family owned a chain of kosher fast-food restaurants. Nordlicht, who has the rumpled look of a professor, was the face of the fund. Huberfeld, 56, who had been sanctioned three times for alleged securities-law violations, stayed in the background.
Little known on Wall Street, Nordlicht and Huberfeld cultivated connections in New York’s Orthodox Jewish community. Among the investors they recruited were the Gindi family, owners of the Century 21 department-store chain, and real estate moguls Ruby Schron and Abraham Fruchthandler. The Gindis, Schron and Fruchthandler declined to comment.
“You win some, you lose some,” said another investor, Gordon Diamond, a meat magnate who served on the board of a Holocaust charity with Huberfeld. “I guess I should have done more due diligence.”

Platinum Gains

Platinum’s first close call came in 2007, when Bank of Montreal discovered that a natural gas trader had been covering up huge bets, many of them with the hedge fund. The bank was forced to liquidate the trades, resulting in big gains for Platinum, among others, according to Vince Lanci, who handled some of the bets as an independent trader and managed money for the fund.
The problem was that Platinum’s Nordlicht was also chairman of Optionable Inc., a brokerage that, according to prosecutors, provided price quotes to the rogue trader. Bank of Montreal sued Nordlicht, saying he helped devise the trades. Nordlicht denied knowing anything about the fraud, and the case was settled out of court.
The FBI investigated, arrested the rogue trader and charged the chief executive officer of Optionable with aiding the scheme. Both men pleaded guilty. Nordlicht wasn’t accused of wrongdoing by the government. When the Optionable CEO was released from prison in 2014, he went to work for a company controlled by Platinum.
The trades with Bank of Montreal helped Platinum record a 53 percent gain in 2007. That attracted investors, and its main fund’s assets more than doubled to $567 million by the end of the year.

Ostrich Boots

Nordlicht needed to put that money to work. That’s when he found Scott Rothstein, a Florida lawyer who was promising huge returns to investors who would advance him funds against future payments from legal settlements. Rothstein’s wild spending had turned him into a Gatsby-like figure on the Fort Lauderdale charity circuit. Short and stocky, he wore pinstriped suits, loud hand-painted ties and orange ostrich boots.
Platinum and related funds advanced him more than $100 million through a feeder fund at an annual interest rate of 50 percent. Rothstein would later say that was so high his investors should have known something was wrong. In 2009, he missed a payment. Nordlicht flew to Florida for a meeting, which Rothstein described in a deposition two years later, after he pleaded guilty to the fraud.
The two men sat facing each other on a couch in his office. Rothstein said in his deposition that he wasn’t sure if Nordlicht knew that the lawsuits and settlements didn’t really exist. “If we go down, you go down,” Rothstein recalled saying. “We’re in this together.”
Rothstein said Nordlicht told him his father had been investigated for fraud and that he didn’t want to relive the experience. He talked about the situation with Bank of Montreal.
“He was trying to explain to me without using the words that he was a player, that he got it,” Rothstein said. “He said these things only blow up when the parties start fighting.”

Never Charged

Rothstein said in his deposition that Nordlicht agreed to lie by giving positive references to potential investors. Over the next six months, Rothstein said, Platinum and related funds stopped advancing him money and received all but about $20 million back as he raised cash from others.
Nordlicht was never charged in connection with the Ponzi scheme and has denied helping Rothstein, who’s now in the witness protection program because he also informed on organized crime. Nordlicht wrote to investors that Platinum, like others, was tricked by Rothstein and that the fund recovered its losses by suing a bank for its role in the scheme.
With potential losses from Rothstein’s fraud averted, Platinum’s main fund posted gains of 21 percent in 2009 and 19 percent in 2010, according to investor presentations.
That year the fund popped up on the radar of the SEC, which was investigating a scheme involving a Los Angeles rabbi who, the agency later alleged, tricked terminally ill hospice patients into providing personal information so annuities could be purchased in their names.
The annuities were funded by Platinum, which had put up more than $56 million, according to investigation records. It spent four years building its case. But when its enforcement actions were announced in 2014, the SEC only fined the intermediaries who ran the scheme and a shell company set up by Platinum to hold its money. Nordlicht and the fund itself weren’t named or accused of wrongdoing.

Oil Flop

By then, Platinum was inflating its returns by reporting false valuations for some assets, according to prosecutors in Brooklyn who brought charges last month. One of the biggest was the California oil fields. The firm’s year-end financials for 2014 valued them at about $140 million. In reality, the project was a flop that barely produced any oil, people familiar with the matter said in August.
CohnReznick LLP, the New York accounting firm that audited Platinum’s financial statements, declined to comment. The valuation agent, Sterling Valuation Group, said it was lied to by the fund and didn’t check the information it was provided. Sterling’s reports noted that the valuations depended on what the fund told it, according to Eric Rose, a spokesman for the New York-based firm.
“Obviously, a more expensive valuation would involve such activities as visiting the investment location or interviewing personnel,” said Rose, who added that the valuation firm isn’t under investigation.
Because Platinum couldn’t sell the oil fields, the fund started to depend on money from new investors to pay off those who wanted their money back, prosecutors said. In December 2013, an intermediary introduced Huberfeld to Norman Seabrook, who controlled a pension fund as president of the New York City correction officers’ union, according to prosecutors.
Huberfeld agreed to pay Seabrook a kickback if he invested his union’s pension funds with Platinum, the U.S. said. After the union put in $20 million, the intermediary, who’s cooperating with the corruption probe, allegedly gave Seabrook $60,000 stuffed in a Ferragamo bag. Seabrook and Huberfeld pleaded not guilty.

‘SEC Room’

That money tided Platinum over for only a short time. “It can’t go on like this or practically we will need to wind down,” Nordlicht wrote in a June 2014 e-mail cited by the SEC.
The next year, SEC lawyers conducted an examination of Platinum. They spent so much time at its offices that Nordlicht started calling a conference room “the SEC room,” the person with knowledge of the matter said. When the lawyers left by the end of the year without bringing any charges, Nordlicht told investors he’d been given a clean bill of health, the person said.
That wasn’t exactly true. The SEC sued Platinum last month at the same time prosecutors filed their case and credited its examiners with uncovering suspicious activity.

Nordlicht displayed little concern when interviewed for an October 2015 Bloomberg article. In that story, hedge fund researcher Nate Anderson said Platinum displayed “red flags you can see from outer space.” Nordlicht argued that while he exploited loopholes, he always did it to earn money for the fund’s investors. “We’ll scour the four corners of the earth for the best risk-adjusted strategy,” he said.The next month, so many investors asked for their money back that Nordlicht was forced to admit that some of the fund’s assets couldn’t be sold right away. By that December, Platinum’s managers were contemplating fleeing the country, according to prosecutors.
“Assume we are not coming back to ny,” Huberfeld wrote in an e-mail to Nordlicht cited by prosecutors. “We can fly straight to Europe from Miami on Tuesday. Take passport.”

Friday, December 16, 2016



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15日凌晨3点,美元加息如期而来,而特朗普(Donald Trump)当天在位于纽约的特朗普大厦也举行了一场圆桌会议。根据此前预期,特朗普上台之后将采取减税+基建+宽松财政的整体策略,很可能带动制造业再度兴起。


罗睿兰在《今日美国》(USA Today)发表的一篇评论文章中曾表示,很多技术职位并不需要太高的学历,她鼓励政府在职业教育和职业培训方面进行大力投资。这一举动也被外界解读为迎合特朗普制造业回归政策的一项积极举措。
















此外,在总统大选期间,曹德旺甚至拿到了更多的优惠承诺。《华盛顿邮报》指出,包括特朗普在总统预选中的对手约翰·凯西克(John Kasich,共和党)州长在内的州政府官员向福耀承诺提供超过1千万美元的拨款和激励,成为有记录以来最高水平的激励措施之一。

▲John Kasich。图片来源:东方IC






















Wednesday, November 9, 2016

Hillary Clinton’s concession speech full transcript: 2016 presidential election

Hillary Clinton’s concession speech full transcript: 2016 presidential election

Trump Victory Big For Biotech

Trump Victory Big For Biotech

Agence France-Presse/Getty Images
But health-care stock indexes, of all things, are actually soaring, with the iShares Healthcare Index (IYH) and the Health care Select SPDR ETF (XLV) each up more than 2,.3% in morning market action.
It may seem odd at first glance given Trump’s vow to dismantle the Affordable Care Act. President Obama’s health-care law extended health benefits to millions of uninsured Americas, who are now able to pay for medical care, boosting profits for hospitals, pharmacies and some health insurers. And with both houses of Congress now in republican hands, the fear is that he can actually carry it off (though the reality may be quit different).
But look at what’s happening with drug makers. Biotech and pharmaceutical stocks, which make up 60% the weighting in the S&P Healthcare Index, are recovering today after enduring a sharp selloff over the past year, largely due to Clinton’s outspoken stance against drug price increases. Her defeat is viewed as a win for the industry, especially biotech companies developing expensive treatments for cancer, autoimmune disorders and various rare diseases.
The iShares Nasdaq Biotechnology ETF (IBB) was the big winner, jumping almost 7% today, followed by a 5.3% gain by the iShares U.S. Pharmaceutical ETF (IHE).
And drug wholesalers are enjoying a similar leap, with McKesson (MCK) and Amerisource Bergen (ABC) climbing more than 5% in recent market action.
It a bit of an odd move. Trump and other republicans made high drug prices part of their campaign messages. But the issue never had the priority for them that it did for Clinton, explain Citigroup analyst Robyn Karnauskas. “We will know more when the new president unveils his plans in coming months,” she writes in a recent note
For hospitals and some health insurers, however, Trump’s victory is akin to Armageddon, or at least that’s how investors are reacting.
“A GOP Triple Play: The worst possible outcome for HC stocks is a reality,” writes Sheryl Skolnick and Ann Hynes, health-care service analysts at Mizuho Securities in a note published this morning warning of “extreme risk” for stocks exposed to a repeal of Obamacare.
We see extreme risk of ACA repeal/replace, loss of the Medicaid expansion, a primary driver of results for both hospitals and health plans, and reversal of the many value-based regulations that promote home health care. Only the potential for a Senate filibuster protects the ACA. We therefore are downgrading our Buys to Neutral and cutting PTs for our covered companies.
Shares of Tenet Healthcare (THC) toppled 27% and LifePoint Health (LPNT) fell almost 12%.
In the insurance industry, Centene (CNC) and Molina Healthcare (MOL), the two largest Medicaid-focused health insurers, each fell 18%.

Tuesday, April 12, 2016

Why are swap rates below bond yields?

Why are swap rates below bond yields?

A trader monitors financial information on computer screens on the trading floor at Panmure Gordon & Co., as results continue to be announced in the 2015 general election in London, U.K., on Friday, May 8, 2015. David Cameron is on course to remain prime minister at the head of a minority government after the U.K. general election, an exit poll and early results indicated. The pound jumped. Photographer: Chris Ratcliffe/Bloomberg©Bloomberg
US interest rate swaps, popular derivatives that track government bond yields, have experienced a spectacular collapse this month with an array of reasons being suggested by traders.
This market emerged during the 1980s and has become a fundamental part of finance. Like bonds sold by companies, swap rates have historically traded at a premium over Treasury yields — seen as the risk-free rate for pricing other types of debt and derivatives.
Now dealers and users of US swaps, such as hedge funds, asset managers and companies, are watching the swap rate relationship to underlying Treasury yields, known as a spread, become increasingly negative. Last week, the 10-year swap rate at one stage was quoted 18 basis points below the 10-year Treasury yield. The current swap rate of 2.225 per cent trails that of the Treasury benchmark’s yield of 2.33 per cent by 10.5 basis points.
Why is a negative relationship prevailing?
Analysts at Deutsche Bank say the recent swap spread tightening reflects “tighter macro prudential regulation, higher capital requirements and reduced dealer balance sheet capacity”.
Also playing a role is swapping activity from companies selling debt.
Companies and institutional investors exchange floating rates of interest for fixed rates via a swap contract. When a company sells fixed-rate debt, it can use a swap to offset the payment of a bond coupon and pay a much lower floating rate — three-month Libor.
Such activity pushes swap spreads lower and has occurred when dealers have been swamped by sales of Treasury bonds from central banks and other investors. The combination of hefty company debt sales being swapped and higher dealer inventories of Treasury debt, helps explain why swap spreads are negative.
How serious is the current dislocation between swaps and bonds?

Some say swaps are a broken market and the most visible example of post-2008 regulation of the banking system that entails serious consequences for investors, banks, companies and even the US taxpayer.
The bigger implication is that the cost of funding US government deficits in the coming years, which are projected to climb sharply, may well be higher due to a tougher regulatory environment for banks that underwrite Treasury debt sales.
Deutsche’s regression analysis places a fair value of around 3 basis points for the 10-year swap rate over the underlying 10-year Treasury yield. It thinks “the days of positive double-digit spreads, and perhaps positive spreads full stop, could be behind us”.
And with year end and a Federal Reserve interest rate rise approaching, higher volatility looms for the swaps market. Last week’s moves represented some of the biggest daily shifts since the financial crisis.
How long can swap rates trade negative to Treasury yields?
Under normal market conditions the current inversion should be swiftly reversed, but thanks to tougher bank capital regulation, derivatives trading appears to have entered a new era. Currently, no one appears willing to normalise the relationship between swap rates and Treasury yields.
“For a trader, trying to pick the bottom offers a different risk/reward in today’s heavily scrutinised world, so we haven’t seen the type of aggressive buyers that we used to see when valuations move to extremes,” says Michael Cloherty, head of US rates strategy at Royal Bank of Canada.
Trading Treasuries and swaps relies on funding via the repurchase or repo market. Thanks to balance sheet constraints, the use of repo by dealers is shrinking, another factor sustaining negative swap spreads.
“As capital and balance sheet have become more scarce commodities, banks have responded by reducing the size of their repo books due to heavy balance sheet consumption and relatively low margins of the business,” says Deutsche.
That means hedge funds, which in the past would reverse any inversion, cannot rely on the repo market to buy US Treasuries and pay the fixed rate on a swap. For a bank, facilitating a repo trade on behalf of a hedge fund means having it sit on its balance sheet, consuming precious capital.



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“上海浦东机场出关口已经贴指示了。不管你是代购还是旅游,只要是带东西回国,2000元/月至20000/年,都要交税!海关会开箱检查,不懂价格的去 网上搜,EMS直邮的也要全部纳税!而且化妆品的税率竟然是60%。所以,出国旅游的小伙伴们,不是自己用的还是别带了,被税了划不来。”









认证为“中华人民共和国上海海关”的微信公众账号“上海海关12360”发文辟谣:你们又被骗了,真是Too Young Too Naive啊。







1. B2C是个啥玩意?

2. 行邮税是个啥玩意?

3. 4月8日税改新政到底跟我有没有关系?







1. B2B (Business to Business)



2. B2C (Business to Customer)



3. C2C (Customer to Customer)






行邮税是行李和邮递物品进口税的简称,是海关对人境旅客行李物品和个人邮递物品征收的进口税。 由于其中包含了进口环节的增值税和消费税,故也为对个人非贸易性人境物品征收的进口关税和进口工商税收的总称。










1. 如果你要“人肉”东西回中国















2. 如果你要邮寄东西回中国









3. 现行税率