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

Overview

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.

Calibration

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

Summary

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

References

[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

1年后,"美国制造"可能比“中国制造”成本更低!(组图)

1年后,"美国制造"可能比“中国制造”成本更低!(组图)

文章来源: - 新闻取自各大新闻媒体,新闻内容并不代表本网立场!
  (被阅读 15530 次)
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。

据彭博社报道,在此次会议之前,IBM公司CEO罗睿兰描绘了该公司填补美国技术职位空缺的愿景:在美国新增2.5万个工作职位,并将在未来四年投资10亿美元。

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。



▲图片来源:东方IC

在此背景下,一个不可忽视的真相是,中美制造成本差距正在缩小。

两个月前(10月7日),来自中国福建的亿万富豪——福耀玻璃董事长曹德旺在美国莫瑞恩投资6亿美元建设的汽车玻璃工厂正式竣工投产,而根据福耀玻璃昨日(15日)向每日经济新闻(微信号:nbdnews)提供的数据显示,当地政府至少向其补贴了3000多万美元。

一面是中国制造成本的不断上升,一面是美国政府力推的制造业回归。有机构预测,2018年,美国制造成本将比中国制造便宜2%~3%。

“我购买厂房基本上没花钱”

“不久前的一个早上,当私人飞机降落在俄亥俄州后不久,曹德旺,这位中国亿万富翁就动身驱车沿75号州际公路前往他所豪赌的工厂。在这间工厂上,他赌上了自己的遗产,以及美国夕阳工业区(原文称之为“铁锈地带”)的未来。”

这是10月27日,《华盛顿邮报》头版对曹德旺的一篇报道的开头。



▲图片来源:华盛顿邮报

在2016年福布斯全球亿万富豪排行榜上,曹德旺以17.4亿美元的身家位列第1198名。

根据福耀玻璃向每日经济新闻(微信号:nbdnews)提供的资料显示,福耀玻璃早在1995年就进军美国市场,美国作为全球最重要的汽车消费市场和生产国,一直在福耀的发展战略中占据重要地位。福耀在美国市场的年销售额近4亿美元,是福特、通用、克莱斯勒、卡特彼勒等美国品牌的供应商。

10月7日投产的福耀玻璃莫瑞恩工厂原址曾是通用汽车的工厂,2008年金融危机后,通用关闭了这座工厂,此后一直闲置,直到2014年3月被福耀买下。

目前,这座工厂是世界上制造汽车玻璃最大的单体工厂,面积18万平方米,整个厂区占地面积675亩里不仅采用了先进的设备,自动化程度高于国内现有工厂水平,主要生产汽车前挡玻璃、后挡玻璃、门窗玻璃以及天窗等汽车配套玻璃,具备450万套配套产品和400万片配件产品的生产能力,雇佣当地工人2000多名。曾有人预计,全部投产后,美国每四辆汽车就有一辆配有福耀生产的玻璃。



▲图片来源:东方IC
 
福耀玻璃购买该工厂时,奥巴马政府已提出“让制造业回归美国”的政策。为了吸引中国制造业投资,美国从各级政府到民间机构都积极采取措施,营造适合制造业发展的投资环境和社会氛围,让中国制造业企业安心落户。

那么,曹德旺在美国的新工厂究竟拿到了美国政府的多少补贴呢?

曹德旺曾亲口表示:“我买这个厂房花了1500万美元,改造用了1500万美元,当地政府通过各种渠道补贴我3000多万美元,所以我购买厂房基本上没花钱。”

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

如此优厚的补贴,有多少企业家能一点也不心动?

福耀玻璃方面还向每日经济新闻(微信号:nbdnews)记者透露,2014年7月,福耀成立福耀美国伊利诺伊有限公司,收购世界汽车玻璃巨头PPG公司旗下芒山(Mt.Zion)工厂,包括土地、厂房、两条浮法玻璃生产线设备等。2016年6月,芒山工厂的两条浮法玻璃生产线均完成升级改造,进入正式生产阶段,年产量达28万吨。

除了上述两个项目之外,福耀集团在美国密歇根州有附件装配工厂以及产品设计中心,并在多个州设立了销售部门,形成了汽车玻璃完整的供应链,未来,福耀还将继续在美国建立研发中心和汽车玻璃生产基地的意向,预计总投资额达到10亿美金,以及5000个就业岗位。

中美制造成本差距在缩小,但人工成本仍是挑战

据波士顿咨询公司2013年的研究报告,当时在美国制造商品的平均成本只比在中国高5%。2015年,在美国低成本地区生产已经变得和在中国生产一样经济划算。更令人震惊的是,到2018年,美国制造的成本将比中国便宜2%~3%。



▲图片来源:财富中文网

这个预测很可能要成真,因为中美制造的成本差距正在缩小。

此前,一家浙江制造企业给出的中美制造成本对比的精准数据也颇令人瞩目。浙江省慈溪市江南化纤有限公司成立于2000年,一直位居国内同行出口的前列。

2014年,“江南化纤”在美国南卡罗莱纳州投资办厂,成为首家在美国建立再生聚酯短纤维制造工厂的中国企业,一期计划投资2500万美元,二期计划投资2000万美元。“江南化纤”反映,去美国投资办厂,主要原因是国内综合成本连年攀升,颇感吃力。“江南化纤”测算比较了创办相同规模企业的中美成本,并提供了部分成本构成对比表。其中:

土地成本:中国是美国的9倍;

物流成本:中国是美国的2倍;

银行借款成本:中国是美国的2.4倍;

配件成本:中国是美国的3.2倍;

人工成本:中国成本优势趋弱;

电力/天然气成本:中国是美国的2倍以上;

折旧成本:美国是中国的1.7倍;

……



只有厂房建设成本:美国是中国的4倍。

不过,《华盛顿邮报》也指出,对福耀玻璃而言,最大的两个挑战是招聘和发薪水。工人的起薪为一小时约12美元。

对此,曹德旺表示:“对美国投资,美国工人的工资和福利将占到总营业额的40%,的确比中国高。但制造业的税负却更少,只征收所得税,没有流转税的税负,这样就能省下一半。另外,美国的能源也比中国便宜。比如天然气的价格只是中国的五分之一,电费是国内三分之一。这对我们投资是个很大的鼓励。”同时,将生产基地移到国际市场的前沿,可以降低物流和服务成本。

当然,即使美国制造的成本真的比中国制造更低,也不能与“卖得更便宜”画上等号。如何避免,或者说如何应对这样一天的到来,值得所有关心制造业的人深刻思考。

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.

海淘税改新政对海淘海带的影响其实是这样(组图)

海淘税改新政对海淘海带的影响其实是这样(组图)

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4月8日,跨境电商税改正式实施,一张“浦东机场到处是不愿加税而弃置的商品”的照片顿时在网上传的是沸沸洋洋,隔着手机这小屏幕我都能感到它的热气腾腾。图片配文:

“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。”



(上面介个是图一)

这还不够,一张黄渤在海关被扣的照片自然也“不甘示弱”,这个转这个传啊。



(上面介个是图二,右边那个叉腰的人就是黄渤)

一票小伙伴炸了,反应各式各样:

“难道代购的小船已经彻底翻了咩?”

“南京条约只要百分之五的关税,你这是逼着我们求续约吗?”

“肿么办肿么办?要我裸着回国接受七大姑八大姨的犀利目光洗礼吗?”

事实证明,这种说话风格咋咋呼呼+爱用emoji的行文风格已经默默荣升为微博造谣的标准格式了。

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。



文章说了,图一发生的背景是这样子滴:一位从韩国归来的游客带了4箱东西,大概2万人民币以上彩妆和1.5万人民币左右的护理品。带太多东西海关需要清点数量,然而恰逢中转大厅装修,没地方清点,海关只能把东西铺在地上进行清点。

所以图一的画面,只是例行检查而已。

而黄渤那张照片就更搞笑了,2015年在巴黎机场的黄渤愣生生地穿越到2016年的浦东机场,还跟风走了个微博热搜。远在泰国剧组拍戏的渤哥嘻嘻哈哈地表示:分身术段数太高,在下不会。



那么,让大伙儿一惊一乍的4月8日跨境电商税改新政到底是个神马东东?

北京时间3月24日,中国财政部、海关总署、税务总局联合发布《关于跨境电子商务零售进口税收政策的通知》,宣布:

自2016年4月8日起,中国将实施跨境电子商务零售(企业对消费者,即B2C)进口税收政策,并同步调整行邮税政策。

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?

这分为两个最受人关注的小问题:我往中国寄东西会受到影响吗?我往中国“人肉”东西会受到影响吗?

下面我就来一一解答。

B2C是个啥玩意?

微博上有一位自称是海关工作人员的网友“客官不要急”做了科普。

(对于真实性有所怀疑的小盆友不要急,我是认真做了真实性分析的。微博认证为“共青团中央官方微博”的“共青团中央”都转发了他的微博,所以还是比较靠谱的。)





目前东西从境外进入中国有三种渠道:

1. B2B (Business to Business)

商业对商业,商家对商家,走货物渠道。税率为关税+增值税+消费税。

跟一般小伙伴都没有什么关系,本次改革也不受影响。

2. B2C (Business to Customer)

商家对个人,就是广大海淘热爱者熟知的洋码头之流。

本次税收政改最受影响的群体。

3. C2C (Customer to Customer)

不算严谨,但是“自用”“合理”范围的携带和寄送都属于这个类别。

适用行邮税。

普罗大众最关注的“我往中国寄东西会受到影响吗?”“我往中国‘人肉’东西会受到影响吗?”都属于这个类别。

行邮税是个啥玩意?

正儿八经的来讲:

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。

说人话就是:

哎呀,我给我在中国的老爸老妈寄点保养品什么的/我好闺蜜出国给我带点东西回中国的,又不是卖的,还要算关税增值税消费税,乱七八糟的好麻烦,合成一个好了啦。于是,行邮税就产生了。

4月8日税改新政跟我有没有关系?

简单的来讲,4月8日税改新政对跨境电商的影响最大,体现为:

a.跨境电商税率变了

b.跨境电商免税额消失了

c.跨境电商有数额限制了

对关心“我往中国寄东西会受到影响吗?”“我往中国‘人肉’东西会受到影响吗?”的小伙伴来说,相关的只是:行邮税变了。

综合还在实行的旧规定和现行的新规定,具体情况是这样的:

1. 如果你要“人肉”东西回中国

(1)你享有的免税额是这个样子滴

在维持居民旅客进境物品5000元人民币免税限额不变基础上,允许其在口岸进境免税店增加一定数量的免税购物额,连同境外免税购物额总计不超过8000元人民币。

举例说明:

?你在美国买了5000人民币+在上海机场免税店买了3000人民币=不用交税

?你在美国买了3000人民币+在上海机场免税店买了5000人民币=不用交税

?你在美国买了5000人民币+在上海机场免税店买了5000人民币=超出的2000人民币要交税

?你在美国买了7000人民币+在上海机场免税店买了1000人民币=超出的2000人民币要交税(虽然总数不超过8000人民币,但是境外部分7000元超出了规定的5000元,超出的2000元部分要交税)

如果你超出了免税额,中国海关会对超出的部分,按照行邮税进行征税。

(2)你享有的限额是这个样子滴

首先需要明确的是,限额不等于免税额。超出免税额要交税,超过限额就要另行处理了。

如果你要“人肉”东西回国,你带的东西要在自用合理范围内,不能有倒卖嫌疑。如果你一下子带N多N多N多一模一样的口红,谁会信你是自己用啊……

如果你超过限额,会全部按照货物征收税款,或者退运。

(3)关于海关严查

各个口岸不一样,但是百分百开箱查验是不可能的。

2. 如果你要邮寄东西回中国

(1)你享有的免税额是这个样子滴

50块人民币。如果你超出了免税额,中国海关会对全部物品,按照行邮税进行征税。

(2)你享有的限额是这个样子滴

自用合理数量+单包裹多物品1000人民币以内。

超过1000人民币的限额是退运或者按货物报关。重申一点:限额不等于免税额,邮寄的免税额只有50元人民币。

(3)关于海关严查

包裹太多,百分百开包也是不可能的。开过箱的包裹里面会放查验告知单。

(总体是涨了,但是有些东西反而降了。例如护肤品,原先是统一50%的税率,今后是30%。但是未列明的物品从原来10%的税率涨到30%。)

3. 现行税率

根据美国侨报报道,行邮税由4档税目调整为3档(税率分别为15%、30%、60%)。其中,税目1主要为最惠国税率为零的商品,税目3主要为征收消费税的高档消费品,其他商品归入税目2。



但据上面提到的”客官不说话”透露,化妆品的税率已经降为30%了,但是网页显示仍为60%。

完税价格

简单来说,就是价格不一样的东西,海关会定一个海关价格,差不多在这个价格区间里面的(1/2-2倍),那就套用海关价格。在这个价格区间之外的,那就物主提供海关认可的付款凭证(发票,小票,网站购买截图),海关根据实际价格计算。

中国海关总署发布了《中华人民共和国进境物品完税价格表》,网址如下:

http://www.customs.gov.cn/publish/portal0/tab49661/info793342.htm

下面截取大家最为关心的表、化妆品和包的部分。