Tuesday, January 24, 2017

Money-Fund Overhaul Gives Federal Home Loan Banks New Prominence

Money-Fund Overhaul Gives Federal Home Loan Banks New Prominence

A rise in debt issuance by the FHLBs lends fresh support to a U.S. mortgage market in flux

By Katy Burne
The Wall Street Journal
Jan. 23, 2017 7:30 a.m. ET
The Federal Home Loan Banks are emerging as one of the unexpected beneficiaries of last year’s money-market fund overhaul, lending fresh support to a U.S. mortgage market in flux as interest rates creep higher.
Money funds that invest in government debt are fueling a rise in debt issuance by the FHLBs, independently chartered financial institutions created by Congress 80 years ago to bolster U.S. housing finance. The increase is a boon to FHLB member banks like J.P. Morgan Chase & Co. and Wells Fargo & Co., which borrow from the FHLBs for a range of needs including to fund mortgage lending, and is the latest ripple from a series of regulatory changes at the heart of financial markets.
The home loan banks’ outstanding debt rose nearly 10% from a year earlier in 2016, finishing the year at $989.3 billion, its highest level since 2009. About 30% of their debt is now floating-rate debt, the most since at least 2002, and a nod to growing money-market fund appetite for short-term government debt.
Each of the 11 regional home loan banks lends to local members such as banks and other financial institutions, secured by the mortgage loans or bonds posted by the borrowers. Because the FHLBs were created by Congress, money funds often consider their debt to be the next best thing to government debt.
The lending surge isn’t the first turn in the spotlight for the FHLBs, which are headquartered in cities as diverse as Dallas, New York, Pittsburgh and Topeka, Kan. In the 2008 crisis, the Federal Reserve called FHLBs the “lender of next-to-last resort” after the Fed’s discount window, citing the home loan banks’ role in helping lenders survive the financial meltdown.

Home Grown

Federal Home Loan Banks have increased their outstanding borrowings, and the component that is floating-rate debt, to help fund new loans to banks.
Total debt outstanding
Top Borrowers from FHLBs*

Loans outstanding to member banks†
FHLB debt eligible to be bought by U.S. money funds‡
*through Sept. 30, 2016 †as of year end

‡Bonds with 397 or fewer days to maturity
Sources: FHLB Office of Finance; Inside Mortgage Finance (top banks) THE WALL STREET JOURNAL.
Wall Street Journal
It is the latest sign of how far-reaching the 2016 money-market overhaul has been. That effort, overseen by the Securities and Exchange Commission, aimed to prevent a repeat of the 2008 run on a large money-market fund that lost money on debt holdings issued by Lehman Brothers Holdings Inc.
The new regulations required so-called prime money-market funds holding mostly corporate securities to report daily share prices that fluctuate with changes in their portfolios, rather than fixed share values.
Over the past year, this prompted many investors to shift about $1 trillion from prime funds into government-debt funds that aren’t subject to the same restrictions. Funds flowed out of prime funds that once were the leading purchasers of bank commercial paper and certificates of deposit and into government-only funds.
Now the FHLBs, helped by the appetite from government funds, are lending money to banks that have seen their access to prime-fund cash curtailed.
“FHLBs have always been a source of attractive financing,” said Mark Cabana, interest-rate strategist at Bank of America Merrill Lynch. With the money fund overhaul having limited a source of short-term funding, “having the FHLBs step up is increasingly convenient.”
The FHLBs are the second-largest issuer of debt held by U.S.-taxable money-market funds, after the Treasury, according to iMoneyNet.
Government money funds like to buy the FHLB’s floating-rate securities because while they have maturities ranging from six to 18 months, their interest rates reset monthly or quarterly with the London interbank offered rate benchmark, and are attractive to investors anticipating a rising-rate environment.
Last year, the FHLBs’ regulator—the Federal Housing Finance Agency that also regulates government-backed mortgage giants Fannie Mae and Freddie Mac—warned the FHLBs were exposing themselves to the risk that they could be unable to refund maturing short-term debt called “discount notes” if the market dried up.
“We want them to always take advantage of opportunistic times,” said Andre Galeano, associate director of examinations in the division of FHLB regulation at the FHFA. “We don’t want them to have to issue when market conditions are not apt.”
David Messerly, investor relations director at the FHLB Office of Finance, said the FHLBs were in dialogue with their regulator about those concerns but declined to specify further. Since the warning, discount notes have fallen to 41.5% of outstanding FHLB debt, down from a peak of 54% in December 2015.
The increased lending by FHLBs also is timely because demand for their secured loans is growing, on account of new federal rules requiring banks to have predetermined levels of cash on hand.
With banks now subject to new liquidity rules and constrained from too much short-term borrowing, the FHLBs have stepped in and are able to provide low-cost loans to big U.S. banks.
The largest borrower from FHLBs is J.P. Morgan, which had $79.5 billion in loans outstanding in the third quarter, up 8% from the year before, according to Guy Cecala, chief executive of lending-trade publication Inside Mortgage Finance. A spokesman for J.P. Morgan declined to comment.
Wells Fargo is the second-largest borrower. Its borrowings hit $68.7 billion as of the third quarter, up 158% from the year earlier period. A Wells Fargo spokesman said the terms of FHLB loans make them attractive.
“Demand for our debt is strong, and that’s a good thing. It keeps liquidity flowing to member banks so they can keep lending,” Mr. Messerly said.
Write to Katy Burne at katy.burne@wsj.com

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.”