Structured Credit As Portfolio Management Tool

8/11/2019 Structured Credit As Portfolio Management Tool

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Structured Credit As Portfolio Management Tool

The Primary Analyst(s) identified above certify that the views expressed in this report accurately reflect his/her/their personal views about thesubject securities/instruments/issuers, and no part of his/her/their compensation was, is or will be directly or indirectly related to the specific views orrecommendations contained herein.

This report has been prepared in accordance with our conflict management policy. The policy describes our organizational and administrativearrangements for the avoidance, management and disclosure of conflicts of interest. The policy is available at www.morganstanley.com/institutional/research.

Please see additional important disclosures at the end of this report.

Primary Analyst: Peter PolanskyjMorgan Stanley & Co. IncorporatedNew York: [email protected]

2Please see additional important discl osures at the end of this report.

Evolution of the Structured Credit Market

2004Moody's adopts correlationmodels for rating syntheticCDOs

Industry standard Dow JonesCDX index introduced

Fitch introduces correlationmodel

Synthetic CDO-Squareds -regular issuance begins

Synthetic HY index tranches

begin tradingMarket adopts base correlation asa standard

Correlation model on Bloombergintroduced (CDSM)

First pure HY synthetic CDOs

Cash CDO issuance tops $100 Bn

Basel II published -regulatorycapital treatment for CDOs

Delta-adjusted bespoke issuance$300 Bn

Spread

(bp)

0

200

400

600

800

1000

1200

1998First IG cashflowCBO(Travelers Funding)

Russian default causes turmoilin EM CDOs

2002Synthetic Tracers launched

FASB addresses consolidationissues relating to SPEs

HY default rates peak at 10.4%for this cycle

First managed synthetic CDO

Largest managed syntheticCDO ($4.5 billion)

First hedge fund CFO

Regular issuance of HY CBOsends in favor of CLOs

Regular issuance of IG CBOsends in favor of synthetics

2002 the only down year forarbitrage CDO issuance

$280 billion notional creditrisk referenced in syntheticstructures

2000IG cashflowCBOs- regularissuance begins

First arbitrage syntheticCDOs

Structured finance CDOs -regular issuance begins

First trust preferred CDO

Default correlation modelsgain popularity

FAS 133 becomes effective

1996Moody's introduces BinomialExpansion model for CDOratings

First balance sheet CLO

HY Loans -regular use inCDOs

Annual arbitrage CDO issuancetops $10 billion

Investment Grade

High Yield

Emerging Markets

2006Leveraged loan CDSstandards emerge

SFAS 155 introduced,increasing US insurance co.and bank involvement

1997EM CDOs- regular issuance

begins

First synthetic balance sheetCDO

1999Synthetic balance sheet CDOs -regular issuance

First European HY CBO(EuroCredit)


2001First distressed debt CDO

Popular press addresses defaultsin HY CBOs

S&P adopts correlation modelsfor rating synthetic CDOs

1995HY CBOs- regular issuance

begins

First sovereign EM CDO

2003Portfolio liquidation gives

birth to an active cash CDOsecondary market

Synthetic TRACX Indexintroduced (100 names)

Synthetic IG index tranchesbegin trading

First structured credit hedgefunds emerge

$950 billion notional creditreferenced in syntheticstructures

2005Auto sector stress spurs sell-off in index equity tranches

Collins & Aikman bankruptcy 1st industry-widesettlement

Levered super senior products gain popularity

Delta Air Lines and Northwest file for bankruptcy withinminutes of each other

Delphi 1s t significant fallen angel default since 2002, inover 800 S&P rated synthetic CDOs

Hybrid cash/synthetic ABS CDOsgain popularity

High leveraged loan recoveries keep CLO ratings stable

S&P introduces significant changes to ratings model

Forward starting, self managed and CPPI structures emerge

Delta-adjusted bespoke issuance $600 Bn


2004Moody's adopts correlationmodels for rating syntheticCDOs

Industry standard Dow JonesCDX index introduced

Fitch introduces correlationmodel

Synthetic CDO-Squareds -regular issuance begins

Synthetic HY index tranches

begin tradingMarket adopts base correlation asa standard

Correlation model on Bloombergintroduced (CDSM)

First pure HY synthetic CDOs


Basel II published -regulatorycapital treatment for CDOs

Delta-adjusted bespoke issuance$300 Bn

Spread

(bp)

0

200

400

600

800

1000

1200

1998First IG cashflowCBO(Travelers Funding)

Russian default causes turmoilin EM CDOs

2002Synthetic Tracers launched

FASB addresses consolidationissues relating to SPEs

HY default rates peak at 10.4%for this cycle

First managed synthetic CDO

Largest managed syntheticCDO ($4.5 billion)

First hedge fund CFO

Regular issuance of HY CBOsends in favor of CLOs

Regular issuance of IG CBOsends in favor of synthetics

2002 the only down year forarbitrage CDO issuance

$280 billion notional creditrisk referenced in syntheticstructures

2000IG cashflowCBOs- regularissuance begins

First arbitrage syntheticCDOs

Structured finance CDOs -regular issuance begins

First trust preferred CDO

Default correlation modelsgain popularity

FAS 133 becomes effective

1996Moody's introduces BinomialExpansion model for CDOratings

First balance sheet CLO

HY Loans -regular use inCDOs


Investment Grade

High Yield

Emerging Markets

Investment Grade

High Yield

Emerging Markets

Investment GradeInvestment Grade

High YieldHigh Yield

Emerging MarketsEmerging Markets

2006Leveraged loan CDSstandards emerge

SFAS 155 introduced,increasing US insurance co.and bank involvement

1997EM CDOs- regular issuance

begins

First synthetic balance sheetCDO

1999Synthetic balance sheet CDOs -regular issuance

First European HY CBO(EuroCredit)


2001First distressed debt CDO

Popular press addresses defaultsin HY CBOs

S&P adopts correlation modelsfor rating synthetic CDOs

1995HY CBOs- regular issuance

begins

First sovereign EM CDO

2003Portfolio liquidation gives

birth to an active cash CDOsecondary market

Synthetic TRACX Indexintroduced (100 names)

Synthetic IG index tranchesbegin trading

First structured credit hedgefunds emerge

$950 billion notional creditreferenced in syntheticstructures

2005Auto sector stress spurs sell-off in index equity tranches

Collins & Aikman bankruptcy 1st industry-widesettlement

Levered super senior products gain popularity

Delta Air Lines and Northwest file for bankruptcy withinminutes of each other

Delphi 1s t significant fallen angel default since 2002, inover 800 S&P rated synthetic CDOs

Hybrid cash/synthetic ABS CDOsgain popularity

High leveraged loan recoveries keep CLO ratings stable

S&P introduces significant changes to ratings model

Forward starting, self managed and CPPI structures emerge

Delta-adjusted bespoke issuance $600 Bn


Source: Morgan Stanley

Investment Grade

High Yield

Emerging Markets

2007 Investment Symposium


2/28


Jan-07

200730 year CDS gainsmomentum in corporatecredit

1997Long form confirmationdocument, previously tradeterms were individuallynegotiated

Asian crisis increased CDSvolumes

Indonesia debtrescheduling - motivatedworking groups to discussstandardization

First balance sheetsynthetic CDO

Dec-96 Jan-98

1999ISDA Publishes 1999Credit DerivativesDefinitions (firstcomprehensivemarket standard)

Jan-00Jan-99

2001Modified restructuring,motivated by Conseco

Railtrack bankruptcy,dispute over deliverabilityof convertible bonds,established standards

Enron bankruptcy - largevolume reference entityand counterparty

Argentina default

Jan-02Jan-01

2003TRACX indices(100 names) introduced

IBoxx indices introduced

Parmalat default, largereference entity

ISDA 2003 definitionspublished

Jan-04Jan-03

2005ISDA published template forCDS on ABS

Collins & Aikman bankruptcy 1st ISDA-coordinated industry-wide CDS settlement

Delphi bankruptcy 1stsignificant fallen angel defaultsince 2002, large operationaltest for the market

Delta Air Lines and NorthwestAirlines file for bankruptcy onthe same day

Calpine Bankruptcy ISDAproposes solution to deliverableconvertibles debate through avote

Recovery locks gain acceptance

Jan-06Jan-05

0

50

100

150

200

250

300

1998Russia default,showedshortcomingsof long formconfirmation

2002HY trailing default ratepeaks for this credit cycle at10.4%

CDSW pricing model introducedon Bloomberg, increasedtransparency

DTC trade matching increasedliquidity

WorldCom bankruptcy, largevolume reference entity

Obligation acceleration andrepudiation/moratorium droppedas credit events for corporates

CFMA requires CDS to becovered by anti-fraud provisions

Xerox restructuring

Standardized quarterly enddates begin trading

Alan Greenspan praises CDS forspreading credit risk throughoutfinancial system

Synthetic TRACERS index (50names) introduced

2000First arbitrage syntheticCDO

Conseco restructuring

Armstrong default resulted inreference entitydisagreement betweencounterparties

2004CDX index family becomesstandard

Basel II regulatory relief forCDS without restructuring

2006ABX standardizedindices on US sub-primehome equity begintrading

Complex restructuringscreate CDS successionand deliverability issues

ISDA standardizes USLCDS contract

ISDA standardizes CDOCDS contract

LevXLCDS indexlaunches in Europe

CDS basis turnsmeaningfully negative inmost corporate creditmarkets

CPDO products pushCDX and iTraxx indicesmeaningfully tighter

IG

CorporateSpread(bp)

Evolution of the Credit Derivatives Market


How Big Is the Synthetic Structured Credit Market?

Credit Risk (Delta Adjusted)Portfolio StyleSpecified Currency

of NotionalNotional

1,554,440450,2002006

635,19538%28%34%68%32%38%56%340,477265,35675,1212005

338,55324%51%25%63%37%51%43%120,70481,05939,6452004

TotalSenior +

Super SeniorMezzanineEquityStaticManagedEURUSDTotalUnfundedFundedVintage

One of the most technical markets in the world. Understanding the supply/demand structure is

of crucial importance.

Tremendous growth over the past 3 years

Clear themes in capital structure, currency and maturity

Creditflux data based on dealer contributions and likely covers two-thirds of the market. Data

excludes the traded index tranche market.

Source: Morgan Stanley, Creditflux

Structured Credit Market Summary Bespoke Issuance ($ MM)



3/28


And Cash? - Structured Finance/CLOs Dominate 2006 Issuance


In USD million

2007 J an -Feb 2006 2006 2007 J an -Feb 2006 2006 2007 Jan -Feb 2006 2006

High Grade ABS 15,116 7,242 120,293 13,758 7,242 117,832 1,359 - 2,461Mezzanine ABS 16,066 6,403 61,704 16,066 6,038 59,472 - 364 2,232CMBS/REIT Debt 4,171 3,118 31,787 4,171 3,118 30,395 - - 1,232Other SF 5,140 1,325 20,463 3,781 1,295 18,741 1,359 30 1,677Total SF CDOs 40,493 18,088 234,246 37,775 17,694 226,440 2,718 394 7,602

CLOs 16,851 9,485 154,037 14,577 6,849 90,706 2,274 2,636 60,203Middle Market CLOs 16,620 3,424 56,826 1,846 2,467 18,199 14,773 328 37,208Synthetic Corporate Credit CDOs 4,023 3,290 19,167 2,622 402 8,844 1,340 2,694 9,147Trust Preferred CDOs 537 1,754 15,005 537 1,754 14,622 - - 383Other 2,319 6,582 21,421 455 3,518 13,295 506 2,797 6,009

Total 80,842 42,622 500,702 57,812 32,684 372,106 21,611 8,850 120,552

Global CDOs US Europe


Lots of Forms of Credit OutstandingAlways key in t his envi ronment to d iff erent iate among corpor ate, resi dent ial, commerci al creditmarkets and vehicles. Some statistics more problematic than others.

CLO notional outstanding - $0.4 tn$0.5tnUS Levered Loans

US LBOs in 2006 - $0.2tn$0.2tnPrivate Equity Uninvested Capital

RMBS outstanding - $5.5 tn$10 tnUS Residential Mortgage Market

CMBS outstanding - $0.8 tn$500 bn securitized in 2006

Bespoke CDO risk outstanding - $3 tn

HY unsecured collateral no longer packaged

CBOs no longer actively issued/traded

Structured Market Size & CommentUnderlying Market

$20 tnCorporate Credit Derivs

$1 tnSubprime Mortgage Market$3 tnUS Commercial Mortgage Market

$1 tn

$4 tn

$17 tnUS Equities

High Yield Bonds

Investment Grade Bonds

US Corporate Credit

Putting Some Size to the Markets

Source: Morgan Stanley Research



4/28


What Does Bespoke Really Mean?

Investment grade portfolio management

may be at an important crossroads today

Basel II and FASB proposals are very

supportive of taking credit risk in structured

form

Further, large corporate bond portfolios are

in need of tools to implement macro

strategies

So, what does bespoke really mean?

The US credit environment is becoming

more inviting to taking customized

structured credit solutions, taking a pagefrom Europe

Morgan Stanley 2006


Banks and Basel II

Basel II has already had profound

implications on credit investing

Based on ratings approaches, risk

weightings fall dramatically, making

structured credit solutions fairly efficient

from a regulatory capital perspective

We see the impact of this event already on

senior tranche spread and record cash and

synthetic CDO issuance

12%

50%

50%

A

20%

50%

50%

A-

35%

100%

100%

BBB+

60%

100%

100%

BBB

100%

100%

100%

BBB-

10%8%7%

CDO Tranche

(Super Senior X-100%)

50%20%20%CDO Tranche

50%20%20%Corporate Bonds

A+AAAAA

Source: Morgan Stanley, Basel II. Assumes RBA Approach

Basel II Risk Weightings Favor Structured Credit



5/28


Insurance and FASB

FASB guidelines related to changes in

MTM practices may represent a secular

shift in the use of synthetic structured credit

SFAS 155, Accounting for Certain Hybrid

Financial Instruments (2/06)

CLNs issued from an SPE are accounted

for similar to conventional corporate

bonds

No bifurcation of an embedded credit

derivative

To not MTM the underlying credit

derivative, an investor must not consolidate

SPE

100% ownership of QSPE (static or rules

based)

Up to 50% for actively managed

The following information contains a general, summary

discussion of certain select accounting issues. Any suchdiscussion is necessarily generic and may not be

applicable to or complete for any particular investors

specific facts and circumstances. Morgan Stanley is not

offering and does not purport to offer accounting advice

and this information should not and cannot be relied upon

as such. Morgan Stanley has prepared this information

based on our understanding of the issues following review

of materials prepared by third party accounting experts.

The positions of such third party experts may be reasoned

and the views of other third party experts may differ from

those summarized herein. Potential investors are urged to

consult their own accounting advisors before making any

investment decisions regarding any transaction.


$0

$5,000

$10,000

$15,000

$20,000

$25,000

$30,000

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Global Corporate CreditDerivatives = 3.6x Cash Markets

Total Corporate Credit Notional Outstanding ($b)

Source: BIS, ISDA

Global Corporate Cash Credit Global CDS Market



6/28


$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

$70,000

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

USD Rates

Derivatives = 10.7x Cash Markets

Total US Government Debt Notional Outstanding ($b)

Source: BIS, ISDA

US Government Debt Securities USD Interest Rate Swap Notional

Innovation As a Driver Of Markets



7/28


Innovation As a Driver of Markets

2005 Levered Super Senior

2006/7 Equity in Fashion; Watch the Styles

CPDO Friend or Foe?

Innovation in ABS CDOs

ABX TABX

2007 Morgan Stanley


Levered Super Senior Showed The Potential in 2005

Most important 2005 theme is the interplay

of equity and super senior, as the middle

has been much more stable

Supersenior pricing on investment grade

pools widened by 8-10 bp from starting

levels in the single to low double digit

range

Levered super senior products were a big

part of why spreads came rallying back in

late 2005

Implied Super Senior PricingFollows Actual Pricing

Implied 30-100% Spread (bp)

-10

-8

-6

-4

-2

0

2

4

6

8

Oct-04 Jan-05 Mar-05 Jun-05 Aug-05 Nov-05 Jan-06

5yr DJ CDX 10yr DJ CDX

CDX 3-4 Roll CDX 4-5 Roll




8/28


0

5

10

15

20

25

30

Oct-

03

Apr-

04

Oct-

04

Apr-

05

Oct-

05

Mar-

06

Sep-

06

Mar-

07

Equity Products Reiterated The Potential in 2006

On-the-Run IG CDX 5-Year 0-3% Correlation


Despite much higher credit volatility, there

have been strong equity tranche flows

Non-traditional equity products have been

the main drivers

POs are very popular and are good ways

to play default risk when timing is

uncertain

IOs are better suited for a new-term low

default environment

Rated equity structures are based on the

excess spread framework and have the

characteristic of initial ratings being

sensitive to market levels

Spring 2005 -Repricing withAuto Stress

Spring 2006 -Equity POsGain Popularity


Rated Equity Rationale

How Does Excess Spread Cover Lossesfrom Default?

Source: Morgan Stanley, Moodys. Note: 5-year excess spreadassumes that the notional is written down evenly over five years basedon Moodys 5-year losses.

Rating agency perspective

Excess spread provides enough coverage

for losses over time to warrant an

investment grade rating

Wider all-running premiums on equity

can result in higher ratings at initiation,

all else being equal

Market perspective

Rated equity provides absolute price

support for equity risk

Agencies do not assign a big weight for

JTD in IG; clearly this is a risk factor

45.3%5-year Excess Spread

Baa Portfolio

38.3%5 Year Excess Spread

10.0%Annual Excess Spread

38.87%Loss as % of 0-3% Tranche

1.17%Moody's 5-year Loss

10.0%Annual Excess Spread

15.80%Loss as % of 0-3% Tranche

0.47%Moody's 5-year Loss

IG Portfolio



9/28


CPDO Friend or Foe?

CPDOs have seized a disproportionate

amount of investor mindshare

There is a perception problem, since the

technology is nearly 100% associated

with just one example of its application

We have some issues with the original

index product, based on rebalancing risk

within the indices and mean-reversion

assumptions

We find other strategies much more

appealing, including managed structuresand tranches

Investment Strategy Indices Managed Portfolios Curves Strategies Long/Short Strategies Tranches

Leverage Process Trade NAV Portfolio PV Limits & Cash In Levels

Risk Management Gap Risk Cash Out Trigger

Fees

Credit Linked Note Stable Coupons/Principal Ratings


A CPDO Problem Rebalancing Risk

1.1 bp0.15 bp0.04 bpCitigroupBIGCredit

4.5 bp0.71 bp-0.03 bpBBB

-1.2 bp-0.22 bp0.03 bpA

-2.0 bp-0.34 bp0.00 bpAAA/A A

Avg Si x-Mont hSpread

WideningDue to

Rebalancing

Avg Mo nth lySpread

ChangeDue to

Rebalancing

Avg Mo nth lySpread

Change ofIndices

CorporateBondSector

Measuring Index Rebalancing Risk (bp)

Source: Morgan Stanley, Yield Book.Note: Based on Citigroup BIG Credit Index monthly data starting in

December 1994. Spread widening is based on OAS and isdue to rebalancing imputed from monthly excess returns ofthe indices.

Average One-Year Rati ng Migrat ions,1970-2006 (%)

Source: Moodys

4.480.180.020.220.804.3984.724.930.210.05Baa

3.700.020.000.020.100.514.9588.102.550.06A

3.930.010.000.000.020.060.287.0487.840.83Aa

2.990.000.000.000.000.020.000.677.5088.82Aaa

WRDefaultCa-CCaaBBaBaaAAaAaaCohortRating

End of Period Rating



10/28


CPDO Roll and MTM Risk

0%

20%

40%

60%

80%

100%

0% 2% 4% 6% 8%

0

2

4

6

8

10

Cash-in ProbabilityAverage Time to Cash-in

Impact of Rebalancing Risk on Performance

Cash-in Probabil it y T ime to Cash- in (years)

Cash-in Probability Recovery

Rebalancing impact (% of spreads)

0%

20%

40%

60%

80%

100%

0% 2% 4% 6% 8%

60%

70%

80%

90%

100%



Cash-in ProbabilityRecovery

CPDO MTM Risk: Distribution of

Worst NAVs

95-100

>70 75-80

85-90 90-95

80-8570-75

10%

12%

17%

14%

18%

15%

20%

22%

11%

22%

14%

6%7%

1% 3%10%

24%

49%

2%5%6%

10%11%

16%

21%

23%

8%

17%

2%

30%

25%

1%

29%

18%

0% 2% 4% 6% 8%


Distribution



CPDO Bullish or Bearish Trade?

Single-name products perform best in

modestly bearish environments

Curve strategies based on steepeners

are interesting given the theme that

forwards do not get realized but timing

is not great

CPDO on senior tranches is very

interesting but the agencies are not

ready to rate yet

There is a natural analogy with LSS91%5.1596.3%25bp

91%5.2797.8%29bp

98%6.0699.9%50bp

-6.38100.0%60bp

-6.58100.0%70bp

-6.81100.0%80bp

Recovery

Averag e Cash-in Period

(Years)Probabilityof Cash-in

MeanSpreadLevel

Modestly Wider Spread EnvironmentsFavor CPDOs




11/28


Some Recent Innovations in ABS CDOs

Interest Diversion Tests (BBB Turbo)

Typically paid after a coupon to the equity. Interest proceeds that would go to the equity are used to pay down

the balance of the BBB tranche. This shortens the WAL of the tranche and provides additional cashflows early

in the deals life

Pro-rata paydown of the principal waterfall for mezzanine deals

First introduced in high grade deals, a pro-rata paydown allows all classes of rated notes to be paid down in

proportion to their outstanding balances provided there has never been a breach of a coverage test and a certain

portion of the collateral balance is outstanding. This prevents the cost of funds from increasing as the deal

delevers and so boost the equity returns, and also shortens the WAL of mezzanine tranches

Synthetic Assets

Synthetic ABS assets have become more widespread as the market has standardized and the ISDA ABS

synthetic confirm was released in June 2005. This allows the manager to select from a wider range of assets than

the current new issue market

Hybrid Structures

Hybrid structures allow collateral to be sourced in cash or synthetic form


ABX and TABX Whats in it?

ABX Based on 20 underlying subprime home equity ABS transactions.

Indices with ratings AAA, AA, A, BBB, and BBB- are created to

reference the difference tranches in each of these 20 transactions. New

series of the index are created every six months; so far three series have

traded: ABX 06-1, 06-2 and 07-1

Recent volatility has been almost entirely confined to the BBB and BBB-

classes

Tranched ABX (TABX) launched on February 14, 2007. Two sets of

tranches will trade, referencing BBB and BBB-. Each of these, in turn, will

reference the 40 securities resulting in combining ABX 06-2 and ABX 07-1

While tranche trading has become a highly liquid and commoditized product

in corporate credit, TABX is a long way away from this status.

Concepts of Delta and Implied Correlation fraught with complications



12/28


But More Diversity in ABS CDOs Ratings, Vintage, etc

1%

4%

1%

4%

5%

17%

14%

11%

8%

4%

3%

6%

26%

4%

17%

17%

80%

65%

35%

37%

15%

11%

0%NA

1%B and lower

0%BB-

Ratings Compositi on of Select 2006 Mezzanine ABS CDOs

2%BB

4%BB+

37%BBB-

33%BBB

14%BBB+

5%A

3%AA

1%AAA

Std DevMaximumAverageRating

Recall t hat ABX/TABX is either 100% BBB-, or 100% BBB and 2006 Collateral

Source: Morgan Stanley, Intex

Structured Credit Applications Secured andUnsecured Corporate Credit



13/28


Who Puts the L in LBOs?

Much of the L in LBOs is

furnished by leveraged loan market

CLO market has become the

primary support mechanism for

leveraged loans

Both US and European CLO

portfolios have significant and

growing exposure to LBOs

Risk implications of LBO exposure

vary significantly across CLO

tranches

What if Atlas shrugs?Inverted Investment Pyramid

$1.1 Trilli on High Yield Market

$480Bn L evered Loan Market

$125Bn Private Equity

Uninvested

Capital

$30-35Bn

~$250Bn CLO Market

CLO, Mezz & Equity


Private Equity Hunting Grounds

AA

A

BBB

BBB

BBBBBB

BB

BB

BB

BBB B

BCCC

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2003 2004 2005 2006

BBBs Increasingly the LBO Hunting Ground

Top 20 LBO Deals

Note: Looks at the top 20 LBO deals each year as measured by total invested capital, and takes the S&P rating before thedeal was announced.

Source: Morgan Stanley, FactSet

Cheaper valuation mu ltipl es and PE consor tium deals keep BBBs a target



14/28


The Top-Heaviness Problem

0

5,000

10,000

15,000

20,000

25,000

30,000

Mar-03

Jun-03

Sep-0

3

Dec-0

3

Mar-04

Jun-04

Sep-0

4

Dec-0

4

Mar-05

Jun-05

Sep-0

5

Dec-0

5

Mar-06

Jun-06

Sep-0

6

Dec-0

6

3.0

3.5

4.0

4.5

5.0

5.5

6.0

Source: Morgan Stanley Source: Morgan Stanley, S&P LCD

Private Issuance Volume Leverage

Other, 6%

Senior Debt,59%

FY 2003 1H06

Sub Debt,17%

Senior Debt,37%Equity,

39%

Other, 1%

SubDebt,7%

Equity,33%

Volume($MM)

Leverage(x)

All th ings being equal , recover ies wi ll be lower in the next defaul t cycle

More L in LBOs Less Pie for Subordinated Bondholders


Endless CLO Bid?


2006 global CLO issuance amounted to

$154 billion, more than two times entire

2005 issuance

Continued strong ratings performance

142 upgrades and 25 downgrades over the

last 32 months. Only two downgrades in

European CLOs. Bulk of the ratings

unchanged

Loan recoveries remain high even as

corporate defaults rise

Basel II regulatory capital regime favors

CLOs

0

20

40

60

80

100

120

140

160

180

2000 2001 2002 2003 2004 2005 2006 2007

YTD

USD Euro Other

Growth in Global CLO Issuance



15/28


Loan CDS Just in Time?

SPL (Spread per Unit of Leverage ) is a

Morgan Stanley measure akin to a new

issue P/E for credit products

While leveraged loans may be more

attractive than high yield bonds given

valuations, absolute valuations have come a

long way

Additionally, LCDS premiums optically

trade well inside leveraged loan spreads

This stands in stark contrast to the early

days of the unsecured bond and ABS CDS

markets in which premiums were

significantly wider than their cashcounterparts

0

50

100

150

200

250

Dec-98 Nov-00 Sep-02 Jul-04 May-06

Source: Morgan Stanley, S&P LCD

Leveraged Loan Market SPL

Average: 111Max: 206Min: 52

Monthly Loan SPL


Hedging Isnt Just for Gardeners

Curve flatteners using indic es or singlenames. Flatteners are tough trades from acarry/rolldown perspective today, but they arecheap default hedges, compared to owningoutright protection.

True forward starting tranches. Tranchesthat forward start with a guaranteed amountof subordination are trades that perform wellwhen there are near-term defaults, but arelong credit risk trades.

Variable cost struct ures. Motivated byBasel II but with broader applications, there

are many zero-cost type protectionsolutions, where protection premiums startout very low and rise quickly with defaults.Unlike other strategies, variable coststructures benefit from defaults occurringlater in the cycle.

Junior m ezzanine protection in unsecuredHY. We feel that when the credit cycle turns,unsecured high yield will be the first shoe todrop, and the technicals support this trade aswell, given a lack of strong structured creditflow from the long side.

Principal protected hedging s trategies. Forinvestors who are not able to hold protectionoutright, principal protected strategies wherezero-coupon risk-free assets are mixed withall-upfront positions in tranche protection canbe combined to create zero-coupon principalprotection that has upside if losses aretriggered in the tranche.

2nd-to-Default Baskets on financials. We

focus on financials, where 2nd-to-defaultexposure appears to be a lower costalternative to hedge the industrys inherentsystemic characteristics.

OTM payer options in indices . Whileimplied volatility has moved significantlyhigher, options on the indices provide astrategy not subject to many of the technicalsthat influence tranche pricing.

Hedging Default Risk Hedging Systemic Risk



16/28


The Case For Hedging Loan Exposures

Sub-prime housing and concomitant fears of the credit cycle turning are

beginning to be reflected in re-pricing of risk premia in corporate credit

markets

Wide ranging interest investors with exposure to loans through CLO

tranches, funds with loan exposures through private equity sponsored

transactions financed through leveraged loans

Leveraged loans have furnished the L in LBOs, and CLO portfolios are the

primary support mechanisms for leveraged loans

LBO capital structures are loan-heavy. If the next set of defaults were to

come from LBO names, loan recoveries can be significantly lower than

historical experience

Exploding covenant-lite volumes do not bode well for loan recoveries

Substantial overlap of obligors and sectors across CLO portfolios


CLO Exposure to LBOs and Covenant-Lite Loans

Distribution of LBO Exposure in 2006CLO Portfolios

0%

5%

10%

15%

20%

25%

30%

35%

5.0%-

7.5%

7.5%-

10.0%

10.0%-

12.5%

12.5%-

15.0%

15.0%-

17.5%

17.5%+

Distribution of Covenant-Lite Loansin 2006 CLO Portfolios

Source: Morgan Stanley Research

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

0%-2% 2%-4% 4%-6% 6%-8% 8%-10%

10%+



17/28


CDS on CLOs: A New Arrow in a Hedgers Quiver

The broad chassis of ABS CDS also applies to cash CLOs (specific reference

obligation, amortization of notional, PAUG mechanics) but there are a few

key differences

A Better Fit for Hedging Loans:

Significant overlap of obligors across CLO portfolios

CLOs have sizeable second lien and unsecured bond buckets

PIK-ability of mezzanine tranches is helpful

Callability of CLOs. Protection when needed

At the moment, scale of transactions is a constraint.

What Is Correlation Trading CorporatesVersus ABS



18/28


Correlation and Minefields

LowCorrelation

HighCorrelation


Correlation Intuition

Senior Tranches Subordinate Tranches

0

100

200

300

400

0% 20% 40% 60% 80% 100%

Correlation measures how risk is

distributed among tranches

Subordinate tranches

Spread decreases as correlation rises

Senior tranches

Spread increases as correlation rises


Fundamental Correlation Relationships

bp



19/28


Correlation Intuition Large Baskets

Each tranche resides somewhere on a

correlation sensitivity spectrum, ranging

from very long (3-7%) to very short (15-

30%)

For a given tranche, the level of correlation

sensitivity changes

When correlation changes

When spreads change

Spread (bp)

10% 20% 30% 40% 50% 60% 70% 80% 90%

3-7% 10-15% 15-30%7-10%

Correlation


Sensitivity of Four Tranches of DowJones CDX NA IG


Hidden Meaning of Default Correlation in Credit Markets

0.9x0.7x1.5x1.0x1.1x0.1x0.6xCoefficientof Variance*

Moody'sA & Baa

Moody'sBaa

Moody'sA

1000Credits 20%Correlation

50Credits 20%

Correlation



We have demonstrated that correlation affects the relationship between volatility and

portfolio size

We compare results from a 50-name and 1000-name portfolio with real world default

experience (using Moodys five year cumulative default statistics)

The volatility of expected losses for large portfolios is much greater for correlated

portfolios this is broadly consistent with real world default experience

Source: Morgan Stanley* Standard deviation divided by mean

Volatilit y of Expected Losses In the Models and in the Real World



20/28


Correlation Impact on Portfolio Loss Distribution

When the names in a portfolio are

correlated, the expected portfolio loss

distribution is less concentrated in any one

single loss bucket

A portfolio that consists of correlated

names also has a fatter right tail

Probability

0%

10%

20%

30%

40%

50%

60%

0-2%

2-4%

4-6%

6-8%

8-10%

10-12%

12-14%

14-16%

16-18%

18-20%

20-22%

Losses

Independent & Identical Independent Correlated


Correlation Creates Portfolio L ossDistributions w ith Fatter Tails


Summary of Greeks

Change in tranche value due to the passage of timeTheta ()

Change in tranche value due to changes in default correlationRho ()

Tranche price sensitivity of a delta-neutral position to jump-to-default risk or changes inspread distribution of the underlying portfolio. It represents a form of convexity to movesin a single credit while all others remain constant (I = Idiosyncratic risk)

I-Gamma (i-)

Tranche price sensitivity of a delta-neutral position to parallel shifts in spreads ofunderlying names. It represents a form of convexity (M = Market)

M-Gamma (m-)

Tranche price sensitivity to changes in underlying portfolio spreads, measured as a ratioof tranche PV01 to index PV01 (PV10% is also used sometimes)

Delta ()

What does it measure?Greek




21/28


Delta or Sensitivity to Spread Changes

As spreads widen, a short protection position in

any of the tranches would experience a negative

mark-to-market

For small spread movements, the price impact can

be estimated using tranche delta (PV01 or

PV10%)

Tranches with higher deltas would move more

than tranches with lower deltas; tranches with

deltas less than 1x would move less than the index

(and vice versa)

Broadly speaking, junior tranches have higher

deltas than senior tranches due to higher default

risk, assuming both are quoted on a running

premium basis

For bigger moves in spreads, delta-basedcalculations are only approximations, as tranche

convexity becomes more meaningful

-30%

-20%

-10%

0%

10%

20%

30%

50% 75% 100% 125% 150% 175% 200%

Spread Change Factor

P&L(%)

0-3% 3-7% 7-10%

10-15% 15-30% 0-100%


Spread Sensitivity


I-Gamma or Sensitivity to Spread Distribution Changes

-0.20%

-0.15%

-0.10%

-0.05%

0.00%

0.05%

0-3% 3-7% 7-10% 10-15% 15-30%

AIG+16bps

MMC+240bps

The effect of changes in the distribution of the underlying spreads, especially when the overall portfolio average

remains unchanged, is subtle and worth exploring.

Tight trading names moving somewhat wider generally impact senior tranches, while wide or even average credits

moving significantly wider impact junior mezzanine and first-loss tranches, depending on the size of the move.

For example, in 2004, a 16 bp move in a tight trading name (AIG) increased risk in 15-30% type tranches, while

widening of Marsh & McLennan from 30 to over 250 bp shifted the risk from 15-30% type tranches to 0-3% tranches.


Tranche Pricing Impact:Two Opposite Examples

Insurance Moves to the Right, ImpactingBoth Senior and Subordinate TranchesNumber of Credits

0

5

10

15

20

25

30

0-

10

10-

20

20-

30

30-

40

40-

50

50-

60

60-

70

70-

80

80-

90

90-

100

100-

110

110-

120

120-

130

130-

140

140-

150

150-

160

160-

170

170-

180

180-

190

190-

200

Spread

15-30%7-15%3-7%0-3%



22/28


Tranche Convexity or M-Gamma

-0.8%

-0.6%

-0.4%

-0.2%

0.0%

0.2%

0.4%

0.6%

50% 75% 100% 125% 150% 175% 200%


P&L(%)

0-3% 3-7% 7-10%

10-15% 15-30%

-2%

-1%

0%

1%

2%

3%

4%

5%

50% 75% 100% 125% 150% 175% 200%


P&L(%)

0-3% 3-7% 7-10%

10-15% 15-30%


The impact of w ide spr ead moves is measured by M-Gamma, that is PV100 or 100*PV01

Delta neutral positions on in-the-money tranches are positively convex, while such positions onout-of-the-money tranches are typically negatively convex (from the perspective of the protectionseller)

5 Yr IG Tranche Convexity(Delta Neutral)

10 Yr IG Tranche Convexity(Delta Neutral)


Jump to Default Sensitivity Differs by Investor Type

-14.0%

-12.0%

-10.0%

-8.0%

-6.0%

-4.0%

-2.0%

0.0%

0-3

%5

Yr

IG

3-7

%5

Yr

IG

7-1

0%

5Yr

IG

10-1

5%

5Yr

IG

15-3

0%

5Yr

IG

Index

5Yr

IG

0-3

%1

0Yr

IG

3-7

%1

0Yr

IG

7-1

0%

10Yr

IG

10-1

5%

10Yr

IG

15-3

0%

10Yr

IG

Index

10Yr

IG

0-1

0%

5Yr

HY

10-1

5%

5Yr

HY

15-2

5%

5Yr

HY

25-3

5%

5Yr

HY

35-1

00%

5Yr

HY

Index

5Yr

HY

-8%

-7%

-6%

-5%

-4%

-3%

-2%

-1%

0%

1%

2%

0-3%

5YrIG

3-7%

5YrIG

7-10%

5YrIG

10-15%

5YrIG

15-30%

5YrIG

0-3%

10YrIG

3-7%

10YrIG

7-10%

10YrIG

10-15%

10YrIG

15-30%

10YrIG

0-10%

5YrHY

10-15%

5YrHY

15-25%

5YrHY

25-35%

5YrHY

35-100%

5YrHY

We divide the market into two broad camps

Community 1: Levered investors with long/short strategies and exposure to equity/junior

mezzanine type tranches

Community 2: Other institutional investors (banks, insurance, money managers) who are more

ratings-sensitive, higher up in the capital structure


Loss Due to 1 Default (% of Notional) Delta Neutral P/L Due to 1 Default (% of Notional)



23/28


The Unwind Risk Three Triggers

20062005

Avg Notches

for Downgrade

As a % of Rated

Universe*

Avg Notches

for Downgrade

As a % of

Rated Universe*

6.8%

7.7%

Downgrades

58

87

Upgrades

2.3%

8.2%

Upgrades

1.59

1.88

159

70

Upgrades

4.5%

6.6%

Upgrades

137

67

Downgrades Downgrades

S&P

Moody's

Downgrades

1.51826.3%

1.392385.3%

Synthetic CDO Rating Act ions

A significant move wider in spreads, which if combined with equity correlation moving lowercould force the hand of many. A modest move wider is actually supportive of todays market

Significant downgrade activity at the tranche level, particularly AAAs and AAs

Jump to defaults, 2001/2002 style. Sudden shifts are not priced in

Our base case is for the structured credit bid at the rated tranche level to continue, but warning

flags about the risks have been raised

*2005 numbers calculated as a percentage of the rated tranches outstanding as of 1/1/2005. 2006 numberscalculated as a percentage of the rated tranches outstanding as of 1/1/2005 for Moodys and 1/1/2006 for S&P.Source: Morgan Stanley, S&P, Moodys.

Ratings Activity


Thinking About Zero Correlation

Low levels of implied correlation can be

interpreted as indicating an environment

in which defaults are driven more by

idiosyncratic events than by a

recessionary environment

The markets interpretation of the future

should be most evident in mezzanine

tranches

Based on this risk-neutral framework, 7-

10% in 7 years and 10-15% in 10 years

can go tighter

5 year 3-7% has traded near their zero

correlation level recently

Source: Morgan StanleyNote: 5-Year CDX 6 tranches.

bp

0

50

100

150

200

250

300

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Correlation

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

bp3-7% (LA) 7-10% (LA) 0-3% (RA)

0% Correlation Equals 0bp Spread Level

0% Correlation Above0bp Spread Level

What Happens When Correlation Goes to Zero?



24/28


DAL + NWAC = Correlation Without a Model

The 2000-2001 spike in default rates was

driven by both industry specific events and

unrelated bankruptcies across multiple

industries

The sizeable telecom buildup and bust was

a noteworthy industry specific event that

increased default rates

Other unrelated bankruptcies, driven by the

prevalence of fraud, resulted in defaults

across industries

The Delta and Northwest bankruptcy was a

combination of an industry specific event

and a broader cross-sector dynamic; the

ability to fund pensions and other future

labor costs

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

1970

1973

1976

1979

1982

1985

1988

1991

1994

1997

2000

Cohort


Moody's 5 Year Cumulative Default Rate IG Universe


Pensions and Labor Costs Link Industries

Issues such as pension and labor costs that

have plagued the airline industry may

spread to other sectors

Similar issues could prove to be a driver in

determining default correlation across

sectors

This list highlights companies where

significant potential exists for a high

realized default correlation

It must be noted that the extent to which

pension and healthcare issues are addressed

through legislation will not reduce the

correlation these companies will experience

their fates are tied regardless of

exogenous risks24%MiningALAlcan Inc29%Metal Fabricate/HardwareTKRTimken Co22%ChemicalsTRATerra Industries Inc22%Auto Parts & EquipmentTRWTRW Automotive Holdings Corp22%ChemicalsHPCHercules Inc25%Auto Parts & EquipmentDCNDana Corp27%ChemicalsPOLPolyOne Corp29%Forest Products & PaperBOWBowater Inc32%Auto Parts & EquipmentTENTenneco Automotive Inc33%Forest Products & PaperABYAbitibi-Consolidated Inc

33%Forest Products & PaperSSCCSmurfit-Stone Container Corp34%Auto ManufacturersNAVNavistar International Corp36%ComputersUISUnisys Corp40%Auto Parts & EquipmentARMArvinMeritor Inc43%Auto ManufacturersGMGeneral Motors Corp62%Oil & GasAENAustral Pacific Energy Ltd68%Auto ManufacturersFFord Motor Co73%Auto Parts & EquipmentVCVisteon Corp81%Auto Parts & EquipmentDRRADura Automotive Systems Inc

102%Auto Parts & EquipmentHAYZHayes Lemmerz Intl Inc112%Auto Parts & EquipmentGTGoodyear Tire & Rubber Co145%AirlinesAMRAMR Corp147%Iron/SteelAKSAK Steel Holding Corp215%AirlinesCALContinental Airlines Inc256%Auto Parts & EquipmentDPHDelphi Corp266%Auto Parts & EquipmentXIDEExide Technologies875%AirlinesNWACNorthwest Airlines Corp1

1235%AirlinesDALDelta Air Lines Inc1

Funding Gap/Mkt CapIndustry GroupTickerIssuer

Source: Morgan Stanley(1) Market Cap based on the average of the 6 months prior to the bankruptcy filing.

Not Only One Sector Unfunded PensionLiabilities Relative to Equity MarketCapitalization



25/28


Visualizing Real-World Correlation

Recent moves in implied correlation seemcounterintuitive

The contradiction can be understood bylooking at 2 worlds

World A likelihood of 100 defaults areequally related to one another

World B the default propensity of threecompanies are highly correlated to eachother but not to the rest

The average correlation fails to acknowledgethat many of the names have differentrelationships than this average indicator

Therefore, while one may see a lowerimplied correlation, it could be a scenario ofhigh correlation for a small subset ofcompanies

50%50%10%10%10%100

50%50%50%10%10%10%4

10%10%10%90%90%3

10%10%10%90%90%2

48%10%10%10%90%90%1

Aver age10054321Credit

WORLD B

50%50%50%50%50%100

50%50%50%50%50%5

50%50%50%50%50%4

50%50%50%50%50%3

50%50%50%50%50%2

50%50%50%50%50%50%1

Aver age10054321Credit

WORLD A


Correlation Details Matter


ABX and TABX Whats in It?

ABX Based on 20 underlying subprime homeequity ABS transactions. Indices with ratingsAAA, AA, A, BBB, and BBB- are created toreference the difference tranches in each ofthese 20 transactions. New series of the indexare created every six months; so far threeseries have traded: ABX 06-1, 06-2 and 07-1

Recent volatility has been mostly confined tothe BBB and BBB- classes

Tranched ABX (TABX) launched on February14, 2007. Two sets of tranches will trade,referencing BBB and BBB-. Each of these, inturn, will reference the 40 securities resulting incombining ABX 06-2 and ABX 07-1

While tranche trading has become a highlyliquid and commoditized product in corporatecredit, TABX is a long way away from thisstatus

40%-100% Tranche

25%-40% Tranche

15%-25% Tranche

10%-15% Tranche

5%-10% Tranche

0%-5% Tranche

ABX.HE BBB- Indices

60% Amortization on Underlying Indices

10% Writedown on Underlying Indices

Illustrative Flow ABX.HE BBB- Indices




26/28


65

70

75

80

85

90

95

100

Jul-06 Sep-06 Oct-06 Dec-06 Feb-07

ABX HE Indices Have Fallen Sharply

ABX 06-1 ABX 06-2 ABX 07-1

Sell-off has been dramatic, but traded volumes remain li ght.

Different technicals relative to single-name ABS CDS market.

$ Price of ABX HE BBB- Indices

Source: Mark-it


TABX Early Experience


Much of the trading activity has been in

the 40-100% tranches

Concepts of delta and implied

correlation fraught with complications

and significantly unlike corporate

investment grade index tranches

Implied losses from underlying spreads

suggest that with the possible

exception of the two senior tranches,

rest are deeply in-the-money

At current spread levels, re-tranching

of the 40-100% tranche ((tranche-lets)offers an interesting correlation

market opportunity

TABX (BBB-) Price History (Feb 14 Mar 1)

30

40

50

60

70

80

90

100

2/14/200

7

2/15/200

7

2/16/200

7

2/17/200

7

2/18/200

7

2/19/200

7

2/20

/200

7

2/21

/200

7

2/22

/200

7

2/23

/200

7

2/24

/200

7

2/25

/200

7

2/26

/200

7

2/27

/200

7

2/28

/200

7

3/1/20

07

40-100%

5-10%

15-25%

0-5%10-15%

25-40%



27/28


Disclaimer

Credit Products Rating Distribution Table(as of February 28, 2007)

Rating Count

o

Total Count

o

Total IBC

o a ng

Category

Overweight 121 38% 69 38% 57%

Equal-weight 134 42% 77 42% 57%

Underweight 64 20% 38 21% 59%

Total 319 184

Equal-weight (E) Over the next 6 months, the fixed income instruments total return is expected to be in line withthe average total return of the relevant benchmark, as described in this report, on a risk adjusted basis.

Underweight (U) Over the next 6 months, the fixed income instruments total return is expected to be below theaverage total return of the relevant benchmark, as described in this report, on a risk adjusted basis.

More volatile (V) The analyst anticipates that this fixed income instrument is likely to experience significant priceor spread volatility in the short term.

Coverage Universe Investment Banking Clients (IBC)

Coverage includes all companies that we currently rate. Investment Banking

Clients are companies from whom Morgan Stanley or an affiliate received

investment banking compensation in the last 12 months.

Analyst Ratings Definitions

Overweight (O)Over the next 6 months, the fixed income instruments total return is expected to exceed theaverage total return of the relevant benchmark, as described in this report, on a risk adjusted basis.


DisclaimerImportant Disclosures on Subject Companies

The information and opinions in this report were prepared by Morgan Stanley & Co. Incorporated and/or one or more of its affiliates (collectively, Morgan Stanley) and the researchanalyst(s) named on page one of this report.

Morgan Stanley policy prohibits research analysts from investingin securities/instruments in their MSCI sub industry. Analysts may nevertheless own such securities/instruments to theextent acquired under a prior policy or in a merger, fund distribution or other involuntary acquisition.

Morgan Stanley is involved in many businesses that may relate t o companies or instruments mentioned in this report. These businesses include market making, providing liquidity andspecialized trading, risk arbitrage and other proprietary trading, fund management, investment services and investment banking. Morgan Stanley trades as principal in thesecurities/instruments (or related derivatives) that are the subject of this report. Morgan Stanley may have a position in the debt of the Company or instruments discussed in this report.

Other Important Disclosures

The securities/instruments discussed in this report may not be suitable for all investors. This report has been prepared and issued by Morgan Stanley primarily for distribution to marketprofessionals and institutional investor clients. Recipients whoare not market professionals or institutional investor clients of Morgan Stanley should seek independent financial advice priorto making any investment decision based on this report or for any necessary explanation of its contents. This report does not provide individually tailored investment advice. It has beenprepared without regard to t he individual financial circumstances and objectives of persons who receive it. Morgan Stanley recommends that investors independently evaluate particularinvestments and strategies, and encourages investors to seek the advice of a financial advisor. The appropriateness of a particular investment or strategy will depend on an investorsindividual circumstances and objectives. You should consider this report as only a single factor in making an investment decision.

Morgan Stanley fixed income research analysts, including those principally responsible for the preparation of this research report, receive compensation based upon various factors,including quality, accuracy and value of research, firm profitability or revenues (which include fixed income trading and capital markets profitability or revenues), client feedback andcompetitive factors. Analysts compensation is not linked to investment banking or capital markets transactions performed by Morgan Stanley or the profitability or revenues of particulartrading desks.

This report is not an offer to buy or sell any security/instrument or to participate in any trading strategy. In addition to any holdings disclosed in the section entitled Important Disclosures onSubject Companies,Morgan Stanley and/or its employees not involved in the preparation of this report may have investments in securities/instruments or derivatives ofsecurities/instruments of companies mentioned in this report, and may trade them in ways different from those discussed in this report. Derivatives may be issued by Morgan Stanley orassociated persons.

Morgan Stanley makes every effort to use reliable, comprehensiveinformation, but we make no representation that it is accurate or complete. We have no obligation to tell you whenopinions or information in this report change.

With the exception of information regarding Morgan Stanley, reports prepared by Morgan Stanley research personnel are based on public information. Facts and views presented in thisreport have not been reviewed by, and m ay not reflect information known to, professionals in other Morgan Stanley business areas, including investment banking personnel.

The value of and income from investments may vary because of changes in interest rates, foreign exchange rates, default rates, prepayment rates, securities/instruments prices, marketindexes, operational or financial conditions of companies or other factors. There may be t ime limitations on the exercise of options or other rights in securities/instruments transactions.Past performance is not necessarily a guide to future performance. Estimates of future performance are based on assumptions that may not be realized.

This report may include research based on technical analysis. Technical analysis is generally based on the study of trading volumes and price movements in an attempt to identify andproject price trends. Technical analysis does not consider the fundamentals of the underlying issuer or instrument and may offer an investment opinion that conflicts with other researchgenerated by Morgan Stanley. Investors may consider technical research as one input in formulating an investment opinion. Additional inputs should include, but are not limited to, a reviewof the fundamentals of the underlying issuer/security/instrument.



28/28


Disclaimer

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Documents

Structured Credit As Portfolio Management Tool