Archive for the ‘Sub-Prime!’ Category

November 11, 2015

Thursday, November 12th, 2015

There is speculation that negative interest rates are nothing special:

Now that Sweden and Switzerland have shown that negative benchmark interest rates don’t necessarily result in flights to cash, asset bubbles or banking strains, the global giants of central banking may be more willing to embrace sub-zero borrowing costs the next time their economies slide.

European Central Bank President Mario Draghi is open to reducing the rate he charges banks to leave money in his coffers overnight further into negative territory. Bank of England Governor Mark Carney has also revised his thinking to say the U.K. benchmark could fall below 0.5 percent if needed having previously worried deeper cuts would roil money markets.

Meantime, Fed Chair Janet Yellen said last week that “if circumstances were to change” then “potentially anything, including negative interest rates, would be on the table.” One of her policy-setting colleagues has already advocated them for next year.

Plumbing new depths the next time economies stumble would continue the pattern of the past few decades in which each of the peaks and troughs in rates were more often than not lower than in the previous business cycle.

It appears that I am no longer the only person in Canada who understands that trailer fees are only one of many broker incentives:

Canadian Oil Sands Ltd. is accusing Suncor Energy Inc. of buying support for its $4.3-billion hostile takeover bid, as the largest Syncrude owner seeks more time to drum up a richer offer.

In a red, bold-lettered “warning” sign posted on its website, Canadian Oil Sands says Suncor is paying brokers to get Canadian Oil Sands’ investors to tender their shares – a strategy it says shows Suncor’s bid is “exploitive” and “opportunistic.”

“Knowing the weakness of their bid, they feel it is necessary to pay brokers and incentivize them to encourage clients to tender their shares,” the notice reads.

“We don’t think that’s right. We think our shareholders should decide for themselves, free from the influence of brokers being financially compensated to do Suncor’s work for them.”

I eagerly await cries of astonished horror from the regulators.

I ran across two good papers on sub-prime today; the first, by Christopher Palmer, is titled Why Did So Many Subprime Borrowers Default During the Crisis: Loose Credit or Plummeting Prices?:

The foreclosure rate of subprime mortgages increased markedly across 2003-2007 borrower cohorts — subprime mortgages originated in 2006-2007 were roughly three times more likely to default within three years of origination than mortgages originated in 2003-2004. Many have argued that this surge in subprime defaults represents a deterioration in subprime lending standards over time. I quantify the importance of an alternative hypothesis: later cohorts defaulted at higher rates in large part because house price declines left them more likely to have negative equity. Using loan-level data, I find that changing borrower and loan characteristics explain approximately 30% of the difference in cohort default rates, with almost of all of the remaining heterogeneity across cohorts attributable to the price cycle. To account for the endogeneity of prices, I employ a nonlinear instrumental-variables approach that instruments for house price changes with long-run regional variation in house-price cyclicality. Control function results confirm that the relationship between price declines and defaults is causal and explains the majority of the disparity in cohort performance. I conclude that if 2006 borrowers had faced the same prices the average 2003 borrower did, their annual default
rate would have dropped from 12% to 5.6%.

The second, by Christopher L. Foote, Kristopher S. Gerardi and Paul S. Willen, is titled Why Did So Many People Make So Many Ex Post Bad Decisions? The Causes of the Foreclosure Crisis:

We present 12 facts about the mortgage crisis. We argue that the facts refute the popular story that the crisis resulted from finance industry insiders deceiving uninformed mortgage borrowers and investors. Instead, we argue that borrowers and investors made decisions that were rational and logical given their ex post overly optimistic beliefs about house prices. We then show that neither institutional features of the mortgage market nor financial innovations are any more likely to explain those wrong beliefs than they are to explain the Dutch tulip bubble 400 years ago. Economists should acknowledge the limits of our understanding of asset price bubbles and design policies accordingly

Fact 1: Resets of adjustable-rate mortgages did not cause the foreclosure crisis

Fact 2: No mortgage was “designed to fail”

Fact 3: There was little innovation in mortgage markets in the 2000s

Fact 4: Government policy toward the mortgage market did not change much from 1990 to 2005

Fact 5: The originate-to-distribute model was not new

Fact 6: MBSs, CDOs and other “complex financial products” had been widely used for decades

Fact 7: Mortgage investors had lots of information

Fact 8: Investors understood the risks

Fact 9: Investors were optimistic about house prices

Fact 10: Mortgage market insiders were the biggest losers

Fact 11: Mortgage market outsiders were the biggest winners

Fact 12: Top-rated bonds backed by mortgages did not turn out to be “toxic.” Top-rated bonds in collateralized debt obligations (CDOs) did.

The best part of the latter paper is that for the first time I’ve found a little authoritative data on the default rate of AAA RMBS (politicians find it much more useful to talk about the downgrade rate):

To start with, the top-rated tranches of subprime securities fared better than many people realize. The top panel of Figure 9 is generated from data on AAA-rated bonds created in 2006 from private-label securitization deals.27 Specifically, the panel shows the fraction of these bonds on which investors suffered losses or, using industry jargon, the fraction that was “impaired.” In some of these deals, 70 percent of the underlying subprime loans terminated in foreclosure (Jozoff et al. 2012). Yet despite these massive losses, the figure shows that investors lost money on less than 10 percent of private-label AAA-rated securities. How is that possible? As many have explained, the AAA-rated securities were protected by a series of lower-rated securities which absorbed most of the losses. If a borrower defaulted and the lender was unable to recover the principal, the resulting loss would be deducted from the principal of the deal’s lower-rated tranches. For subprime deals, the degree of so-called AAA credit protection—the principal balance of the non-AAA securities—was often more than 20 percent. Given a 50 percent recovery rate on foreclosed loans, 20 percent credit protection meant that 40 percent of the borrowers could suffer foreclosure before the AAA rated investors suffered a single dollar of loss. For riskier deals, credit protection was higher, often substantially so. The key takeaway is that for subprime securities, credit protection largely worked, and investors in the AAA-rated securities were largely spared.

The relatively robust performance of private-label AAA-rated securities is explained clearly in the final report of the Financial Crisis Inquiry Commission (2011), among other sources. Yet it still surprises many people. If these AAA-rated securities didn’t suffer losses, where were the famous “toxic mortgage-related securities” that caused the financial crisis? The answer is that banks used lower-rated securities from private-label deals to construct other securities, such as the collateralized debt obligations (CDOs) discussed earlier. Recall that because these CDOs were backed by tranches of subprime securities, which were technically labeled asset-backed securities (ABS), the resulting CDOs were called ABS CDOs. The main difference between the original ABS and the ABS CDOs was that the CDOs were not backed by 2,000 or so subprime loans, but rather a collection of 90–100 lower-rated tranches of subprime ABS deals, with most of these tranches having BBB ratings. Yet the organizing principal of CDOs and the original ABS securities was the same: senior AAA-rated tranches were protected from losses by lower-rated tranches. For the original ABS, losses would occur if individual homeowners defaulted. For the CDOs, losses would occur if the BBB-rated securities from the original ABS deals defaulted.

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Figure 9. Downgrades and Impairments Among Mortgage-Backed Securities (MBS) and Collateralized Debt Obligations (CDOs). The two panels on the left show that among private-label MBS, lower-rated tranches suffered massive losses. However, while a large fraction of AAA-rated tranches were downgraded, the vast majority of these tranches paid off, as few of them suffered actual impairments. The two panels on the right show that the same is not true for CDOs. Because these bonds tended to be backed by the lower-rated tranches of private-lable MBS, both the AAA-rated and the lower-rated tranches of CDOs suffered significant impairments. Source: Tables 12, 13, 17 and 18 in Financial Crisis Inquiry Commission (2010).

The difference between the ABS and CDO experiences has been discussed on PrefBlog previously, notably in the post Hull & White on AAA Tranches of Subprime.

I haven’t passed on any drone news lately … so here’s a fun drone story:

On a cool October night, after the stores in a shopping mall had closed, six young drone racers gathered in a subterranean parking garage to hone their aviation skills. Using remote-control joysticks, they navigated small X-shaped drones around pylons and beneath shopping carts, each vying for the lead.

The young men all work steady jobs, but racing drones, they said, has become a consuming new passion..

What the sport needs most at this stage is money, and in the last few months it has started to flow. In August, another organization, the Drone Racing League, announced a $1 million investment from the Miami Dolphins owner Stephen M. Ross through his investment arm RSE Ventures. The league’s chief executive, Nicholas Horbaczewski, would not reveal its plans, but he acknowledged reports that described races similar to video-game competitions held in large arenas. Horbaczewski said the company’s first major event would be in early 2016.

Pilots navigate the drones using a remote control with two joysticks that control altitude, speed and direction. They wear large goggles that broadcast live standard-definition video from a camera mounted on the front of the drone. It is this first-person-view technology, or F.P.V., that has given the sport a major boost, allowing pilots to feel as if they are in the drone. The experience, they said, is similar to the pod-racing scenes from “Star Wars: Episode I — The Phantom Menace.”

The drone frames are made of light but sturdy material like carbon fiber and are little more than small platforms for motors, a battery, electronic circuitry and four to six propellers. Most are of the four-motor variety and are thus better known among hobbyists as quadcopters, or quads, rather than drones.

“Three years ago, this technology was so expensive, so unattainable, that only the professional cinematographer could afford it,” [chief operating officer of the International Drone Racing Association Charles] Zablan said. Now, he said, a full racing kit with F.P.V. goggles can be bought for about $1,000.

It was a mixed day for the Canadian preferred share market, with PerpetualDiscounts gaining 4bp, FixedResets up 24bp and DeemedRetractibles off 14bp. The Performance Highlights table continues to show a lot of churn. Volume was average.

For as long as the FixedReset market is so violently unsettled, I’ll keep publishing updates of the more interesting and meaningful series of FixedResets’ Implied Volatilities. This doesn’t include Enbridge because although Enbridge has a large number of issues outstanding, all of which are quite liquid, the range of Issue Reset Spreads is too small for decent conclusions. The low is 212bp (ENB.PR.H; second-lowest is ENB.PR.D at 237bp) and the high is a mere 268 for ENB.PF.G.

Remember that all rich /cheap assessments are:
» based on Implied Volatility Theory only
» are relative only to other FixedResets from the same issuer
» assume constant GOC-5 yield
» assume constant Implied Volatility
» assume constant spread

Here’s TRP:

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TRP.PR.E, which resets 2019-10-30 at +235, is bid at 20.10 to be $1.02 rich, while TRP.PR.C, resetting 2016-1-30 at +154, is $0.55 cheap at its bid price of 14.01.

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Most expensive is MFC.PR.L, resetting at +216bp on 2019-6-19, bid at 20.65 to be 0.43 rich, while MFC.PR.F resetting at +141bp on 2016-6-19, is bid at 15.15 to be 0.50 cheap.

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The cheapest issue relative to its peers is BAM.PR.R, resetting at +230bp on 2016-6-30, bid at 16.51 to be $1.98 cheap. BAM.PF.E, resetting at +255bp on 2020-3-31 is bid at 21.00 and appears to be $1.13 rich.

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FTS.PR.K, with a spread of +205bp, and bid at 19.97, looks $0.86 expensive and resets 2019-3-1. FTS.PR.H, with a spread of +145bp and resetting 2020-6-1, is bid at 14.70 and is $0.65 cheap.

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Investment-grade pairs predict an average three-month bill yield over the next five-odd years of -0.58%, with one outlier above 0.00%. There are two junk outliers above 0.00% and two below -2.00%.

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Shall we just say that this exhibits a high level of confidence in the continued rapacity of Canadian banks?

HIMIPref™ Preferred Indices
These values reflect the December 2008 revision of the HIMIPref™ Indices

Values are provisional and are finalized monthly
Index Mean
(at bid)
Mod Dur
Issues Day’s Perf. Index Value
Ratchet 4.27 % 5.12 % 31,652 17.68 1 2.4984 % 1,819.2
FixedFloater 6.06 % 5.30 % 28,946 17.16 1 -4.3319 % 3,221.0
Floater 3.96 % 4.01 % 64,188 17.37 3 -2.7438 % 1,994.4
OpRet 4.84 % 4.56 % 33,233 0.78 1 0.1187 % 2,717.5
SplitShare 4.74 % 5.58 % 147,281 4.38 5 0.2806 % 3,209.3
Interest-Bearing 0.00 % 0.00 % 0 0.00 0 0.2806 % 2,504.0
Perpetual-Premium 5.81 % -1.14 % 87,406 0.08 6 -0.0859 % 2,500.3
Perpetual-Discount 5.51 % 5.63 % 83,445 14.46 33 0.0448 % 2,594.0
FixedReset 4.76 % 4.47 % 227,964 15.57 76 0.2374 % 2,149.2
Deemed-Retractible 5.17 % 5.21 % 108,240 5.42 34 -0.1377 % 2,585.1
FloatingReset 2.57 % 3.76 % 55,157 5.78 10 -0.4711 % 2,191.5
Performance Highlights
Issue Index Change Notes
TRP.PR.B FixedReset -4.80 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 12.90
Evaluated at bid price : 12.90
Bid-YTW : 4.47 %
BAM.PR.G FixedFloater -4.33 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 25.00
Evaluated at bid price : 15.68
Bid-YTW : 5.30 %
BAM.PR.B Floater -3.38 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 12.00
Evaluated at bid price : 12.00
Bid-YTW : 3.97 %
BAM.PR.K Floater -3.33 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 11.90
Evaluated at bid price : 11.90
Bid-YTW : 4.01 %
TRP.PR.A FixedReset -2.94 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 16.50
Evaluated at bid price : 16.50
Bid-YTW : 4.65 %
FTS.PR.G FixedReset -1.74 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 19.16
Evaluated at bid price : 19.16
Bid-YTW : 4.36 %
BMO.PR.R FloatingReset -1.74 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2022-01-31
Maturity Price : 25.00
Evaluated at bid price : 22.60
Bid-YTW : 3.73 %
BAM.PR.X FixedReset -1.55 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 15.86
Evaluated at bid price : 15.86
Bid-YTW : 4.79 %
BAM.PR.C Floater -1.49 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 11.90
Evaluated at bid price : 11.90
Bid-YTW : 4.01 %
SLF.PR.J FloatingReset -1.43 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 13.80
Bid-YTW : 9.15 %
TD.PR.T FloatingReset -1.32 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2022-01-31
Maturity Price : 25.00
Evaluated at bid price : 22.50
Bid-YTW : 3.76 %
BAM.PF.F FixedReset -1.26 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 21.71
Evaluated at bid price : 22.02
Bid-YTW : 4.61 %
SLF.PR.G FixedReset -1.23 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 15.26
Bid-YTW : 8.63 %
BAM.PR.Z FixedReset -1.18 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 21.42
Evaluated at bid price : 21.76
Bid-YTW : 4.76 %
IAG.PR.A Deemed-Retractible -1.14 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 21.66
Bid-YTW : 6.68 %
TRP.PR.F FloatingReset -1.13 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 14.90
Evaluated at bid price : 14.90
Bid-YTW : 3.93 %
MFC.PR.M FixedReset -1.12 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 21.11
Bid-YTW : 5.97 %
MFC.PR.F FixedReset 1.00 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 15.15
Bid-YTW : 9.09 %
RY.PR.J FixedReset 1.04 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 21.92
Evaluated at bid price : 22.38
Bid-YTW : 4.15 %
TD.PF.C FixedReset 1.10 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 20.14
Evaluated at bid price : 20.14
Bid-YTW : 4.24 %
TRP.PR.E FixedReset 1.11 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 20.10
Evaluated at bid price : 20.10
Bid-YTW : 4.47 %
TRP.PR.G FixedReset 1.12 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 21.39
Evaluated at bid price : 21.67
Bid-YTW : 4.54 %
CM.PR.P FixedReset 1.32 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 19.91
Evaluated at bid price : 19.91
Bid-YTW : 4.28 %
IAG.PR.G FixedReset 1.38 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 22.76
Bid-YTW : 5.30 %
BAM.PR.T FixedReset 1.39 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 18.25
Evaluated at bid price : 18.25
Bid-YTW : 4.80 %
IFC.PR.C FixedReset 1.50 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 20.35
Bid-YTW : 6.57 %
PWF.PR.T FixedReset 1.75 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 22.23
Evaluated at bid price : 22.70
Bid-YTW : 3.88 %
MFC.PR.J FixedReset 1.90 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 22.55
Bid-YTW : 5.20 %
TD.PF.D FixedReset 2.18 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 22.29
Evaluated at bid price : 23.00
Bid-YTW : 4.08 %
SLF.PR.H FixedReset 2.36 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 19.10
Bid-YTW : 6.87 %
BAM.PR.E Ratchet 2.50 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 25.00
Evaluated at bid price : 16.00
Bid-YTW : 5.12 %
IFC.PR.A FixedReset 3.03 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 17.00
Bid-YTW : 8.36 %
Volume Highlights
Issue Index Shares
TRP.PR.D FixedReset 73,026 YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 19.40
Evaluated at bid price : 19.40
Bid-YTW : 4.58 %
TRP.PR.E FixedReset 48,335 YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 20.10
Evaluated at bid price : 20.10
Bid-YTW : 4.47 %
BAM.PF.A FixedReset 37,825 YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 21.24
Evaluated at bid price : 21.52
Bid-YTW : 4.72 %
TD.PF.A FixedReset 22,048 YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 20.30
Evaluated at bid price : 20.30
Bid-YTW : 4.22 %
BMO.PR.S FixedReset 21,359 YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 20.42
Evaluated at bid price : 20.42
Bid-YTW : 4.28 %
TD.PR.Z FloatingReset 20,800 YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2022-01-31
Maturity Price : 25.00
Evaluated at bid price : 22.77
Bid-YTW : 3.64 %
There were 35 other index-included issues trading in excess of 10,000 shares.
Wide Spread Highlights
Issue Index Quote Data and Yield Notes
TRP.PR.B FixedReset Quote: 12.90 – 13.70
Spot Rate : 0.8000
Average : 0.4996

Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 12.90
Evaluated at bid price : 12.90
Bid-YTW : 4.47 %

BAM.PR.X FixedReset Quote: 15.86 – 16.65
Spot Rate : 0.7900
Average : 0.5528

Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 15.86
Evaluated at bid price : 15.86
Bid-YTW : 4.79 %

CU.PR.D Perpetual-Discount Quote: 22.40 – 22.92
Spot Rate : 0.5200
Average : 0.3677

Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 22.10
Evaluated at bid price : 22.40
Bid-YTW : 5.47 %

BAM.PR.G FixedFloater Quote: 15.68 – 16.50
Spot Rate : 0.8200
Average : 0.7006

Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 25.00
Evaluated at bid price : 15.68
Bid-YTW : 5.30 %

GWO.PR.N FixedReset Quote: 13.90 – 14.34
Spot Rate : 0.4400
Average : 0.3301

Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 13.90
Bid-YTW : 9.94 %

BAM.PR.B Floater Quote: 12.00 – 12.28
Spot Rate : 0.2800
Average : 0.1798

Maturity Type : Limit Maturity
Maturity Date : 2045-11-11
Maturity Price : 12.00
Evaluated at bid price : 12.00
Bid-YTW : 3.97 %

Tranche Retention in the sub-prime CDO Market

Wednesday, March 31st, 2010

Bloomberg has a fascinating story today titled How Lou Lucido Let AIG Lose $35 Billion With Goldman Sachs CDOs.

Without having to ask AIG’s permission, firms such as TCW, hired to oversee funds called collateralized debt obligations, replaced maturing assets with junk that quickly went bad. Managers including Lucido said they didn’t realize how severe the mortgage crash would be and were called upon by CDO contracts to reinvest. At the same time, buying riskier assets could mean bigger paydays.

Lucido’s team, following criteria set by [under-writer] Goldman Sachs, changed almost one-third of the collateral in Davis Square III after the CDO’s creation in 2004, according to data compiled by Bloomberg from Moody’s Investors Service reports. The securities were mostly backed by the types of newer loans that are going bad at more than twice the rate of older ones. By November 2008, after U.S. taxpayers rescued AIG with a bailout that later swelled to $182.3 billion, even the highest-rated parts of Davis Square III had lost almost half their value.

When the Financial Products unit agreed to guarantee certain top-rated CDO pieces, it didn’t envision that assets added later could cause losses, according to a person with knowledge of AIG’s thinking who spoke on condition of anonymity because he wasn’t authorized to comment.

As long as managers adhered to investment criteria outlined in the prospectus, there was little AIG could do, according to Mark Herr, a spokesman for the insurer.

The tiniest slice, less than 1 percent in the case of Davis Square III, was made up of what’s called equity, which wasn’t rated by credit companies. Equity investors were paid only after everyone else. They received a higher return while the going was good because they took the most risk and were the first ones wiped out if borrowers quit paying their mortgages.

While Lucido said he didn’t own a stake in Davis Square III, he said he did have his own money riding on the equity pieces of some CDOs.

Goldman Sachs did own an equity stake in Davis Square III, according to Michael DuVally, a spokesman for the firm, who declined to say how much it was. Even so, the bank didn’t try to influence TCW’s investment decisions, DuVally said.

It didn’t have to. TCW was promised 20 percent of what was left over after equity investors got 10 percent returns, according to a Goldman Sachs sales pitch to potential equity investors dated September 2004. That was on top of its fee of 0.10 percent of the CDO’s assets, according to the prospectus.

[Andrey Krakovsky, chief investment officer at New York-based asset manager Tacticus Capital LLC,] said managers often owned equity pieces of CDOs and earned fees linked to their returns.

More than $16 billion of CDOs managed by TCW have defaulted, been liquidated or stopped paying some investors, according to RBS Securities Inc.

TCW now finds itself defending Gundlach’s team at the same time it’s suing him for having “no understanding or respect for the obligations of a fiduciary,” according to a complaint filed Jan. 7 in Los Angeles Superior Court.

It is unfortunate, but nowhere does the article discuss the track record records of the managers of these CDOs. Like so much other smiley-boy stuff, it prefers to talk about “experience”.

However, my point in highlighting this article has more to do with tranche-retention than investment management. Tranche retention has been both disparaged and and praised as a method for encouraging investment managers to think about what they’re doing; this article represents another small, but useful, point against the concept.

Hull & White on AAA Tranches of Subprime

Friday, January 15th, 2010

John Hull and Alan White have published a working paper titled The Risk of Tranches Created from Residential Mortgages:

This paper examines, ex-ante, the risk in the tranches of ABSs and ABS CDOs that were created from residential mortgages between 2000 and 2007. Using the criteria of the rating agencies, it tests how wide the AAA tranches can be under different assumptions about the correlation model and recovery rates. It concludes that the AAA ratings assigned to the senior tranches of ABSs were not totally unreasonable. However, the AAA ratings assigned to tranches of Mezz ABS CDOs cannot be justified. The risk of a Mezz ABS CDO tranche depends critically on the correlation between mortgage pools as well as on the correlation model and the thickness of the underlying BBB tranches. The BBB tranches of ABSs cannot be considered equivalent to BBB bonds for the purposes of subsequent securitizations.

This paper won’t be popular amongst the Credit Ratings Agencies Are Evil crowd!

Credit derivatives models often assume that the recovery rate realized when there is a default is constant. This is less than ideal. As the default rate increases, the recovery rate for a particular asset class can be expected to decline. This is because a high default rate leads to more of the assets coming on the market and a reduction in price.

As is now well known, this argument is particularly true for residential mortgages. In a normal market, a recovery rate of about 75% is often assumed for this asset class. If this is assumed to be the recovery rate in all situations, the worst possible loss on a portfolio of residential mortgages given by the model would be 25%, and the 25% to 100% senior tranche of an ABS created from the mortgages could reasonably be assumed to be safe. In fact, recovery rates on mortgages have declined in the high default rate environment experienced since 2007.

The evaluation of ABSs depends on a) the expected default rate, Q, for mortgages in the underlying pool, b) the default correlation, ρ, for mortgages in the pool, and c) the recovery rate, R. Data from the 1999 to 2006 period suggest a value of Q less than 5% assuming an average mortgage life of 5 years. But, as has been mentioned, a different macroeconomic environment could be anticipated over the next few years. It would seem to be more prudent to use an estimate of 10%, or even higher. We will present results for values of Q equal to 5%, 10%, and 20%. The Basel II capital requirements are based on a copula correlation of 0.15 for residential mortgages.6 We will present results for values of ρ between 0.05 and 0.30. As already mentioned, a recovery rate of 75% is often assumed for residential mortgages, but this is probably optimistic in a high default rate environment. We will present results for the situation where the recovery rate is fixed at 75% and for the situation where the recovery rate model in the previous section is used with Rmin=50% and Rmax=100%.

ABS CDOs also depend on the parameter, α. Loosely speaking, this measures the proportion of the default correlation that comes from a factor common to all pools. A value of α close to zero indicates that investors obtain good diversification benefits from the ABS CDO structure. In adverse market conditions some mezzanine tranches can be expected to suffer 100% losses while others incur no losses. However, a value of α close to one indicates that all mezzanine tranches will tend to sink or swim together. We do not know what estimates rating agencies made for α. (Ex post of course, we know that it was high.) We will therefore present results based on a wide range of values for this parameter.

The meat of the matter – at least as far as the CRAs are concerned – is:

Table 2 shows that when a 20% default rate is combined with a high default correlation, and a stochastic recovery rate model, the AAA ratings that were made seem a little high. Also, the ratings are difficult to justify when the most extreme model (double t copula, stochastic recovery rate) is used. But overall the results in Table 2 indicate that the AAA ratings that were assigned were not totally unreasonable.

Very bad things happened to CDOs created from the mezzanine tranches of the structures – and here the CRAs can be faulted:

It should be noted that a CDO created from the triple BBB tranches of ABSs is quite different from a CDO created from BBB bonds. This is true even when the BBB tranches have been chosen so that their probabilities of default and expected losses are consistent with their BBB rating. The reason is that the probability distribution of the loss from a BBB tranche is quite different from the probability distribution of the loss from a BBB bond.

The authors conclude:

Contrary to many of the opinions that have been expressed, the AAA ratings for the senior tranches of ABSs were not unreasonable. The weighted average life of mortgages is about five years. The probability of loss and expected loss of the AAA-rated tranches that were created were similar to or better than those of AAA-rated five-year bonds.

The AAA ratings for Mezz ABS CDOs are much less defensible. Scenarios where all the underlying BBB tranches lose virtually all their principal are sufficiently probable that it is not reasonable to assign a AAA rating to even a quite thin senior tranche. The risks in Mezz ABS CDOs depend critically on a) the width of the underlying BBB tranches, b) the correlation between pools, c) the tail default correlation, and d) the relationship between the recovery rate and the default rate. An important point is that the BBB tranche of an ABS cannot be assumed to be similar to a BBB bond for the purposes of determining the risks in ABS CDO tranches.

In practice Mezz ABS CDOs accounted for about 3% of all mortgage securitizations. Our conclusion is therefore that the vast majority of the AAA ratings assigned to tranches created from mortgages were reasonable, but in a small minority of the cases they cannot be justified.

I think it’s fair to conclude that the problems of the sub-prime crisis were not with the rating agencies or, to a small degree, with investors who plunked down their money. The problem lay in concentration: the banks took the view that if one is good, two is better … and went the way of all those who fail to diversify sufficiently.

Update: For a review of what participants were thinking at the time, see Making sense of the subprime crisis. For more on subprime default experience, see Subprime! Problems forseeable in 2005?. I will admit, though, that what I’m really waiting for is an accounting of realized losses on subprime paper.

Cassandra's Reward

Sunday, October 5th, 2008

Via Dealbreaker and Alea, a fascinating look at Freddie Mac’s contribution to the housing bubble:

For two years, Mr. Mudd operated without a permanent chief risk officer to guard against unhealthy hazards. When Enrico Dallavecchia was hired for that position in 2006, he told Mr. Mudd that the company should be charging more to handle risky loans.

In the following months to come, Mr. Dallavecchia warned that some markets were becoming overheated and argued that a housing bubble had formed, according to a person with knowledge of the conversations. But many of the warnings were rebuffed.

Mr. Mudd told Mr. Dallavecchia that the market, shareholders and Congress all thought the companies should be taking more risks, not fewer, according to a person who observed the conversation. “Who am I supposed to fight with first?” Mr. Mudd asked.

In the interview, Mr. Mudd said he never made those comments. Mr. Dallavecchia was among those whom Mr. Mudd forced out of the company during a reorganization in August.

Well … who knows who said what to whom when. But I’ll bet that all the internal memoranda are made public with the next few years and will be very interesting.

Another revealing quote from the article is:

“When homes are doubling in price in every six years and incomes are increasing by a mere one percent per year, Fannie’s mission is of paramount importance,” Senator Jack Reed, a Rhode Island Democrat, lectured Mr. Mudd at a Congressional hearing in 2006. “In fact, Fannie and Freddie can do more, a lot more.”

Um … demand destruction is the market’s role. Once a government gets into the business of distorting a market’s price signals, watch out! A recent example of the US government getting it right was leaving oil prices alone … they fell quickly enough when it became clear that US consumers were adjusting their behaviour to use less.


Friday, September 26th, 2008

Reuters reports:

The U.S. Securities and Exchange Commission is ending its program to supervise large independent investment banks now that the five participants have collapsed or reorganized.

… while Dealbreaker handles the stage directions:

SEC officials mount their horses, tip their hats, and ride off into the sunset. Pan back to show village burned to the ground and citizenry slaughtered, voiceover by Wilfred Brimley waxing poetic, “They did what they came to do. Their work here was done.”

The official SEC Press Release states:

The last six months have made it abundantly clear that voluntary regulation does not work. When Congress passed the Gramm-Leach-Bliley Act, it created a significant regulatory gap by failing to give to the SEC or any agency the authority to regulate large investment bank holding companies, like Goldman Sachs, Morgan Stanley, Merrill Lynch, Lehman Brothers, and Bear Stearns.

So let the finger-pointing begin! The SEC Inspector General has released two reports on the matter; the first, titled SEC’s Oversight of Bear Stearns and Related Entitites: Broker-Dealer Risk Assessment Program is a classic of its genre – there wasn’t enough box-ticking, so everything went wrong. Accordingly, the Inspector-General has recommended additional box-ticking.

There is more meat in the second report, titled SEC’s Oversight of Bear Steams and Related Entities: The CSE Program, which, interestingly, has been liberally sprinkled with redactions.

There is a bias in the report which must be borne in mind when formulating policy, stated on page 9 of the PDF as:

Bear Stearns was com liant with the CSE program’s capital and liquidity requirements; however, its collapse raises questions about the adequacy of these requirements;

While I agree that such questions have been raised, they are irrelevant and should be consigned to the trash bin. It should not be the purpose of regulation to ensure that nothing will ever collapse. The proper purpose of regulation in the capital markets should be to ensure that collateral damage in the event of such a collapse is minimized and does not lead to systemic failure.

I will certainly agree that there is evidence that the BSC bankruptcy managed to achieve the potential for collateral damage and contagion, but when examining the apparent failure of regulation to prevent this occurance, it must be borne firmly in mind that regulators should not care a whit whether the firm goes bust, subordinated debt-holders lose money and everybody loses their jobs. Such events are part of business and an attempt to regulate them out of the realm of possibility will ultimately hurt the economy more than it helps.

If, however, it can be shown (or at least persuasively argued … I don’t want to set the bar too high!) that the Treasury guarantee of the assets was absolutely required in order to save the system, THEN we have a failure of regulation which should be examined for potential improvements.

Bear Stearns’ increasing reliance on secured funding indicates that, although it appeared to be compliant with CSE program’s capital requirement, the market did not perceive it to be sufficiently capitalized to justify extensive unsecured lending. In this sense, Bear Stearns was not adequately capitalized.

These facts illustrate that although Bear Stearns was compliant with the CSE program’s ten percent Basel capital requirement, it was not sufficiently capitalized to attract the funding it needed to support its business model. Although the Commission has maintained that liquidity (not capital) problems caused Bear Stearns’ collapse, this audit found that it is entirely possible that Bear Stearns’ capital levels could have contributed to its collapse by making lenders unwilling to provide Bear Stearns the funding it needed.

The fact that Bear Stearns collapsed while it was compliant with the CSE program’s capital requirements raises serious questions about the adequacy of the CSE program’s capital ratio requirements.

Well, no it doesn’t, as I asserted above. The fact that Bear’s collapse due to liquidity issues while it was compliant with capital requirements HAD SYSTEMIC IMPLICATIONS is what raises serious questions about the adequacy of the CSE programme’s capital ratio requirements.

To summarize, as early as November 2006, Bear Steams was implementing a more realistic approach to liquidity planning than contemplated by the CSE programsy liquidity stress test. While this more realistic approach may have helped Bear Steams in the summer of 2007, it was not sufficient to save the firm in March 2008. Bear Steams’ initiative to line up secured funding indicates that the crisis which occurred in March 2008 was not totally unanticipated by Bear Steams, in that Bear Steams had been taking specific steps to avoid such a crisis for more than a year before it occurred.

According to the expert retained by OIG in conjunction with this audit, the need for Basel IIfirms to undertake specific efforts to line up committed secured funding in advance of a stressed environment depends on the extent to which the Basel I1firms can rely on secured lending facilities from the central bank during a liquidity crisis. On the one hand, if it is assumed that secured lending facilities will always be available from the central bank, lining up committed secured lending facilities is not necessary. In this case, a liquidity stress test, which assumes that secured lending facilities will automatically be available is appropriate. On the other hand, if it is assumed that collateralized central bank lending facilities might not be available during a time of market stress, Basel II firms have incentives to line up committed secured lending facilities, in advance, from other sources. In the context of CSE firms which are not banks, the policies of the Federal Reserve towards making collateralized loans to non-banks becomes an important element of their liquidity planning process.

In the heavily redacted section detailing Finding 2; that [the SEC] did not adequately address several significant risks that impact the overall effectiveness of the CSE programme; the report states:

Bear Stearns had a high concentration of mortgage securities. Prior to Bear Stearns becoming a CSE, TM was aware that its concentration of mortgage securities had been steadily increasing.

Yet, notwithstanding [redacted] and warnings in the Basel standards, TM did not make any efforts to limit Bear Steams’ mortgage securities concentration.

Further, a leverage limit is recommended for the future:

Although banking regulators have established a leverage ratio limit, the CSE program has not established a leverage ratio limit. The adoption of leverage limits must be reassessed in light of the circumstances surrounding the Bear Steams’ collapse, especially since some individuals believe that this policy failure directly contributed to the current financial crisis.

I note with amusement that in this official review of risk management and supervision thereof, Wikipedia is cited as a source for a definition. Really! Page 20, note 110. Get with the programme, guys – Wikipedia is not an authoritative source.

Model validation personnel, modelers, and traders all sat together at the same desk.”‘ According to the OIG expert, sitting together at the same desk has the potential advantage of facilitating communication among risk managers and traders but has the potential disadvantage of reducing the independence of the risk management function from the trader function, in both fact and appearance.

This is really bad, a violation of the most basic principles of internal risk control.

In 2006, the expertise of Bear Steams’ risk managers was focused on pricing exotic derivatives and validating derivatives models. At the same time, Bear Steams’ business was becoming increasingly concentrated in mortgage securities, an.area in which its model review still needed much work. The OIG expert concluded that, at this time, the risk managers at Bear Steams did not have the skill sets that best matched Bear Steams’ business model.

And that part’s just bizarre! The concept is, however, endemic in the industry … ‘Hey, Fred! You’re doing Preferred Shares this week!’

Furthermore, the OIG expert believes that meaningful implementation of high grade and high yield mortgage credit spread scenarios requires both a measure of sensitivity of mortgage values to yield spreads as well as a model of how fundamental mortgage credit risk factors make yield spreads fluctuate. These fundamental factors include housing price appreciation, consumer credit scores, patterns of delinquency rates, and potentially other data. These fundamental factors do not seem to have been incorporated into Bear Stearns’ models at the time Bear Stearns became a CSE.

… doesn’t look like they were much good at quant work …

When selling an asset, Tier 1capital is reduced by the amount of losses on the sale, but capital requirements are also reduced by removing the asset from the bank’s portfolio. A bank looking to improve its Basel capital ratios by selling assets therefore has a perverse incentive not to sell assets that have modest capital requirements relative to the markdowns the banks should have taken but has not yet taken. This perverse incentive tends to amplify the tendency for markets to freeze up and become illiquid by reducing trading volume that would othennrise occur as banks sell losing positions into the market. On the one hand, these perverse incentives are mitigated to the extent that capital requirements on such assets are high and valuations are appropriately conservative. For assets that face a 100% capital haircut, for example, the bank gains no improvement in its capital ratios by avoiding taking a markdown, and the bank increases its capital by the proceeds of any asset sales. On the other hand, these perverse incentives are worsened to the extent that supervisors allow banks to avoid marking assets down quickly enough, to avoid taking appropriate valuation adjustments in a timely manner, or to understate assets’ risks.

Similar to what Dealbreaker claimed yesterday.

There is much of interest in the report; but a lot of the juicy stuff has been redacted, presumably because it was provided to the SEC on a confidential basis.

Update, 2008-10-7: Via Dealbreaker and Bloomberg comes some juicy stuff about all the redactions:

An unedited version of the 137-page study posted to Grassley’s Web site Sept. 26 showed that Bear Stearns traders used pricing models for mortgage securities that “rarely mentioned” default risk. A link on the site to the full report wasn’t working today.

The firm lost one a top modeler “precisely when the subprime crisis was beginning to hit” and writedowns were being taken, the full report said. “As a result, mortgage modeling by risk managers floundered for many months,” according to the unedited document, quoting internal SEC memos from April and December 2007. The comments were removed from the edited version publicly released by the SEC.

Trading and Markets unit members saw that Bear Stearns traders dominated less-experienced risk managers, the inspector general reported in sections that were excised from the public report.

“As trading performance remained strong for years in a row, it clearly wasn’t career-enhancing to stand in the way of increasingly powerful trading units demanding more balance sheet and touting their state of the art risk-management models,” said Brad Hintz, an analyst at Sanford C. Bernstein & Co. in New York, and a former chief financial officer at Lehman Brothers Holdings Inc.

In other words, the risk managers were there as part of the standard box-ticking exercise, not because anybody in management really wanted them to do anything. I noted on April 16 one particularly nasty report with respect to a Merrill Lynch CDO offering of a corporate finance guy bullying a trader to make his underwriting go.

Moody's Updates Sub-Prime Loss Estimate

Friday, September 19th, 2008

Moody’s has issued a press release:

According to Moody’s, and as outlined in the Special Report referenced above, lifetime cumulative losses on 2006 vintage subprime first-lien pools are now projected to average 22%, considering pool performance through the July 2008 remittance reports. Projected losses increase progressively with the 2006 quarter of origination, averaging 17% for Q1 2006 and rising to 26% for Q4 2006. This compares to Moody’s previous projections in January, which estimated losses in a range between 14-18%.

This estimate may also be compared with Fitch’s earlier estimate of 21% on 2006 subprime, compared to 10% for 2005 and 26% for 2007 vintage. Fitch’s report has been discussed on PrefBlog.

Canadian Non-Bank ABCP: Appealed, But Court Passes!

Monday, August 18th, 2008

The judgement has been released:

[121] For the foregoing reasons, I would grant leave to appeal from the decision of Justice Campbell, but dismiss the appeal.

This affirms the earlier decision by Mr. Justice Colin Campbell.

The National Post reports:

Yesterday three Alberta oil companies abandoned their opposition to the workout after reaching agreements with ABCP dealers.

… but provides no details.

BIS Quarterly Review Deprecates ABX Benchmark for SubPrime

Tuesday, June 10th, 2008

As reported by the WSJ, the BIS Quarterly Review deprecated the widespread use of the ABX indices when estimating credit losses on sub-prime.

They make three major points regarding pitfalls in using the ABX:

  • Accounting Treatment – many subprime RMBS are held by investors who do not mark-to-market, resulting in a wide gap between reported writedowns and estimated fair value of losses.
  • Market Coverage – the indices only sample the universe … but this is probably not a big deal, the sample is reasonable.
  • Deal-Level coverage – “Similarly, ABX prices may not be representative because each index series covers only part of the capital structure of the 20 deals included in the index … In particular, tranches referenced by the AAA indices are not the most senior pieces in the capital structure, but those with the longest duration (expected average life) – the so-called “last cash flow bonds”.”

The last point is very important and forms the core of their argument.

This information has been available to non-specialists for some time … I could have sworn I mentioned it specifically on PrefBlog at one point, but can’t find the reference … and at any rate I should have emphasized it myself when discussing the fair value estimates. The best tracing to this information I can give is … in my discussion of the Greenlaw paper, I referenced the comments to Econbrowser’s Mortgage Securitization post, in which I referenced Felix Salmon’s How to test the accuracy of the ABX post, which referenced his prior ABX RIP post, which referenced Alea’s ABX Extra piece, which … highlighted the information.

The guts of the BIS argument are given only in the notes:

Incomplete coverage at the deal level further reduces effective market coverage: typical subprime MBS structures have some 15 tranches per deal, of which only five were originally included in the ABX indices. As a result, each series references less than 15% of the underlying deal volume at issuance.

Duration effects at the AAA level are bound to be significant for overall loss estimates as the AAA classes account for the lion’s share of MBS capital structures. Using prices for the newly instituted PENAAA indices, which reference “second to last” AAA bonds, to calculate AAA mark to market losses generates an estimate of $73 billion. This, in turn, translates into an overall valuation loss of $205 billion (ie some 18% below the unadjusted estimate of $250 billion).

I will suggest that even the PENAAA indices will be not very well corellated with actual credit analysis, but these data certainly provide an indication of the value of subordination.

The last review of loss estimates was the discussion of the OECD paper; there is not really enough data in the BIS note to put it on the board as an estimate … but it certainly seems to support the “lowball Bank of England estimate” rather than the “terrifying IMF estimate”!

The main articles – apart from the “Overview” and “Highlights” – in the BIS Review are:

  • International Banking Activity Amidst the Turmoil
  • Managing International Reserves: How Does Diversification Affect Financial Costs?
  • Credit Derivatives and Structured Credit: the Nascent Markets of Asia and the Pacific
  • Asian Banks and the International Interbank Market

Update, 2008-6-11: This post was picked up by iStockAnalyst and attracted a puzzled comment on the Housing Doom blog:

Here’s a technical criticism of the ABX index that was posted yesterday. If you can understand what this guy is complaining about you’re doing better than me.

“BIS Quarterly Review Deprecates ABX Benchmark for SubPrime”, James Hymas, iStockAnalysis, June 10, 2008.

Well, I guess for new readers who have not been assiduously reading my remarks, this post will be a little cryptic!

The gist is: in order to make a sub-prime RMBS with a large AAA component, it must be tranched; for example, the Bear Stearns ABS I use as a model had a total value of USD 395-million, which was divided into seven publicly marketed and three private tranches … payments went first to the USD 314-million senior tranche, then on down the line until the final (public) tranche of USD 4.5-million, initially rated at BBB- and downgraded to B on August 24, 2007 gets paid … if it ever does! I looked at the economics of tranching very early on.

This particular issue is relatively simple, but there are issues with more tranches … as the BIS piece above notes, the average is 15 tranches per deal of which … maybe five? I’m guessing … would be rated AAA.

So you have five AAA tranches that get paid one after the other. Obviously, the first one to be paid is the safest and most likely to meet its committments; the ratings agencies, in their infinite wisdom, determined that tranche #5 was also good enough to warrant an AAA rating. The ten that came after that would be sold to the public with worse ratings and higher yields.

So … the market goes blahooey and all of sudden banks and brokerages, with a need to mark their inventories to market to meet the accounting rules, are stuck with the problem: how to assign a market price to inventory comprised of relatively small issues representing a class of security that simply isn’t trading at all. After discussion with their accountants, they determine that the methodology least likely to get them into trouble is to use the Markit ABX indices as a benchmark. This methodology is also used by third parties (e.g., the OECD, referenced above) to estimate what the total losses for the entire universe of about USD 1.4-trillion might be.

There are a number of problems with this approach. Firstly, the Markit ABX index only rates the worst tranche for each credit rating … the value for the AAA-rated index is based entirely on tranche #5 of our example, even though there are four other tranches rated AAA in this deal, each of which (this is the important bit) are safer than the chosen tranche by definition.

Secondly, the ABX index is based on Credit Default Swaps, a market that is now basically dysfunctional.

Thirdly, we are interesting times; getting out of sub-prime paper is currently a “crowded trade” and the cash market itself is dysfunctional (although it is starting to show signs of life). The market price of the securities does not have a lot to do with the present value of its expected cash flows.

All these factors mean that estimates of sub-prime losses that mark-to-market off the Markit ABX index are (a) highly imprecise, and (b) greatly overstated.

The new PENAAA index referred to above is based on the penultimate tranche in the AAA tranche – tranche #4 in our 15-tranche mini example. A quality spread is quite evident; using the value of this index to estimate market values over the universe results in BIS computing an estimate for losses that is much, much lower than the initial estimate.

Canadian Non-Bank ABCP: Almost Beginning Cash Payments!

Friday, June 6th, 2008

The Globe and Mail reports:

An Ontario judge has approved the plan to restructure $32-billion of asset-backed commercial paper, moving individual and corporate investors closer to recovering troubled investments that have been frozen since last August.

Mr. Justice Colin Campbell of the Superior Court of Ontario issued reasons for his decision to approve a plan that was challenged by a number of individual and corporate investors.

The plan grants a sweeping immunity to every bank, rating agency and other major funds that helped nurture the market. The immunity will shield the ABCP players from future lawsuits related to the investment crisis. Not protected from this immunity are brokerages or dealers that may have fraudulently sold the troubled notes to investors.

It is widely expected that some investors will seek to appeal the judge’s decision, meaning that investors may have to wait at least another month to receive money or new securities that will be issued under the plan.

The Financial Post notes:

The plan calls for the ABCP, which seized up when the credit crunch hit nearly 10 months ago, to be converted to long-term notes.

It will be most interesting to see what disclosures are made on the notes and what price levels become established for them. PrefBlog’s last post in this dreary saga was Almost, but Campbell Procrastinates.

OECD Estimate of Sub-Prime Losses

Thursday, June 5th, 2008

The OECD has published a paper by Adrian Blundell-Wignall, The Subprime Crisis: Size, Deleveraging and Some Policy Options … it was actually published in April, but I missed it … the numbers weren’t scary enough, I suppose, so it was ignored by bloggers and the media.

The abstract reads:

The paper revises our previous USD 300 bn estimate for mortgage related losses to a range of USD 350-420 bn. In doing this the paper explicitly rejects the previous approach based on implied defaults from ABX pricing, because these prices are affected by illiquidity and extreme volatility; they will likely lead to misleading estimates of losses. Instead it builds a proper default model approach and allows for recovery of collateral via house sales over time. The paper separates out the losses due to commercial banks in the US, and goes on to look at the implied deleveraging required to meet capital standards. It could take 6-12 months for banks to offset losses via earnings alone, depending on Fed rate cuts and the dividend policy of banks. Since even more capital than this is required if banks were to expand their balance sheets, the paper looks at possibilities for capital injections from groups like sovereign wealth funds; and it also looks at a novel plan for the use of public money with an RTC-style approach and the issue of zero coupon bonds. Finally the paper looks at the issues of moral hazard, the likely size of the impact in Europe and Asia and non-bank corporate leverage.

The author points out that mark-to-market estimates are more than just a little suspicious:

The ABX estimates are shown in Table 1. The prices for each tranche/vintage are shown in the top section of the table. Thus in the first row, for ABX 06(1), the 14 March price 86 implies that 14% losses are discounted for AAA.5 The weights by vintage and tranche (not shown) are applied and, the weighted expected loss is shown in the bottom row of the table. This number is applied to the stock of US RMBS. Using the September 7 numbers, USD 292 bn is the implied loss (the main basis of the work last year). But as can be seen, over time the implied size of the losses seems to get ever larger. On the 14th of March, a staggering USD 887 bn loss is implied.

A similar picture emerges from our naïve equity market-cap-loss approach in Table 2. Far from the USD 308 bn published in the last FMT, the market cap losses for levered financial institutions most affected by mortgages is now a staggering USD 702 bn, very much showing the same pattern as the ABX approach.

Both approaches are undermined by recent market panic and problems with price discovery. If it is agreed that these are features of recent experience, then it follows that these estimates of losses are way too high.

This estimate of ultimate losses may be compared with

Blundell-Wignall does not give a lot of details regarding his calculation. Essentially, he’s fitting into the formula

Total losses = (total outstanding) x (delinquency rate) x (foreclosures / delinquencies) x (loss given foreclosure)

There’s not a lot of information: I have tried and failed to find details of the parameterization of this equation in either the Bank of England model or the OECD model. The best I can do is state that the BoE assumes loss given foreclosure of 50%, while the OECD varies this in a range of 40%-60%.

Additionally, the BoE examined 1,400-billion in sub-prime, while the OECD is looking at 1,300-billion sub-prime and 1,000-billion “Alt-A, etc.”.