Salomon Smith Barney Consulting Group
Shared by: fanzhongqing
-
Stats
- views:
- 8
- posted:
- 5/17/2012
- language:
- English
- pages:
- 82
Document Sample
MorganStanley | SmithBarney Consulting Group
Investment Advisor Research Questionnaire
Ryan Labs Asset Management
Name of Firm Address
Ryan Labs Asset Management 500 Fifth Avenue, Suite 2520, New York, NY 10110
Name of Product Benchmark
Long Liability Enhanced (LLE) Custom Liability Index (FAS 158 | PPA | Economic)
Broad Market Enhanced (BME) Barclays Capital Aggregate Index
Intermediate Market Enhanced (IME) Barclays Gov’t/Credit Intermediate Index
Short Duration Enhanced (SDE) Merrill Lynch 1 to 3 Year Index
Asset Class Investment Style Minimum Account Size
Fixed Income Investment Grade $10,000,000 Separate Account
$1,000,000 Collective Trust
Contact: Sean McShea Brad Jacob Annette Serrao
Direct: 646-708-8052 646-708-8044 646-708-8051
Fax: 212-202-4252 646-349-1524 646-349-1524
E-mail: SMcShea@ryanlabs.com BJacob@ryanlabs.com ASerrao@RyanLabs.com
Address: 500 Fifth Avenue, Suite 2520, New York, NY 10110
Web site: www.ryanlabs.com
Date: 10/24/2011
I. Firm AUM Information
9/2011 2010 2009 2008 2007
Total Firm $4,283 $3,736 $2,902 $2,065 $1,667
Separate Accounts $4,034 $3,475 $2,883 $2,065 $1,667
Mutual Funds - - - - -
Fixed Income $4,034 $3,475 $2,883 $2,065 $1,667
International Fixed Income - - - - -
Equity - - - - -
International Equity - - - - -
TALF $249 $261 $27 - -
Total AUM (09/30/2011)
Market Enhanced Portfolios $ 2,003.02 million
LDI Portfolios $ 2,031.12 million
TALF $248.86 thousand
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 1 of 82
1. Please provide a description of your organization’s history including its inception, founders, etc.
Founded March, 1988
SEC Registration: February 17, 1989
Mission Ryan Labs Asset Management offers actively managed fixed income separate account
vehicles to institutional investors. Our diversified, disciplined, and structured
investment process is employed versus popular market indexes as well as custom
liability indexes.
Ryan Labs Research and Index Divisions are dedicated to solving financial problems
through low cost, low risk solutions. We believe this is best accomplished through a
dedicated team of professionals leveraging the power of our proprietary computer
systems.
The synergy between Ryan Labs Asset Management, Research, and Index divisions
ensures that all of our products are designed based on proper data, provide the ability to
meet client objective indexes, and produce value-added returns.
History Ryan Labs was organized as a Subchapter S Corporation in March, 1988 by Harlan
Batrus (current), Thomas Kirch (current) and Ron Ryan (retired). Since inception,
Ryan Labs has specialized in quantitative fixed income asset management and has
advised and managed fixed income assets for institutional U.S. tax-exempt clients
versus market as well as custom (e.g. liability) indexes. Currently, our asset
management division manages $4.28 billion in fully discretionary assets versus two
distinct objectives: market indices and custom indices.
Initial Client Metropolitan Life Insurance (1989) (Defined Benefit Pension)
Project: First Custom Liability Index in the United States
Product Line: Separately Managed Accounts (SMA) or Collective Investment Trust (CIT)
Investment Grade Fixed Income versus Market or Custom Liability Indexes:
1. Ryan Labs Asset Management versus market benchmarks
Separate Collective
Product Index
Account Trust
Short Duration Enhanced Merrill Lynch Treasury 1 to 3 Years X
Short Duration Enhanced G/C Merrill Lynch Government/Credit 1 to 3 Years X
Limited Market Enhanced Barclays Credit 0 to 5 Years X
Broad Market Enhanced Barclays Aggregate Index X X
Government Credit Enhanced Barclays Government/Credit Index X
Intermediate Market Enhanced Barclays Government/Credit Intermediate X X
Government Enhanced Barclays Government Index X
Long Market Enhanced Barclays Long Government/Credit Index X X
Long Credit Enhanced Barclays Credit Long Index X
Long Government Enhanced Barclays Government Long Index X
High Yield Barclays US High Yield X
Inflation Index Enhanced US TIPS X
Absolute Return Fund LIBOR X
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 2 of 82
2. Custom (Ryan Labs creates Custom Liability Index equal to the Client Objective)
Product Index
Short Liability Enhanced Custom Liability Index 1 to 3 years
Intermediate Liability Enhanced Custom Liability Index 3 to 5 years
Core Liability Enhanced Custom Liability Index 5 to 7 years
Long Liability Enhanced Custom Liability Index 7 to 10 years
Very Long Liability Enhanced Custom Liability Index 10 to 15 years
Ultra Long Liability Enhanced Custom Liability Index 15 + years
Inflation Index Intermediate 8 Year Custom TIPS
Note: Client may select a valuation curve based on FAS 158, Pension Protection Act (PPA), Treasury
(Economic) or Swaps
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 3 of 82
1. Please define the ownership structure of your firm. Do you envision that this ownership structure
will change in the next 12 months?
Ryan Labs was organized as a Subchapter S Corporation. We do not envision any change of the above
ownership structure in the next 12 months.
The current ownership structure is as follows:
Ownership Structure % of Ownership
Employees (including stock options) 55
Private Investors 45
2. Please list the names of current owners along with their percent ownership.
Please see ADV Part I.
3. Has the organizational or ownership structure of your firm changed during the past 3 years? (If
‘Yes’ to any of these questions, please attach a detailed explanation)
The ownership structure has not changed during the past 3 years.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 4 of 82
4. Please define in general terms the business plan for your firm over the next three years. Please
include goals for assets. Also include information pertaining to major initiatives, including, but not
limited to, acquisitions, product launches, and new distribution networks.
Ryan Labs has no current intentions to pursue any acquisitions. We have always emphasized organic
(internal) growth.
Business Plan: (Three year horizon)
1.) Asset Management
New professional hires – Ryan Labs will continue to search for highly skilled investment
professionals. We will continue to reinvest in people with solid quantitative skills and a
passion for the fixed income business.
i. Short term - The Ryan Labs asset management team consists of 8 professionals. Over
the next six months we do not anticipate hiring any new managers.
ii. Long term – Ryan Labs is always on the lookout for a seasoned portfolio manager. We
seek to hire portfolio managers who can analyze complex cash flow structures to
understand value.
New systems – The bond market continuously evolves. Wall Street firms continue to market
new investment grade securities with additional complexity and features. Ryan Labs retains
two full time programmers to build in new formulas and models to assist asset management.
Our proprietary systems support our investment professionals in the asset management process.
Recent example: In the past year, Ryan Labs invested heavily in new portfolio trading systems and
controls. We added Bloomberg AIM for front-end compliance with clients’ Investment Policy
Statements (IPS); Bloomberg Edge for back-end for daily reconciliation with custodial banks.
New products
i. In 2011, Ryan Labs completed all the legal work, including: structure; trust documents;
Factsheets; and Investment Policies required launching a new Commingled Fund
product with Hand Benefits & Trust. This product was ready for market for four
different investment strategies as of October 1, 2011. The purpose of this new product
launch was to provide an absolute return, core, intermediate, and long duration fixed
income solutions to the DC market and under $10 million-in-size separate account
clientele.
ii. Existing opportunities
1. Risk retention pools – Due to an increase in insurance premiums by traditional
carriers, large institutional entities are setting aside assets to prefund liabilities.
These assets need to be invested in an asset liability framework. Ryan Labs is
actively marketing to this segment of the market.
2. Funding and reporting changes for pensions – Reporting changes
recommended by FASB and funding changes implemented by Congress and
the IRS when the Pension Protection Act (PPA) was implemented in 2008
place a premium on risk management for pension funds. Ryan Labs believes
that its philosophy and strategies will have an even greater appeal to plan
sponsors and consultants in light of these developments. Consequently, Ryan
Labs developed and trademarked a new product called the “Ryan Labs PPA
Liability Index Curve” which it is successfully marketing to pension plan
sponsors.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 5 of 82
3. Other Post-Employment Benefits (OPEB) – GASB regulations 43 and 45
address the “pay-as-you-go” status of the vast majority of public OPEB plans.
Funding of these plans should create additional asset gathering opportunities
for Ryan Labs.
4. Ryan Labs maintains and continues to update on a monthly basis the Dow
Jones Corporate Index. This Index has expanded as an opportunity for Ryan
Labs as it recently generated interest from various asset managers who are
managing their fixed income and ETF portfolios against the Index.
2.) Financial Goals
a. Revenue growth – Ryan Labs is looking to grow assets under management and revenues.
With the addition of new marketing professionals, expanding product capabilities, and
scalability of our existing product line we expect revenue growth of 15% to 20% over each
of the next three years.
b. Expense control – As Ryan Labs continues to expand in people and systems, we have been
mindful to track new expenses. Major expenses factors for us are:
a. Research databases and pricing feeds
b. Maintenance and upgrades to our proprietary trading systems
c. External research (i.e. Moody’s, S&P, Fitch)
d. Healthcare cost
e. Travel (Client service, new business)
c. Shareholder wealth
1. Ryan Labs strives to provide a steady stream of dividends to our investors.
2. As we continue to grow revenue and assets under management,
shareholders should expect the value of their shares to increase over time.
3.) Marketing & Client Service
a. New professionals - Ryan Labs is planning on hiring a new marketing professional and
client service associate in the near future.
b. New distributions
i. Ryan Labs has engaged Hand Benefits & Trust to facilitate entry into the 401K
market, and under $10 million-in-size separate account clientele, which were not
available previously under Ryan Labs’ separate account management structure.
4.) Other
a. Corporate Pension Funding Liability – Due to pension funding requirements, Ryan Labs
created a series of maturity/duration Corporate AA bond indexes (PPA) for actuarial firms.
b. In 2011, Ryan Labs completed all the documentation and audit verification required by
ACA to accredit Ryan Labs as GIPS compliant for the period ending December 31, 2010.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 6 of 82
5.) Please describe your employee incentive program for key investment and non-investment
professionals (e.g. how are salaries, bonuses, equity ownership, etc. used to provide incentives for key
employees).
Ryan Labs investment professionals receive a highly competitive base salary and complete benefits
package comparable to any major institution. In addition, they are reviewed twice annually and are
eligible for an annual discretionary bonus based on several factors, including asset management
performance. Excellent performance (long-term) is compensated by bonus for professional employees.
The bonus for Asset Management is based on an evaluation of the team and respective investment
professional’s contribution to risk adjusted returns of all asset management accounts versus their
respective benchmarks.
Ryan Labs offers employee ownership through stock options to the Asset Management team. These
incentives are determined by quantitative and qualitative factors. The performance bonus is based on
the level of outperformance over the benchmark, and the qualitative factors include a review by the
Director of Asset Management, in conjunction with other Senior Management of the Firm.
Ryan Labs’ core compensation package contains the following:
1. Competitive Base Salaries
2. 401k with company match and management fee
3. Health, Dental, Life and Disability Insurance
4. Sales/Marketing Commissions
5. Portfolio Managers are eligible for an annual bonus based on performance.
6. Stock Options are available for key employees in asset management, operations, and marketing.
7. Collegial, Team Oriented Culture
Asset Management Client Service Sales/Marketing Operations
Direct Compensation
Salary: 70% Salary: 70% Salary: 30% Salary: 70%
Bonus: 30% Bonus: 20% Commission: 70% Bonus: 20%
Indirect Compensation (as a % of Direct Compensation)
401K Match: 5% 401K Match: 5% 401K Match: 5% 401K Match: 5%
Insurance: 5% Insurance: 5% Insurance: 5% Insurance: 5%
Stock Options: 10%
1 Stock Options are available for key employees in asset management
2 Insurance includes health, dental, life, and disability
6.) Has your firm ever been the subject of an investigation by the SEC, NASD or any other government
or regulatory office? If yes, please explain. If the SEC or any other regulatory office has ever fined
the firm, please disclose the relevant details.
No
7.) When was the most recent SEC audit of your firm?
Ryan Labs most recent SEC audit was in April of 2003.
8.) Has the most recent SEC audit of your firm caused you to update any disclosures on your Form ADV
or otherwise required any action on your part to rectify concerns?
No
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 7 of 82
9.) Have there been any material changes to your organization not covered by the questions above?
No
10.) Facilities, systems, and support
a. Portfolio Accounting/Compliance:
Ryan Labs Proprietary Systems maintains all trading activities and pricing information of all
portfolios and calculate daily returns. The systems listed below present portfolio data in a
customized format for client reports and portfolio accounting. We use a third party firm named
ACA Beacon to verify formulas and GIPS performance standards at the firm and product level.
b. Trading:
Ryan Labs Proprietary Systems database maintains all security characteristics of Ryan Labs
investment grade universe. Our systems listed below provide traders and portfolio managers real
time information needed to evaluate individual securities:
SMART - deconstruct any market index.
TOPS - rank all bonds mathematically by a series of quantitative filters.
Ryan Labs Asset Management utilizes external sources for security evaluation:
Tradweb, BondEdge, Bloomberg AIM (pre-trade compliance), Bloomberg Edge (post trade
reconciliation)
c. Performance:
Ryan Labs Proprietary Systems maintains all trading activities and pricing information of all
portfolios and calculates daily returns. Our systems listed below present portfolio data in a
customized format for client performance:
DAILY – creates daily performance and portfolio reports;
PASS – delivers performance attribution report
STYLE – delivers performance style analysis
d. Portfolio Modeling:
Ryan Labs Proprietary Systems maintains all market indexes and custom benchmarks.
Ryan Labs Proprietary System listed below help portfolio managers to perform sector evaluation
and monitor portfolio risks daily:
DAILY - Create daily performance and portfolio reports
IDC BondEdge – assist portfolio modeling
e. Reconciliation:
Bloomberg Edge uses the SWIFT protocol system to link Ryan Labs asset portfolios with the
custodial bank for daily reconciliation.
f. Composite Creation/Maintenance:
Ryan Labs follows the GIPS performance standards for index and composite creation and
maintenance. We use a third party ACA Beacon to verify the standards at the firm level and
product level.
g. Accounting: Ryan Labs maintains a propriety portfolio accounting system for our separate
accounts. We use Hand Benefits & Trust Co. to provide portfolio accounting for the Collective
Trust.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 8 of 82
h. Back-Up: Ryan Labs maintains a mirror of all files with our disaster recovery site located in
Marlborough, MA.
11.) Please discuss your firm’s trading policies including policies for rotating trades among mutual
funds, institutional accounts, private client accounts, wrap accounts. Also discuss your policies
regarding directed brokerage. (Please note that directed brokerage is not a requirement to
participate in any Consulting Group program.)
Ryan Labs uses a best execution strategy in either of the following methods:
1. Putting major firms in competition directly
2. Using regional firms to put other firms in competition
Trades are settled internally by direct contact with the custodian utilizing a signed form.
Trades are checked daily for fails and other operational problems by our asset management personnel.
We use Bloomberg AIM for pre-trade compliance and Bloomberg Edge for daily reconciliation with the
custodian.
Ryan Labs block trades (buys and sells) across all accounts with similar indexes, holdings and
investment policy guidelines. We do not favor one account or a group of accounts for preferential
treatment. Ryan Labs does not participate in directed brokerage scenarios.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 9 of 82
II. Product Information
Total AUM (09/30/2011)
Market Enhanced Portfolios $ 2,003.02 million
LDI Portfolios $ 2,031.12 million
Product/Fund Name Investment Style Benchmark
Long Liability Enhanced Investment Grade Custom Liability Index (FAS 158 | PPA | Economic)
Total # of Total
Period-End Date Assets (LLE): Institutional Inst. Assets:
(in millions) Accounts (in millions)
9/30/2011 654.59 17 654.59
6/30/2011 606.99 17 606.99
3/31/2011 500.98 15 500.98
12/31/2010 385.68 13 385.68
9/30/2010 399.21 13 399.21
6/30/2010 324.13 12 324.13
3/31/2010 269.09 9 269.09
12/31/2009 220.78 7 220.78
9/30/2009 101.02 5 101.02
6/30/2009 105.25 6 105.25
3/31/2009 103.43 5 103.43
12/31/2008 75.68 4 75.68
9/30/2008 66.99 4 66.99
6/30/2008 19.38 2 19.38
3/31/2008 37.12 3 37.12
12/31/2007 27.07 2 27.07
9/30/2007 25.86 2 25.86
6/30/2007 24.34 2 24.34
3/31/2007 26.21 2 26.21
12/31/2006 27.4 2 27.4
9/30/2006 27.82 2 27.82
6/30/2006 26.41 2 26.41
3/31/2006 26.61 2 26.61
12/31/2005 27.26 2 27.26
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 10 of 82
Product/Fund Name Investment Style Benchmark
Broad Market Enhanced Investment Grade Barclays Capital Aggregate Index
Total # of Accounts Accounts
Period-End Date Assets (BME): Institutional Gained Lost
(in millions) Accounts
9/30/2011 198.35 7 1 0
6/30/2011 181.10 6 1 0
3/31/2011 140.87 5 0 0
12/31/2010 148.65 5 0 0
9/30/2010 141.66 5 0 0
6/30/2010 139.80 5 0 0
3/31/2010 138.56 5 0 0
12/31/2009 134.91 5 0 0
9/30/2009 153.97 5 0 0
6/30/2009 148.64 5 0 0
3/31/2009 156.74 5 0 0
12/31/2008 157.53 5 0 0
9/30/2008 164.34 5 2 0
6/30/2008 114.54 4 1 0
3/31/2008 107.78 3 0 0
12/31/2007 108.58 3 0 0
9/30/2007 106.24 3 0 0
6/30/2007 103.69 3 0 0
3/31/2007 104.37 3 0 0
12/31/2006 104.46 3 1 0
9/30/2006 87.83 2 0 0
6/30/2006 86.80 2 0 0
3/31/2006 88.03 2 0 1
12/31/2005 118.04 3 0 0
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 11 of 82
Product/Fund Name Investment Style Benchmark
Intermediate Market Enhanced Investment Grade Barclays Gov’t/Credit Intermediate Index
Total # of Accounts Accounts
Period-End Date Assets (IME): Institutional Gained Lost
(in millions) Accounts
9/30/2011 793.59 15 2 2
6/30/2011 753.07 15 0 1
3/31/2011 745.12 16 0 0
12/31/2010 752.01 16 0 0
9/30/2010 751.99 15 2 0
6/30/2010 705.61 13 2 0
3/31/2010 488.76 11 2 0
12/31/2009 433.68 9 0 0
9/30/2009 434.44 9 3 0
6/30/2009 283.62 6 1 0
3/31/2009 274.53 5 0 0
12/31/2008 273.76 5 0 0
9/30/2008 276.81 5 0 0
6/30/2008 275.43 5 0 0
3/31/2008 283.75 5 1 0
12/31/2007 249.51 4 0 0
9/30/2007 243.10 4 0 0
6/30/2007 242.05 4 0 0
3/31/2007 245.89 4 0 0
12/31/2006 228.02 4 0 0
9/30/2006 225.70 4 0 0
6/30/2006 226.05 5 0 0
3/31/2006 258.59 6 1 0
12/31/2005 238.46 5 0 0
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 12 of 82
Product/Fund Name Investment Style Benchmark
Short Duration Enhanced Investment Grade Merrill Lynch 1 to 3 Year Index
Total # of Accounts Accounts
Period-End Date Assets (SDE): Institutional Gained Lost
(in millions) Accounts
9/30/2011 243.31 8 0 0
6/30/2011 244.92 8 0 0
3/31/2011 242.12 8 0 0
12/31/2010 241.90 8 0 0
9/30/2010 243.37 8 1 0
6/30/2010 229.12 7 0 3
3/31/2010 274.52 10 0 1
12/31/2009 457.32 11 0 0
9/30/2009 456.19 11 0 0
6/30/2009 451.79 11 0 0
3/31/2009 450.98 11 3 1
12/31/2008 365.39 9 0 0
9/30/2008 357.33 9 1 0
6/30/2008 344.18 8 0 0
3/31/2008 346.39 8 1 1
12/31/2007 335.22 8 0 0
9/30/2007 339.35 8 0 0
6/30/2007 331.30 8 0 0
3/31/2007 333.67 8 0 0
12/31/2006 325.53 8 2 0
9/30/2006 257.30 5 1 0
6/30/2006 252.44 5 1 1
3/31/2006 297.37 5 1 0
12/31/2005 202.81 4 0 1
12.) Is your composite for this product CFA Institute GIPs compliant? If yes, what level? If no, please
explain why.
Ryan Labs claims GIPS compliance at firm level as well as product level as of December 31, 2010.
GIPS verification letter is provided by ACA Beacon and is available upon request.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 13 of 82
13.) Please provide your composite disclosures on this product. Please type in the response. Do not
send as a separate document.
Long Liability Enhanced (LLE)
Composite Characteristics: Ryan Labs Long Liability Enhanced Composite was created in June 30,
1991. The composite includes all taxable investment grade fixed income benchmarked to a Custom
Liability Index with an asset allocation of 100% investment grade securities. A complete list and
description of all the firm composites is available upon request. All discretionary accounts managed
against the Custom Liability Index are included in the composite. New accounts that fit the composite
definition are added at the beginning of the first full calendar month for which the account is under
management. Closed account data is included in the composite as mandated by the standards in order to
eliminate a survivorship bias. Additional information regarding the firm’s policies and procedures for
calculating and reporting performance results is available upon request.
Calculation Methodology: Gross of fees returns are calculated gross of management and custodial fees
and net of transaction costs. Composite results reflect the reinvestment of dividends, capital gains, and
other earnings when appropriate. Accruals for all securities are included in calculations. The dispersion
measure is the asset-weighted standard deviation of accounts in the composite for the entire year.
Disclaimers & Footnotes: Ryan Labs Long Liability Enhanced commenced operations on June 30,
1991. Past performance of the account is not indicative of future results. The performance above is
gross of all fees and expenses for the stated period and assumes reinvestment of dividends and other
earnings. Risk Return characteristics are based on returns from the trailing five year period, and do not
reflect the deduction of advisory fees. An advisory fee reduces the investor’s return and any other
expenses Ryan Labs may incur managing the investment advisory account. The investment advisory
fees are described in Part II of the Ryan Labs Form ADV. All returns are calculated net of transaction
costs, and gross of taxes on dividends and interest. Performance results are based on US dollar returns.
The investment advisory fee charged to each investor causes their return to be lower than the gross
returns presented above. Investment results may vary. No assurance can be given that the investment
objective will be achieved, and an investor may lose money. Due to current market volatility, current
performance may be lower than that of the figures shown. This material is intended for informational
purposes only and does not constitute investment advice, a recommendation, or an offer or solicitation
to purchase or sell any security or other instrument. The Account’s total return will fluctuate over a
wider range than money market investments due to greater sensitivity to (i) interest rates, (ii) market
conditions, (iii) and maturities.
Custom Liability Indexes are weighted by the Client’s projected benefit schedule and valued at a yield
curve. Indexes are unmanaged and are not subject to transaction charges or expenses. An investor may
not invest directly in an index.
Broad Market Enhanced (BME)
Composite Characteristics: Ryan Labs Broad Market Enhanced Composite was created in June 30,
1996. The composite includes all taxable investment grade fixed income benchmarked to the Barclays
Capital Aggregate Index3 with an asset allocation of 100% investment grade securities. A complete list
and description of all the firm composites is available upon request. All discretionary accounts managed
against the Barclays Capital Aggregate Index are included in the composite. New accounts that fit the
composite definition are added at the beginning of the first full calendar month for which the account is
under management. Closed account data is included in the composite as mandated by the standards in
order to eliminate a survivorship bias. Additional information regarding the firm’s policies and
procedures for calculating and reporting performance results is available upon request.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 14 of 82
Calculation Methodology: Gross of fees returns are calculated gross of management and custodial fees
and net of transaction costs. Composite results reflect the reinvestment of dividends, capital gains, and
other earnings when appropriate. Accruals for all securities are included in calculations. The dispersion
measure is the asset-weighted standard deviation of accounts in the composite for the entire year.
Disclaimers & Footnotes: Ryan Labs Broad Market Enhanced commenced operations on June 30, 1996.
Past performance of the account is not indicative of future results. The performance above is gross of
all fees and expenses for the stated period and assumes reinvestment of dividends and other earnings.
Risk Return characteristics are based on returns from the trailing five year period, and do not reflect the
deduction of advisory fees. An advisory fee reduces the investor’s return and any other expenses Ryan
Labs may incur managing the investment advisory account. The investment advisory fees are
described in Part II of the Ryan Labs Form ADV. All returns are calculated net of transaction costs,
and gross of taxes on dividends and interest. Performance results are based on US dollar returns. The
investment advisory fee charged to each investor causes their return to be lower than the gross returns
presented above. Investment results may vary. No assurance can be given that the investment objective
will be achieved, and an investor may lose money. Due to current market volatility, current
performance may be lower than that of the figures shown. This material is intended for informational
purposes only and does not constitute investment advice, a recommendation, or an offer or solicitation
to purchase or sell any security or other instrument. The Account’s total return will fluctuate over a
wider range than money market investments due to greater sensitivity to (i) interest rates, (ii) market
conditions, (iii) and maturities.
The Barclays Capital Aggregate Index is composed of domestic investment grade fixed income
securities with maturities of 1-30 years. Pursuant to the rules of the Index, the Index’s portfolio must
(i) have at least one year to final maturity, (ii) have at least $250 million par amount outstanding, (iii)
be fixed rate, (iv) be U.S. Dollar denominated and non-convertible, (v) and be publicly issued. Indexes
are unmanaged and are not subject to transaction charges or expenses. An investor may not invest
directly in an index.
Intermediate Market Enhanced (IME)
Composite Characteristics: Ryan Labs Intermediate Market Enhanced Composite was created in
January 31, 2000. The composite includes all taxable investment grade fixed income benchmarked to
the Barclays G/C Intermediate Index3 with an asset allocation of 100% investment grade securities. A
complete list and description of all the firm composites is available upon request. All discretionary
accounts managed against the Barclays G/C Intermediate Index are included in the composite. New
accounts that fit the composite definition are added at the beginning of the first full calendar month for
which the account is under management. Closed account data is included in the composite as mandated
by the standards in order to eliminate a survivorship bias. Additional information regarding the firm’s
policies and procedures for calculating and reporting performance results is available upon request.
Calculation Methodology: Gross of fees returns are calculated gross of management and custodial fees
and net of transaction costs. Composite results reflect the reinvestment of dividends, capital gains, and
other earnings when appropriate. Accruals for all securities are included in calculations. The dispersion
measure is the asset-weighted standard deviation of accounts in the composite for the entire year.
Disclaimers & Footnotes: Ryan Labs Intermediate Market Enhanced commenced operations on January
31, 2000. Past performance of the account is not indicative of future results. The performance above is
gross of all fees and expenses for the stated period and assumes reinvestment of dividends and other
earnings. Risk Return characteristics are based on returns from the trailing five year period, and do not
reflect the deduction of advisory fees. An advisory fee reduces the investor’s return and any other
expenses Ryan Labs may incur managing the investment advisory account. The investment advisory
fees are described in Part II of the Ryan Labs Form ADV. All returns are calculated net of transaction
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 15 of 82
costs, and gross of taxes on dividends and interest. Performance results are based on US dollar returns.
The investment advisory fee charged to each investor causes their return to be lower than the gross
returns presented above. Investment results may vary. No assurance can be given that the investment
objective will be achieved, and an investor may lose money. Due to current market volatility, current
performance may be lower than that of the figures shown. This material is intended for informational
purposes only and does not constitute investment advice, a recommendation, or an offer or solicitation
to purchase or sell any security or other instrument. The Account’s total return will fluctuate over a
wider range than money market investments due to greater sensitivity to (i) interest rates, (ii) market
conditions, (iii) and maturities.
The Barclays G/C Intermediate Index is composed of domestic investment grade fixed income securities
with maturities from 1 but not greater than 10 years. Pursuant to the rules of the Index, the Index’s
portfolio must (i) have at least one year to final maturity, (ii) have at least $250 million par amount
outstanding, (iii) be fixed rate, (iv) be U.S. Dollar denominated and non-convertible, (v) and be publicly
issued. Indexes are unmanaged and are not subject to transaction charges or expenses. An investor
may not invest directly in an index.
Short Duration Enhanced (SDE)
Composite Characteristics: Ryan Labs Short Duration Enhanced Composite was created in December
31, 1993. The composite includes all taxable investment grade fixed income benchmarked to the Merrill
Lynch Treasury 1 to 3 Year Index3 with an asset allocation of 100% investment grade securities. A
complete list and description of all the firm composites is available upon request. All discretionary
accounts managed against the Merrill Lynch Treasury 1 to 3 Year Index are included in the composite.
New accounts that fit the composite definition are added at the beginning of the first full calendar
month for which the account is under management. Closed account data is included in the composite as
mandated by the standards in order to eliminate a survivorship bias. Additional information regarding
the firm’s policies and procedures for calculating and reporting performance results is available upon
request.
Calculation Methodology: Gross of fees returns are calculated gross of management and custodial fees
and net of transaction costs. Composite results reflect the reinvestment of dividends, capital gains, and
other earnings when appropriate. Accruals for all securities are included in calculations. The dispersion
measure is the asset-weighted standard deviation of accounts in the composite for the entire year.
Disclaimers & Footnotes: Ryan Labs Short Duration Enhanced commenced operations on December
31, 1993. Past performance of the account is not indicative of future results. The performance above is
gross of all fees and expenses for the stated period and assumes reinvestment of dividends and other
earnings. Risk Return characteristics are based on returns from the trailing five year period, and do not
reflect the deduction of advisory fees. An advisory fee reduces the investor’s return and any other
expenses Ryan Labs may incur managing the investment advisory account. The investment advisory
fees are described in Part II of the Ryan Labs Form ADV. All returns are calculated net of transaction
costs, and gross of taxes on dividends and interest. Performance results are based on US dollar returns.
The investment advisory fee charged to each investor causes their return to be lower than the gross
returns presented above. Investment results may vary. No assurance can be given that the investment
objective will be achieved, and an investor may lose money. Due to current market volatility, current
performance may be lower than that of the figures shown. This material is intended for informational
purposes only and does not constitute investment advice, a recommendation, or an offer or solicitation
to purchase or sell any security or other instrument. The Account’s total return will fluctuate over a
wider range than money market investments due to greater sensitivity to (i) interest rates, (ii) market
conditions, (iii) and maturities.
The Merrill Lynch Treasury 1 to 3 Year Index tracks the performance of US Dollar-denominated
investment grade Government public debt issued in the US Domestic bond market. Indexes are
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 16 of 82
unmanaged and are not subject to transaction charges or expenses. An investor may not invest directly
in an index.
14.) Please complete the following tables for the performance composite used to represent the
performance of the product described in this questionnaire. If you have multiple composites for this
product (variations on the same mandate), please complete multiple tables.
Long Liability Enhanced (LLE)
Year Total Benchmark Number Composite Total Assets Percentage
Return Return of Dispersion at End of of Firm
(Percent) (Percent) Portfolios (percent) Period ($ Assets
million)
3Q2011 9.425 7.160 17 - 654.6 16.226
2010 9.841 9.172 13 0.556 386.01 11.097
2009 1.662 -3.949 7 No Dispersion 219.64 7.569
2008 17.434 16.634 4 No Dispersion 75.68 3.480
2007 9.332 9.829 2 No Dispersion 27.07 1.598
2006 2.991 2.642 2 No Dispersion 27.40 1.985
2005 5.008 4.568 2 No Dispersion 27.26 1.580
2004 6.175 6.461 2 No Dispersion 26.02 1.457
2003 2.498 2.629 3 No Dispersion 32.67 3.272
2002 16.516 17.800 5 No Dispersion 103.99 13.657
2001 7.492 5.621 6 No Dispersion 75.30 12.420
2000 18.367 19.114 5 No Dispersion 98.20 18.543
Broad Market Enhanced (BME)
Year Total Benchmark Number Composite Composite Percentage
Return Return of Dispersion Assets, End of Firm
(Percent) (Percent) Portfolios (percent) of Period Assets
($mil)
3Q2011 6.999 6.647 7 - 198.35 4.917
2010 8.718 6.542 5 0.158 148.64 4.273
2009 7.916 5.930 5 0.467 134.91 4.649
2008 6.869 5.240 5 No Dispersion 149.71 6.884
2007 7.376 6.967 3 No Dispersion 108.58 6.409
2006 4.672 4.334 3 No Dispersion 104.46 7.567
2005 2.448 2.429 3 No Dispersion 118.04 6.843
2004 4.507 4.339 4 No Dispersion 192.38 10.774
2003 4.495 4.104 3 No Dispersion 93.96 9.409
2002 13.064 10.255 2 No Dispersion 62.88 8.257
2001 7.852 8.443 2 No Dispersion 72.05 11.883
2000 13.386 11.626 3 No Dispersion 68.99 13.027
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 17 of 82
Intermediate Market Enhanced (IME)
Year Total Benchmark Number Composite Composite Percentage
Return Return of Dispersion Assets, End of Firm
(Percent) (Percent) Portfolios (percent) of Period Assets
($mil)
3Q2011 5.185 4.920 15 0.698 793.59 19.672
2010 6.776 5.891 16 0.421 753.40 21.658
2009 6.325 5.244 9 2.284 433.68 14.946
2008 7.167 5.075 5 No Dispersion 273.76 12.589
2007 7.637 7.386 4 No Dispersion 249.51 14.727
2006 4.447 4.082 4 No Dispersion 228.02 16.516
2005 1.425 1.579 5 0.168 238.46 13.823
2004 3.113 3.042 5 No Dispersion 259.62 14.540
2003 3.743 4.310 9 2.324 240.44 24.078
2002 10.889 9.836 5 No Dispersion 140.60 18.464
2001 7.702 8.963 2 No Dispersion 3.75 0.619
Short Duration Enhanced (SDE)
Year Total Benchmark Number Composite Composite Percentage
Return Return of Dispersion Assets, End of Firm
(Percent) (Percent) Portfolios (percent) of Period Assets
($mil)
3Q2011 1.665 1.356 8 0.129 243.31 6.031
2010 7.458 8.300 4 No Dispersion 160.16 4.604
2009 8.050 5.757 3 No Dispersion 157.18 5.417
2008 3.130 1.896 5 No Dispersion 208.88 9.605
2007 1.749 0.907 5 No Dispersion 207.73 12.261
2006 1.988 1.668 4 No Dispersion 202.81 14.690
2005 4.398 3.963 8 No Dispersion 325.53 18.871
2004 6.881 7.317 8 0.150 335.22 18.774
2003 6.034 6.609 9 0.251 365.39 36.591
2002 2.784 0.785 11 0.744 457.30 60.054
2001 2.691 2.349 8 0.168 241.80 39.883
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 18 of 82
III. Portfolio Management and Other Key Personnel
Key Investment Personnel
Name Primary/ Since Advanced Degree From CFA Investment Joined Firm
Co-PM Mo/Year Experience Mo/Year
Starting
(year)
Richard Familetti Primary PM May-09 Fordham University ✓ 25 May-09
Michael Donelan Primary PM Jul-03 Fordham University ✓ 23 Jul-03
Daniel Lucey Primary PM Feb-10 College of Holy Cross ✓ 8 Oct-09
Phil Mendonca Primary PM Jun-07 Pace University 8 Mar-03
Nick Finkelman Primary PM Mar-03 Pace University ✓ 8 May-03
Matt Salzillo Analyst/ Trader Jul-04 Seton Hall University 7 Jul-04
Key Non- Investment Personnel
Name Primary/ Since Advanced Degree CFA Investment Joined Firm
Co-PM Mo/Year From Experience Mo/Year
Starting (year)
Harlan Batrus Strategist Oct-88 University of Penn 33 Oct-88
Thomas Kirch Senior Advisor Nov-03 Univ. of Delaware 40 Nov-03
Geraldine COO May-91 Pacific Western 36 May-91
Michalik, Ph.D. University
Sean McShea President Apr-93 Columbia University 22 Sep-93
Bradley Jacob VP Marketing Jun-08 DePaul University 7 Jun-08
16. For all key investment and non-investment professionals noted above, please note in the table below
their primary functions served. Please place an ‘l’ (lower case L) in any box to note a primary
function. The ‘l’ will appear as in the box as the font used is wingding. To expand the table,
simply press the ‘Tab’ key while in the bottom right-most cell.
Mkting
Security Security Portfolio Over- Client Business
Name and
Selection Research Construct sight Trading Service Mgmt
Sales
Investment Professional
Michael Donelan 30 20 40 10
Philip Mendonca 30 30 20 20
Richard Familetti 20 30 30 10 10
Matt Salzillo 20 20 50 10
Nick Finkelman 30 35 25 10
Daniel Lucey 30 30 20 20
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 19 of 82
Security Security Portfolio Over- Mkting Client Business
Name Selection Research Construct sight Trading and Service Mgmt
Sales
Other Key Professionals
Sean McShea 40 20 20 20
Geraldine Michalik 30 10 60
Batrus, Harlan 60 40
Brad Jacob 50 50
17. Please provide complete biographies on all key investment and non-investment professionals listed in
the table above.
Name Title Responsibility Years Years Education/Degree
of Exp with
Firm
Thomas Kirch Senior Advisor Company Operations 44 23 BA University of
Delaware
Harlan Batrus Chairman & Company Operations 38 23 BS Wharton School
Managing Director
Geraldine Michalik Chief Operating Company Operations 38 20 PhD Pacific Western
Officer Strategy MBA NYU
Sean McShea President Company Operations/ 24 18 MBA Columbia
Marketing University
Douglas Love Senior Advisor Research 49 16 PhD Columbia U.
David Audley Research Strategist Research 24 2 PhD Johns Hopkins
Michael Donelan Director Asset Portfolio Management 23 8 MBA Fordham U.
Management CFA
Richard Familetti Sr. Portfolio Manager Portfolio 25 2 MBA Fordham U.
Management, Credit CFA
Philip Mendonca Sr. Portfolio Manager Portfolio 8 8 BBA Pace
Management, University
Securitized
Nicholas Finkelman Portfolio Manager Portfolio 8 7 BBA Pace
Management, Credit University
Yulia Minina Credit Analyst Credit Research 9 2 MBA MIT
Matt Salzillo Trader/Analyst Portfolio Management 7 7 BA Seton Hall
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 20 of 82
Name Title Responsibility Years Years Education/Degree
of Exp with
Firm
Ken Szal Trader/Analyst Trading/Operations 2 2 BA Holy Cross
Bradley Jacob VP – Marketing & Marketing/Client 8 3 BS DePaul
Client Service Service University
Eva Zhou Marketing Analyst Marketing/Client 4 4 BBA Baruch
Service College
Annette Serrao Marketing Analyst Marketing/Client 1 1 MBA Pace
Service University
Jean Mimi Systems Systems 23 13 College of Haiti
Claret Kukol Systems Systems 20 12 Bogota University
Luis Lopez Operations Manager Operations 7 3 BA Hunter
Raghava Vudata Index Analyst Operations, Index 3 3 MEM New Mexico
18. Please provide organizational charts for key professionals (Senior/Management level, Investment
level, Research level)?
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 21 of 82
19. Has anyone listed in Personnel tables above had a change on role or responsibilities within the firm
over the last 3 years?
None
20. Please identify all research analysts that contribute to the product profiled in this questionnaire and
note the specific area(s) of coverage for each. If your analysts are generalists, please note
“Generalist” in the second column. Also please indicate who the Head of each research group is.
To expand the table, simply press the ‘Tab’ key while in the bottom right-most cell.
Name of Analyst Area of Coverage Analyst Location
Credit
Yulia Minina Credit New York
Richard Familetti Credit New York
Nick Finkelman Credit New York
Michael Donelan Credit New York
Name of Analyst Area of Coverage Analyst Location
Structured Securities Analysts
Daniel Lucey Securitized New York
Philip Mendonca Securitized New York
Index / Investment System
Raghava Vudata Index Analysis New York
David Audley Index Analysis New York
Liability
Sean McShea Liability Advisory New York
Brad Jacob Liability Advisory New York
Doug Love Liability Advisory New York
21. Please list below all additions and deletions for the past three years of investment professionals and
senior business/marketing personnel. This question pertains to firm-wide personnel changes. If
your firm is a very large, multi-division asset management company, include only personnel changes
from the division that manages the product profiled in this questionnaire. To expand the table,
simply press the ‘Tab’ key while in the bottom right-most cell.
Additions
Additions: Coverage Product Date of
Name Title Responsibilities Responsibilities Hire
Vice President – Marketing and
Bradley D. Jacob All 2008
Marketing Client Services
Structured
Daniel J. Lucey, CFA Portfolio Manager All 2009
Product - PM
Ken Szal Trading Trade execution All 2009
Investment grade
Richard Familetti, CFA Portfolio Manager All 2009
credit - PM
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 22 of 82
Yulia Minina Credit Research Credit Research All 2009
Marketing/ LDI
Annette Serrao Marketing Analyst All 2010
Analysis
Deletions
Departures: Coverage Product Reason for
Name Title responsibilities Responsibilities Departure
Investment Grade 2009/New
James Harrington Portfolio Manager Market
Mortgages Opportunity
2011/ New
Chris Adair VP Marketing Marketing All
Opportunity
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 23 of 82
IV. Investment Process
22. What is the objective for this product?
The Long Liability Enhanced (LLE) portfolio’s overall investment objective is to seek total return
versus the Custom Liability Index while providing protection against interest rate risk. We attempt to
accomplish these investment objectives by investing in US Dollar denominated, investment grade fixed
income securities. The long-term objective of the account is to outperform its Custom Liability Index
when measured over 3 to 5 year periods. The sensitivity to interest rate changes is intended to track the
market for domestic, investment grade fixed income securities. The modified duration of the account’s
investment portfolio at the end of each calendar month during a fiscal year will typically be within half
a year of the benchmark. The primary strategies utilized for value add are sector rotation, issue
selection, and yield curve positioning.
The Broad Market Enhanced (BME) portfolio’s overall investment objective is to seek total return
versus the Barclays Aggregate Index while providing protection against interest rate risk. We attempt to
accomplish these investment objectives by investing in US Dollar denominated, investment grade fixed
income securities. The long-term objective of the account is to outperform the Barclays Aggregate
Index when measured over 3 to 5 year periods. The sensitivity to interest rate changes is intended to
track the market for domestic, investment grade fixed income securities. The modified duration of the
account’s investment portfolio at the end of each calendar month during a fiscal year will typically be
within half a year of the benchmark. The primary strategies utilized for value add are sector rotation,
issue selection, and yield curve positioning.
The Intermediate Market Enhanced (IME) portfolio’s overall investment objective is to seek total return
versus the Barclays Government Credit Intermediate Index while providing protection against interest
rate risk. We attempt to accomplish these investment objectives by investing in US Dollar denominated,
investment grade fixed income securities. The long-term objective of the account is to outperform the
Barclays Government Credit Intermediate Index when measured over 3 to 5 year periods. The
sensitivity to interest rate changes is intended to track the market for domestic, investment grade fixed
income securities. The modified duration of the account’s investment portfolio at the end of each
calendar month during a fiscal year will typically be within half a year of the benchmark. The primary
strategies utilized for value add are sector rotation, issue selection, and yield curve positioning.
The Short Duration Enhanced (SDE) portfolio’s overall investment objective is to seek total return
versus the Merrill Lynch 1 to 3 Year Index while providing protection against interest rate risk. We
attempt to accomplish these investment objectives by investing in US Dollar denominated, investment
grade fixed income securities. The long-term objective of the account is to outperform the Merrill
Lynch 1 to 3 Year Index when measured over 3 to 5 year periods. The sensitivity to interest rate
changes is intended to track the market for domestic, investment grade fixed income securities. The
modified duration of the account’s investment portfolio at the end of each calendar month during a
fiscal year will typically be within half a year of the benchmark. The primary strategies utilized for
value add are sector rotation, issue selection, and yield curve positioning.
23. Please list the product’s general investment philosophy/approach to investing.
The fundamental concept of Ryan Labs investment philosophy is to strive to meet client objectives with
the least amount of total risk and total costs. The firm believes that these objectives are best achieved
through the use of structured portfolios with active issue selection and passive interest rate prediction
strategy. Ryan Labs adds value through a combination of issue selection and sector rotation. Ryan Labs
does not take active interest rate positions; Ryan Labs believes that interest rates are difficult (if not
impossible) to predict, and therefore, need to be neutralized.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 24 of 82
The initial step in Ryan Labs process involves the selection of the benchmark that is considered the
most appropriate for the client. The selected benchmark determines the term structure of the portfolio
and also serves as a performance measurement yardstick.
Clients have the flexibility to choose either a custom liability benchmark or a market benchmark (i.e.,
BC Aggregate, BC G/C, etc.). Custom indexes are created in an attempt to replicate clients’ liability
characteristics or funding requirements. To create a customized benchmark, Ryan Labs uses the
Pension Protection Act yield curve (A to AAA credit), FAS 158 yield curve (AA credit), or Treasuries
to map the projected future value of cash flows. Ryan Labs has the ability to map the projected future
cash flow using other curves. After a benchmark has been identified, Ryan Labs replicates the
maturity/duration, coupon, industry, and rating components of the benchmark. This task is completed
through the use of their proprietary system, Systematic Method of Advanced Replication Techniques
(SMART). We then seek to reduce interest rate risks by replicating the term structure of the benchmark
and monitoring exposure.
Ryan Labs concentrates its spread risk in the short end of the curve and attempts to neutralize interest
rates. Therefore we do not expect market conditions to materially affect our performance with respect
to a benchmark.
24. Has your investment process changed over the last three years?
No
25. Will this product have exposure to commingled vehicles? Provide details around how the
commingled funds will be utilized within the portfolio?
What funds are available for the portfolio? Is your firm currently planning to create any
additional funds?
What is the max allocation to commingled funds for the portfolio? What is max allocation
for each fund?
What are the objectives of the funds? Are they designed to replicate an index sector? Are
they designed to add alpha above the index sector?
There is no mix for funds invested in Separate Accounts and Collective Investment Trust (CIT).
There are four funds in the CIT.
Separate CIT
Product Index Account
Short Duration Enhanced Merrill Lynch Treasury 1 to 3 Years X
Short Duration Enhanced G/C Merrill Lynch Government/Credit 1 to 3 X
Limited Market Enhanced Years Credit 0 to 5 Years
Barclays X
Broad Market Enhanced Barclays Aggregate Index X X
Government Credit Enhanced Barclays Government/Credit Index X
Intermediate Market Enhanced Barclays Government/Credit Intermediate X X
Government Enhanced Barclays Government Index X
Long Market Enhanced Barclays Long Government/Credit Index X X
Long Credit Enhanced Barclays Credit Long Index X
Long Government Enhanced Barclays Government Long Index X
High Yield Barclays US High Yield X
Inflation Index Enhanced US TIPS X
Absolute Return Fund LIBOR X
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 25 of 82
CIT Objectives:
1. Absolute Return Fund: The Ryan Labs Absolute Return Fund’s overall investment objective is to
seek total return versus the LIBOR, using investment grade, high yield, structured product, credit
default swaps, and fixed income ETFs. The long-term objective of the account is to outperform the
LIBOR.
2. Core Fund: The Ryan Labs Core Fixed Income Fund’s overall investment objective is to seek
total return versus the Barclays Aggregate Index while neutralizing interest rate risk. We attempt to
accomplish these investment objectives by investing in US Dollar denominated fixed income
securities. The long-term objective of the account is to outperform the Barclays Aggregate Index
when measured over 3 to 5 year periods.
3. Intermediate Duration Fund: The Ryan Labs Intermediate Duration Fixed Income Fund’s overall
investment objective is to seek total return versus the Barclays Gov/Credit Intermediate Index while
neutralizing interest rate risk. We attempt to accomplish these investment objectives by investing in
US Dollar denominated fixed income securities. The long-term objective of the account is to
outperform the Barclays Gov/Credit Intermediate Index when measured over 3 to 5 year periods.
4. Long Duration Fund: The Ryan Labs Long Duration Fixed Income Fund’s overall investment
objective is to seek total return versus the Barclays Gov/Credit Long Index while neutralizing
interest rate risk. We attempt to accomplish these investment objectives by investing in US Dollar
denominated, investment grade fixed income securities. The long-term objective of the account is to
outperform the Barclays Gov/Credit Long Index when measured over 3 to 5 year periods.
26. Please describe your decision-making process – including the identification of the decision-making
body, how and by whom ideas are generated, how final decisions are finalized (committee process,
individual, voting process, veto authority) etc. Who decides the final buys and sells of the portfolio?
Is it a committee driven process or based on an individual?
The Ryan Labs Asset Management System drives most of the portfolio structure and characteristics.
Portfolio managers must adhere to the elements of our structural proprietary system. No individual
manager is responsible for strategy or direction. Ryan Labs professionals and Systems function as a
team. All professionals meet on a regularly scheduled basis to discuss clients and portfolios.
Fixed Income Decision Making Process
Ryan Labs investment strategy is to create a structured portfolio that is active in security selection and
passive in interest rate projections. Since Ryan Labs does not predict interest rates, we look for bonds
whose spreads can widen and still beat the equivalent Treasury over all interest rate scenarios. We
advocate greater use of spread products (agencies and corporate bonds) in the shorter areas of the yield
curve (ten years and under) where additional coupon is beneficial to support spread movements. Within
the Ryan Labs term structure neutral approach we seek to capture additional return through yield curve
analysis. For example, if the slope of the yield curve is the steepest in the longer portion of the one-year
maturity bucket, our duration within the one-year bucket will be longer than the benchmark. We will
offset this by being shorter than the index in another, less steep maturity bucket. This allows us to
maintain the same dollar weighting by maturity bucket while benefiting more from the roll down the
yield curve. This also allows us to maintain the same overall duration as the index.
The benefit of this approach is lower risk and higher return. Lower risk is achieved through
maintaining the same duration with the same or higher credit quality. Higher return is achieved through
out-yielding the index, choosing better sectors and bonds, and capturing the positive roll of the yield
curve.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 26 of 82
Product Purpose
SMART Index Replication Model
SECTORS Rich / Cheap System
TOPS Tactical Optimal Portfolio System
DAILY Daily Performance Measurement Model
PASS Performance Attribution Model
MANIFOLD Daily custom Internet delivery system
27. Please rank (in list form) the ways in which you seek to add value through your investment process.
(Example for fixed income – country selection, currency selection, duration management, yield curve
positioning, sector selection, security selection, etc.)
Source of Value Added Percent
1. Security selection 60
2. Sector selection 30
3. Yield curve positioning 10
28. Please define your investment “opportunity set”. If you have certain criteria for inclusion in your
investment universe (A rated bonds or better, etc.) please identify them here.
Our opportunity set is the domestic investment grade fixed income universe within the Aggregate
universe. In our separate account strategies, certain clients have quality or sector constraints that are
adhered to.
29. Decision-rules, drivers of security selection, or the qualities of what makes an investment attractive.
Please be as specific as your process allows. List specific factors and thresholds if applicable.
Ryan Labs Proprietary TOPS (Tactical Optimal Portfolio System) System ranks bonds from best to
worst based on an average of how much their spreads can widen relative to the "on the run" Treasury of
a similar maturity/duration and still "breakeven" in total return over four interest rate scenarios. A bond
can have a great average because it can withstand spreads widening significantly if interest rates rise
but not if rates fall, or vice versa. Since Ryan Labs does not predict interest rates, we look for bonds
whose spreads can widen and still beat the Treasury over all interest rate scenarios. For example, if
Breakeven Analysis in TOPS shows equally distributed positive numbers across each interest rate
scenario (+100 bps, +50, -50, -100) the bond passes our first test of relative value.
Next, TOPS provides yield spreads for the bond in question for today and the previous 30, 60, 90, 180
days in addition to the minimum and maximum spread for the 180-day period. The cheaper the spread
today relative to the average spread over the past 180 days, the more attractive the bond becomes. In
general, we subtract the spread difference from its cushion in Breakeven Analysis over each interest
rate scenario.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 27 of 82
We then weigh the analytics of the bond from TOPS against qualitative judgments with respect to credit
and investment policy.
We advocate greater use of spread products (agencies, mortgages and corporate bonds) in the shorter
areas of the yield curve (ten years and under) where additional coupon is beneficial to support spread
movements. We advocate the use of Treasury bonds and Agency Benchmark Notes as the composition
in the longer area of the yield curve (beyond ten years). Total return is a function of duration and
spread. For example, if a single-A corporate bond has 10-year duration and a spread correction of 10
basis points, it will result in approximately 100 basis points of total return difference. Managing versus
an index is oftentimes a zero sum game. By concentrating one’s risks in spread products to lower
durations, you limit your risks to areas where income can absorb the difference over time. This is not
necessarily true in longer durations.
As mentioned previously, Ryan Labs uses spread product in the shorter areas of the yield curve and
Governments (Treasury and Benchmark Notes) in the longer portion. Since investment policy typically
prohibits more than 5% per corporate issuer, the portion of the yield curve that possesses the most
corporate bonds also has the most diversity. Further, the number of bonds within a separate account is
directly related to the dollar amount of the portfolio.
For liquidity and execution purposes, we use block trades across clients. This allows us to maintain the
same pricing standards as that of the benchmark index.
30. Please describe your research process along with the tools used (fundamental, quantitative, both,
tools used, proprietary vs. “street” etc.). Identify what percentage of your research is Internal versus
External.
Internal External
Sector 50% 50%
Macro 0% 100%
Credit 25% 75%
How is credit research conducted?
How is structured/MBS-related research conducted?
How is economic and market research conducted?
How is quantitative research conducted?
How much external research do you use?
Do analysts have veto power?
Credit Research
Ryan Labs maintains a fundamental and qualitative credit research effort that provides a systematic
flow of information to the portfolio managers. This credit research process, in combination with the
technical trading function of the Asset Management team and traders, is designed to create efficiencies
for our asset management team in searching for absolute value.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 28 of 82
What separates Ryan Labs from other managers is the fact that our proprietary research is incorporated
into a methodical investment process that utilizes quantitative, qualitative, fundamental, and technical
analysis, as well as third party checks and balances. As an institutional fixed income manager, we
leverage our proprietary research and infrastructure with the vast array of data that exists on the Street.
This provides a check and balance, while enhancing our ability to customize a fixed income portfolio
regardless of mandate size, recreate benchmarks, report on a daily basis, and historically add alpha over
custom and market driven benchmarks. This combination of process, proprietary tools, and effectively
utilizing third party resources distinguishes Ryan Labs from our competitors.
Our credit research process is designed to provide:
1. Fundamental analysis
2. Peer analysis
3. Technical analysis
4. Time series analysis on individual firms
5. Economic projections of macroeconomic developments
6. Performance of various sectors within the U.S. and world economies
Ryan Labs proprietary credit research function operates in a real time and efficient environment. The
Firm strongly believes in reinvesting in our proprietary systems to maintain our competitive edge, and
to timely assess risk and return. For FY 2009, over 15% of Ryan Labs operating budget is devoted
towards enhancing our proprietary systems, and an additional 11% is devoted to augment our credit
research capabilities, including the acquisition, cataloging, and analysis of market data.
Through the use of our proprietary and third party tools, Ryan Labs implements a five-step credit
research process.
Step One: Macroeconomic Analysis
Ryan Labs' credit research is first approached from a macroeconomic perspective (domestic and
international perspective). Continuous macroeconomic data are analyzed from a plethora of sources,
which are then assimilated by the Credit Research Team. This analysis leads to the formulation of
research’s economic indicator overview and outlook.
On a recurrent basis, the Credit Research Team updates their economic outlook, sharing their insights
with the asset management team. Detailed below is a snapshot of some of the factors that are
incorporated into Ryan Labs’ credit opinions:
Economic Outlook
1
Sample Indicators (%) 2010 2Q11 2011F Commentary
Gross domestic product (y-o-y)4 2.8 1.6 2.8 Threat increasing of stagflation; soft manufacturing data
Personal consumption expenditur 1.3 0.3 0.5 Consumers reigning spending; weak outlook continues
es
CPI-U Inflation2 1.5 3.4 2.9 Higher food, fuel, commodity, apparel & motor vehcile prices
Housing Prices -2.2 -5.1 -5.0 1Q marks double-dip in home prices across the nation
Unemployment Rate3 9.4 9.1 9.0 Slow improvement; "jobless" recovery anticipated
CB Index Consumer Confidence 53.3 57.6 59.5 Consumers "sour" on negative inflation, income expectations
CB Leading Economic Indicators 1.1 0.8 1.2 Global disruptions muddy outlook for economic recovery
Imports 0.8 13.0 14.4 Rise in automotive, capital goods and consumer goods
Exports 5.8 12.9 17.5 Increase: industrial supplies, materials, automotive, engines
Current Account Deficit 3.1 3.1 3.4 Rising goods deficit; mild offset w/income & services surplus
(%GDP)
US $/Euro 1.29 1.42 1.35 FX volatility impacted by Euro debt crises
Sources: DOL, OECD, BLS, IMF-IFS, BEI, Conference Board, Dept. of Commerce; NAR, Case Shiller Index, (CoreLogic HPI -7.4% May 11)
1
Note: Estimates based on information available at time of publication.
2
12 month annual rate; Bureau of Labor Statistics ; 1Q2011 q/q 1.5%, 2Q2011 q/q 0.4%
3
Current; Broader U-6 Under-employment rate estimated at 15.7%
4
12 months y/o/y; GDP grew 0.4% q/o/q in 1Q11 and 1.3% in 2Q11
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 29 of 82
Step Two: Sector Outlook
Based on Ryan Labs' proprietary Sectors database, the research team then evaluates the most recent
performance of each sector and ranks them from the best to worst performing. After analyzing the
macroeconomic data, variables are assigned to each sector to determine their anticipated direction.
The Credit Team then rates each sector according to its projected health, as Green (buy/hold), Yellow
(under review for negative action or positive opportunities), or Red (sell/avoid). The sector reports are
then presented to the asset management team for discussion and market input. The credit team reviews
thirty-eight (38) sectors in order to identify positive and negative indicators within sectors. A succinct
write-up and snapshot of the top and bottom performing sectors is provided to the asset management
team. Quarter end sector positioning versus the benchmark of our model portfolio (Broad Market
Enhanced) is detailed below:
Portfolio Index
Weighting Weighting Difference
Total 100.0 100.00 0.00
Treasury 36.49 34.30 2.19
Government-Related 6.25 11.23 -4.98
Agency 6.25 7.28 -1.03
Corporate 22.64 19.73 2.91
Industrial 8.15 10.80 -2.65
Utility 1.73 2.24 -0.51
Financial Institutions 12.76 6.70 6.06
Securitized 34.62 34.74 -0.12
MBS Pass through 18.52 32.41 -13.89
ABS 8.78 0.25 8.53
CMBS 2.37 2.08 0.29
Other 4.95 0.00 4.95
2004 2005 2006 2007 2008 2009 2010
Total Portfolio Performance 3.27 2.63 4.71 7.34 7.48 8.30 8.92
BarCap Agg 3.16 2.43 4.33 6.97 5.24 5.93 6.54
Performance Difference 0.11 0.20 0.37 0.37 2.24 2.37 2.38
Alpha Decomposition (Total Portfolio)
Total Contribution to Excess Performance (Arithmetic) 0.09 0.26 0.34 0.35 2.05 2.61 2.15
Sector Allocation 0.35 0.04 (0.06) (0.08) (0.56) 1.22 0.09
Sector/Issue Selection Interaction 0.07 (0.09) 0.11 0.11 (0.16) 0.05 (0.58)
Issue Selection (0.27) 0.34 0.25 0.20 2.83 1.47 2.94
Trading + Other (0.05) (0.04) 0.04 0.12 (0.05) (0.14) (0.31)
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 30 of 82
Alpha Decomposition
Cash Contribution to Excess Performance (Arithmetic) 0.02 0.05 0.11 0.05 0.02 0.06 0.09
Govt Related Contribution to Excess Performance (Arithmetic) 0.07 (0.20) 0.04 0.40 0.62 (0.02) (0.29)
Sector Allocation 0.02 (0.03) 0.04 (0.01) (0.41) 0.33 (0.08)
Sector/Issue Selection Interaction (0.02) (0.00) (0.00) (0.00) (0.07) 0.03 (0.10)
Issue Selection 0.19 0.07 0.09 0.35 1.04 (0.12) 0.42
Trading + Other (0.12) (0.24) (0.09) 0.06 0.07 (0.26) (0.53)
2004.00 2005.00 2006.00 2007.00 2008.00 2009.00 2010.00
Finance Contribution to Excess Performance (Arithmetic) 0.32 (0.27) 0.40 (0.14) 0.78 0.82 0.75
Sector Allocation 0.06 0.01 0.00 (0.04) 0.67 0.67 0.14
Sector/Issue Selection Interaction (0.15) (0.16) 0.09 (0.05) (0.40) (0.07) 0.12
Issue Selection (0.08) (0.28) 0.14 (0.11) 0.63 (0.04) 0.18
Trading + Other 0.49 0.16 0.17 0.06 (0.12) 0.26 0.31
2004.00 2005.00 2006.00 2007.00 2008.00 2009.00 2010.00
Industrials Contribution to Excess Performance (Arithmetic) 0.47 0.34 (0.17) 0.48 0.43 1.11 0.14
Sector Allocation 0.19 0.03 (0.06) (0.04) (0.85) 0.37 (0.02)
Sector/Issue Selection Interaction (0.02) 0.08 0.05 0.16 0.30 0.20 0.02
Issue Selection 0.01 0.14 (0.09) (0.06) 0.80 0.27 0.27
Trading + Other 0.29 0.10 (0.06) 0.42 0.18 0.27 (0.13)
2004.00 2005.00 2006.00 2007.00 2008.00 2009.00 2010.00
Utilities Contribution to Excess Performance (Arithmetic) 0.08 0.10 0.01 0.00 0.10 (0.08) (0.03)
Sector Allocation 0.02 0.01 (0.00) 0.01 0.02 (0.11) 0.01
Sector/Issue Selection Interaction 0.01 0.02 (0.00) (0.01) (0.03) (0.00) (0.21)
Issue Selection 0.01 0.04 (0.02) 0.04 0.12 0.08 0.16
Trading + Other 0.04 0.03 0.03 (0.04) (0.01) (0.05) 0.00
2004.00 2005.00 2006.00 2007.00 2008.00 2009.00 2010.00
Securitized Contribution to Excess Performance (Arithmetic) (0.87) 0.24 (0.04) (0.43) 0.09 0.70 1.49
Sector Allocation 0.06 0.02 (0.04) 0.00 (0.00) (0.05) 0.03
Sector/Issue Selection Interaction 0.25 (0.02) (0.02) 0.02 0.05 (0.12) (0.41)
Issue Selection (0.41) 0.37 0.12 (0.02) 0.24 1.29 1.92
Trading + Other (0.77) (0.14) (0.11) (0.43) (0.19) (0.42) (0.05)
5 Year Total Performance
400 6%
RL BME Absolute Return Difference (left axis) 5%
350
Total Return
Barclays Aggregate (right axis) 4%
300 3%
250 2%
1%
200
0%
150 -1%
Return Difference (bps)
-2%
100
-3%
50 -4%
0 -5%
-6%
-50
-7%
-100 -8%
Annualized 154 bps Excess return
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 31 of 82
Finance Sector Attribution
Finance 2004 2005 2006 2007 2008 2009 2010
Contribution to Excess Performance (Arithmetic) 0.32 (0.27) 0.40 (0.14) 0.78 0.82 0.75
Sector Allocation 0.06 0.01 0.00 (0.04) 0.67 0.67 0.14
Sector/Issue Selection Interaction (0.15) (0.16) 0.09 (0.05) (0.40) (0.07) 0.12
Issue Selection (0.08) (0.28) 0.14 (0.11) 0.63 (0.04) 0.18
Trading + Other 0.49 0.16 0.17 0.06 (0.12) 0.26 0.31
RL BME Finance Sector Attribution
250
RL BME Finance (left axis)
1.0%
Index Weighted Returns
Sector Allocation
Sector/Issue Selection Interaction
200
Issue Selection
0.5%
Trading + Other
150
0.0%
100
-0.5%
Index Weighted Return (bps)
50
-1.0%
0 -1.5%
-50 -2.0%
Dec-05 Jun-06 Dec-06 Jun-07 Dec-07 Jun-08 Dec-08 Jun-09 Dec-09 Jun-10 Dec-10
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 32 of 82
Industrial Sector Attribution
Basic Materials Contribution to Excess Performance (Arithmetic) 0.03 (0.01) (0.06) (0.01) 0.07 0.17 0.01
Sector Allocation 0.00 0.01 0.00 0.02 0.11 0.07 0.00
Sector/Issue Selection Interaction 0.01 0.01 0.02 0.03 (0.08) 0.08 0.08
Issue Selection 0.02 (0.01) (0.05) (0.03) 0.08 0.00 (0.06)
Trading + Other 0.01 (0.02) (0.04) (0.03) (0.04) 0.01 (0.02)
Communications Contribution to Excess Performance (Arithmetic) 0.17 0.16 (0.05) 0.20 (0.09) 0.10 0.18
Sector Allocation 0.10 0.02 (0.02) (0.00) (0.66) (0.01) 0.02
Sector/Issue Selection Interaction (0.04) 0.01 0.02 (0.08) 0.32 0.12 0.02
Issue Selection (0.04) 0.02 (0.03) (0.04) 0.08 (0.04) 0.09
Trading + Other 0.14 0.11 (0.02) 0.32 0.17 0.03 0.05
Consumer, Cyclical Total Performance (Arithmetic) 0.04 0.10 (0.02) (0.02) (0.19) 0.15 (0.02)
Sector Allocation (0.00) 0.02 0.01 0.00 0.10 0.10 0.00
Sector/Issue Selection Interaction 0.01 (0.01) (0.02) 0.08 (0.57) (0.04) (0.02)
Issue Selection 0.03 0.13 0.03 (0.07) 0.31 0.01 (0.03)
Trading + Other 0.00 (0.04) (0.04) (0.04) (0.02) 0.07 0.03
Consumer, Non-cyclical Contribution to Excess Performance (Arithmetic) 0.10 0.01 0.03 0.18 0.21 0.27 (0.03)
Sector Allocation 0.04 (0.03) (0.00) (0.06) (0.14) 0.03 (0.03)
Sector/Issue Selection Interaction (0.01) 0.01 (0.02) 0.07 0.18 0.09 (0.14)
Issue Selection (0.01) (0.02) (0.01) 0.02 0.17 0.06 0.24
Trading + Other 0.08 0.04 0.06 0.15 (0.00) 0.09 (0.10)
Energy Contribution to Excess Performance (Arithmetic) 0.09 0.10 (0.06) 0.01 (0.03) 0.13 (0.01)
Contribution to Excess Performance (Arithmetic) 0.03 0.01 (0.05) 0.01 (0.10) 0.04 (0.01)
Sector/Issue Selection Interaction 0.01 0.04 (0.01) (0.00) 0.00 (0.04) 0.00
Issue Selection 0.01 0.04 (0.01) 0.02 0.02 0.11 0.05
Trading + Other 0.04 0.02 0.01 (0.02) 0.05 0.02 (0.05)
Industrial (Capital Goods) Contribution to Excess Performance (Arithmetic) 0.03 (0.01) 0.01 0.11 0.04 0.16 0.08
Sector Allocation 0.01 (0.00) (0.00) (0.02) (0.08) 0.02 0.01
Sector/Issue Selection Interaction 0.00 0.00 0.03 0.05 0.11 0.02 0.00
Issue Selection 0.01 (0.01) (0.00) 0.03 0.02 0.12 0.07
Trading + Other 0.01 0.00 (0.02) 0.04 (0.02) (0.00) (0.01)
Technology Contribution to Excess Performance (Arithmetic) 0.00 (0.01) (0.02) 0.02 0.43 0.15 (0.07)
Sector Allocation 0.00 0.00 0.00 0.01 (0.09) 0.12 (0.02)
Sector/Issue Selection Interaction (0.01) 0.01 0.02 0.01 0.34 (0.03) 0.07
Issue Selection (0.01) (0.01) (0.02) 0.00 0.14 (0.00) (0.08)
Trading + Other 0.01 (0.01) (0.02) (0.00) 0.04 0.05 (0.04)
RL BME Industrial Sector Attribution
100 0.60%
RL BME Industrial (left axis)
Sector Allocation
Index Weighted Returns
0.40%
Sector/Issue Selection Interaction Overweight Communications / Basics
80
Issue Selection in early spring of 2009
0.20%
Trading + Other
60 0.00%
Overweight the industrial sector
-0.20%
2008, Maintained overall sector neutral posture in Corporates through 2008, adding quality
40
Swapping out of Financial Bank risk into Industrial Credit Risk names on technical weakness, as
-0.40%
Index Weighted Return (bps)
spreads stabilized in early 2009
20 and going forward -0.60%
-0.80%
0
-1.00%
-20 -1.20%
Dec-05 Jun-06 Dec-06 Jun-07 Dec-07 Jun-08 Dec-08 Jun-09 Dec-09 Jun-10 Dec-10
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 33 of 82
Securitized Sector Attribution
Securitized 2004 2005 2006 2007 2008 2009 2010
Total Performance (Arithmetic) (0.87) 0.24 (0.04) (0.43) 0.09 0.70 1.49
Sector Allocation 0.06 0.02 (0.04) 0.00 (0.00) (0.05) 0.03
Sector/Issue Selection Interaction 0.25 (0.02) (0.02) 0.02 0.05 (0.12) (0.41)
Issue Selection (0.41) 0.37 0.12 (0.02) 0.24 1.29 1.92
Trading + Other (0.77) (0.14) (0.11) (0.43) (0.19) (0.42) (0.05)
RL BME Securitized Sector Attribution
400 3%
RL BME Securitized (left axis)
350
2%
Index Weighted Returns
Sector Allocation
300 Sector/Issue Selection Interaction
Issue Selection 1%
250 Trading + Other
0%
200
150 -1%
Post Lehman collapse, RMBS sell discipline strategy prevented Overweight to CMBS /ABS
major loss Transitioning out increased upside capture
100 -2%
of non-agency
RMBS into CMBS
Return Difference (bps)
50
-3%
0
-4%
-50
-5%
-100
-150 -6%
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 34 of 82
Government Sector Attribution
Govt Related 2004 2005 2006 2007 2008 2009 2010
Contribution to Excess Performance (Arithmetic) 0.07 (0.20) 0.04 0.40 0.62 (0.02) (0.29)
Sector Allocation 0.02 (0.03) 0.04 (0.01) (0.41) 0.33 (0.08)
Sector/Issue Selection Interaction (0.02) (0.00) (0.00) (0.00) (0.07) 0.03 (0.10)
Issue Selection 0.19 0.07 0.09 0.35 1.04 (0.12) 0.42
Trading + Other (0.12) (0.24) (0.09) 0.06 0.07 (0.26) (0.53)
RL BME Government Sector Attribution
160
RL BME Government (left axis)
Index Weighted Returns
140 Sector Allocation
0.5%
Sector/Issue Selection Interaction
Issue Selection
120
Trading + Other
100
0.0%
80
Late 2008 and into 2009, Overweight the Agency / FDIC sector at spreads
60 close to 200 area in lieu of treasury securities
-0.5%
Index Weighted Return (bps)
40
20
-1.0%
0
-20
-40 -1.5%
Dec-05 Jun-06 Dec-06 Jun-07 Dec-07 Jun-08 Dec-08 Jun-09 Dec-09 Jun-10 Dec-10
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 35 of 82
Step Three: Proprietary Quantitative Analysis
Once we have completed our sector analysis, security selection is based on a series of quantitative
filters that rank every investment grade bond for every maturity cell daily. Ryan Labs proprietary
TOPS (Tactical Optimal Portfolio System) will analyze over 6,000 bonds daily and rank them by
numerous criteria, including:
Analysis Criteria Analyzed
Sensitivity Parallel shift in rates
Breakeven Non-parallel shift in rates
Ryan Ratio OAS solution filter
Yield Spreads Basis point and % spread
Yield History Spreads and 180-day horizons
The TOPS tool assists in ranking bonds from best to worst based on an average of how much their
spreads can widen relative to the "on the run" Treasury of a similar maturity/duration and still
"breakeven" in total return over four interest rate scenarios. Since Ryan Labs does not predict interest
rates, we look for bonds whose spreads can widen and still beat the Treasury over all interest rate
scenarios. For example, if Breakeven Analysis in TOPS shows equally distributed positive numbers
across each interest rate scenario (+100 bps, +50, -50, -100) the bond passes our first test of relative
value.
Additionally, TOPS provides yield spreads for the bond in question for today and the previous 30, 60,
90, 180 days in addition to the minimum and maximum spread for the 180-day period. The cheaper the
spread today relative to the average spread over the past 180 days, the more attractive the bond
becomes. In general, we subtract the spread difference from its cushion in Breakeven Analysis over
each interest rate scenario. As detailed below:
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 36 of 82
Next, TOPS will run further analysis at the issue level, comparing a corporate credit to a Treasury, in
order to determine breakeven and interest rate sensitivity characteristics, as well as the Ryan Ratio and
historical spread on the issue:
Step 4: Individual Issue Research
Once we have used TOPS to identify individual securities, Credit Research then takes a bottom-up
approach as a qualitative check and balance to verify our quantitative output. The Credit Team will
analyze key issuer information, and provide a detailed summary.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 37 of 82
An example of an issue research summary for Energy Transfer Partner follows:
Energy Transfer Partners ETP US Equity Baa3/BBB-/BBB- S/N/S
Amt Out Current Current Current Px
Bond Cusip Coupon Maturity
(MM) Price Yield Spread Source
ETP 9.0 2019 29273RAM 9 4/15/2019 650 $116.96 6.44 330 BofA
RATIOS
$MM 1Q 2010 4Q 2009 3Q 2009 2Q 2009 2009 2008 2007
Profitability
Gross Margin (%) 21% 27% 19% 39% 24% 14% 14%
Op Margin (%) 18% 25% 16% 19% 21% 12% 12%
Profit Margin (%) 13% 17% 6% 13% 15% 9% 10%
Sales Growth (%) 24% 33% -2% -29% -42% 37% -14%
Financial Strength
EBIT Coverage 3.3 3.4 1.7 2.2 2.9 4.2 4.7
CFO/Debt 15% 13% 24% 0%
FCF/Debt 5% 1% -13% 0%
L-T Debt/Capital 54% 57% 60% 57% 57% 60% 54%
Total Debt/Capital 54% 57.5% 60.0% 57.0% 57% 60% 55%
Total Debt/Assets 50% 53.0% 55.2% 52.1% 53% 53% 48%
Total Debt/EBITDA (x) 4.22 4.32 4.10 3.64
Net Debt/EBITDA 3.95 4.27 4.04 3.57
Total Debt/Equity 118% 135.2% 149.7% 132.7% 135% 151% 120%
ROA 6.0% 6.7% 8.1% 8.8%
ROCE 9.8% 20.6% 20.5% 12.2%
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 38 of 82
FINANCIALS
$MM FQ1 2010 FQ4 2009 FQ3 2009 FQ2 2009 FY 2009 FY 2008 FY 2007
BS
Cash 384 68 50 114 68 92 69
Net Fixed Assets 8,784 8,670 8,711 8,613 8,670 8,296 5,548
Total Assets 12,070 11,735 11,255 11,001 11,735 10,627 7,708
S-T Debt 41 41 46 44 41 45 47
L-T Debt 6,015 6,177 6,166 5,693 6,177 5,619 3,627
Total L-T Liab 6,171 6,312 6,292 5,818 6,312 5,719 3,728
Total Liab 6,954 7,135 7,106 6,678 7,135 6,870 4,653
Total SE 5,116 4,600 4,149 4,323 4,600 3,758 3,056
IS
Revenue 1,872 1,506 1,130 1,152 5,417 9,294 6,792
COGS 1,479 1,105 919 702 4,116 7,982 5,817
Gross Profit 393 401 211 450 1,302 1,312 975
EBITDA 428 453 259 295 1,440 1,380 1,009
- D&A 83 82 82 76 313 262 179
- Interest expense 105 110 102 101 394 266 176
Op Income (EBIT) 344 370 177 219 1,128 1,118 830
NI 240 261 72 151 792 866 676
CF
CFO 501 31 93 273 827 1,333 1,113
- CAPEX 120 45 191 257 749 2,055 1,097
CFI -266 -120 -350 -499 -1,346 -2,016 -2,158
CFF 81 107 193 234 495 793 1,088
- FCF 381 -14 -98 17 78 -722 16
DEBT MATURITIES $MM CAP STRUCTURE $MM
Yr Principal
2011 24 Loan Revolver '12 2075 122 drawn
2012 406 Sr Unsec Debt 5050
2013 350 Other Debt 479
2014 438 Acc Payable 345
2015 750 Op Leases 327
2016 125 Mkt Cap 9,146
2017 482
2018 600
2019 1,250
2020 175
2022 150
2024 175
2036 400
2037 75
2038 550
Total 5,950
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 39 of 82
RECOMMENDATION
HOLD on market overreaction and sell at ~$120 - 122 level
9.0 '19 bond is trading at $116.29, 356 bps - the widest among peers, though has average credit metrics
ETP-high beta name and mkt seems to have overreacted on the news of recent acquisition and worries about potential M&As
Recent acquisition is unlikely to have effect on rtg and ETP bondholders have priority over holdco bonds
Improved liquidity, large scale and CFs from new projects likely offset flat basis differentials and higher Capex requirements
DESCRIPTION
One of the largest diversified midstream MLPs, largest TX intrastate natural gas pipeline system, HQ in Dallas, TX
17,500 mi of pipelines in TX and LA, 3rd largest marketer of propane in US
Energy Transfer Equity (ETE) controls ETP thru GP and owns 28% of common units and all incentive distribution rights
09 CFs equity distributions to GP - 37% (high), to LPs - 63%
Strategy: Acquisitions, pipeline construction, diversifying into interstate mkts
'09 Revenue - $5.4bn, current mkt cap - $9.1bn
SECTOR
Pipelines - Positive
+ Exp strong FCF from lower capex (25+ % down from '08) and newly contracted projects
+ Min exposure to consumer, European/FX issues, slow econ recovery or double dip given defensive profile
+ Strong equity issuance to support growth capex
+ Large cushion of equity distributions that can be cut in times of distress
+ Stable debt levels and lower capex (though increasing) after 3 yrs of non-stop growth
- Low basis differential environment, TX basis collapse may be a structural mkt change
- Overreliance on NGl processing spreads
- Overaggressive payouts to equity holders; CFs used to pay equity holders vs debt reduction
STRENGTHS
+ Strong brand, scale allows competitive shipping rates, save on fuel and op costs and arbitrage gas pricing across its system
+ Credit metrics ~ avg for the group: improved liquidity with $384mn cash & $2bn revolver, $780mn maturities next 3 yrs, 3.3x int. cover, debt high but avg for industry
+ Mgmt claimed focus on preserving IG status, long history of protecting BS when completing large deals
+ Transfer of MEP is tax-efficient and neutral for rtg
+ ETP bondholders have priority over ETE
+ New project will provide diversification and signif. CFs in n-t
NEGATIVES
- Controlled by ETE, more interested in increased cash distributions to itself than ETP internal growth needs (CAPEX)
- High Capex requirements to build several new projects
- Relies on arbitrage in gas pricing at various mkt hubs, but TX basis differentials are flat
- High beta due to acquisitive profile
- Non-diversified pipeline system, but new project will provide diversification in n-t
- Weakest n-t CFs vs large cap MLP peers in terms of retained CFs. Retained CFs - portion of LTM FFO after interest but before changes
RISKS
* Another M&A deal
* CFs distributions much over 50% to GP --> increased cost of capital
* Slower oil and gas demand growth
* ETE mgmt will steer future growth to RGNC vs ETP
ENERGY TRANSFER EQUITY (ETE) Ba1/BB-/BB-; N/S/S
+ ETE bonds subordinated to ETP debt
+ Increased scale and diversification post acquisition
- Another M&A maybe on its way
- Increased consolidated debt profile, incl $1.2bn RGNC debt and $300mn of preferred units issued to GE Financial
- Est Debt/Ebitda ~ 5.5x, debt likely to remain elevated given conflict b/n ETE's call for growing distributions and MLP's growth needs
- ETE's debt supported by ETP CFs and now also from RGNC. '09 ETP cash pmts to ETE General Partner were 27%
EVENTS
* May'10 MEP/RGNC acquisition: ETE will own 28% of 50mn LP units, 1.8% GP stake and all of the incentive distribution rights
VALUATION
Stock at $46.37, until last few days has been underperforming S&P and Holdco ETE
Pipelines have slightly outperformed HG Corporates last couple weeks.
Avg Pipelines CDS trades at 159bps vs CDX IG at 116bps
ETP has highest yield and CDS spread vs peers, but average credit metrics. Eg BPL'19 with similar credit metrics trades at 242 bps vs 299 for ETP 9.0 '19
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 40 of 82
Ticker Coupon Maturity Price Yield↓ Sprd ZSprd CDS Basis S&P Moody O/S
ETP 9.7 3/15/2019 119.84 6.66 355 383 232 -151 BBB- Baa3 600
ETP 9 4/15/2019 116.29 6.53 356 383 232 -92 BBB- Baa3 650
BWP 5.2 6/1/2018 96.83 5.7 259 289 BBB- Baa2 185
ETP 6.7 7/1/2018 107.06 5.59 248 280 232 -47 BBB- Baa3 600
EEP 9.875 3/1/2019 129.43 5.55 244 272 171 -101 BBB Baa2 500
BPL 5.5 8/15/2019 99.77 5.53 242 254 BBB Baa2 275
BWP 5.75 9/15/2019 102.25 5.44 232 245 BBB- Baa2 350
KMP 9 2/1/2019 124.29 5.42 231 258 177 -82 BBB Baa2 500
PAA 5.75 1/15/2020 103.28 5.31 219 227 174 -53 BBB- Baa3 500
KMP 6.85 2/15/2020 112.59 5.17 206 215 177 -39 BBB Baa2 700
EPD 5.25 1/31/2020 101.17 5.09 198 204 BBB- Baa3 500
OKS 8.625 3/1/2019 124.83 5.05 194 219 164 -55 BBB Baa2 500
SE 5.65 3/1/2020 104.60 5.04 193 199 100 -99 BBB Baa2 300
PAA 8.75 5/1/2019 126.29 5.03 192 215 174 -41 BBB- Baa3 350
EPD 6.5 1/31/2019 110.13 5.03 192 214 BBB- Baa3 700
WPZ 5.25 3/15/2020 102.49 4.92 180 185 163 -23 BBB- Baa3 1500
SE 6.2 4/15/2018 108.53 4.87 176 209 100 -109 BBB Baa2 500
EEP 5.2 3/15/2020 102.70 4.85 173 177 171 -6 BBB Baa2 500
ROCKIE 6.85 7/15/2018 113.31 4.83 172 203 BBB Ba1 550
WPZ 6.05 6/15/2018 108.18 4.8 163 BBB- Baa2 250
MMP 6.55 7/15/2019 113.02 4.76 164 180 129 -51 BBB Baa2 550
MMP 6.55 7/15/2019 113.07 4.75 164 180 129 -50 BBB Baa2 550
EPD 5.2 9/1/2020 104.16 4.68 156 155 BBB- Baa3 1000
KMP 5.95 2/15/2018 108.32 4.64 153 188 177 -12 BBB Baa2 975
CNP 6 5/15/2018 110.23 4.45 133 165 116 -49 BBB Baa3 300
CNP 6 5/15/2018 110.18 4.45 133 165 116 -49 BBB Baa3 300
Comp. Avg 7.053 3/29/2019 5.14 204 224 163 -62
COMPARABLE METRICS
Debt Net Debt Debt
Ticker Rtg Int Cover CFO/Debt Op Margin
/Capital /Capital /EBITDA
WPZ BBB- 1.7 0.82 0.70 6.8 0.20 21.6
BWP BBB 2.3 0.48 0.47 6.0 0.13 33.3
ETE BB- 2.3 0.71 0.70 5.4 0.09 20.5
CNP BBB 1.7 0.79 0.71 5.4 0.18 13.6
PAA BBB- 3.3 0.56 0.55 5.1 0.07 4.2
BPL BBB 3.8 0.58 0.57 4.8 0.03 17.0
SE BBB+ 2.3 0.56 0.55 4.8 0.18 32.2
KMP BBB 3.7 0.62 0.61 4.6 0.19 21.6
EEP BBB 2.4 0.50 0.48 4.6 0.18 10.8
EPD BBB- 2.6 0.53 0.53 4.4 0.21 6.9
ETP BBB- 2.8 0.57 0.57 4.3 0.13 20.8
MMP BBB 4.0 0.58 0.58 4.3 0.16 29.1
WMB BBB- 2.2 0.48 0.37 2.8 0.31 17.9
CORPORATE STRUCTURE AND ACQUISITION DETAILS
Energy Transfer Equity (ETE), Ba1/BB-/BB-; N/S/S
Controls (GP) Controls (GP))
Owns 22% common units Owns 28% common units
Regency Energy Partners (RGNC) Ba3/BB-; P/*+ Energy Transfer Partners (ETP), Baa3/BBB-/BBB-; S/N/S
bought 49.9% MEP
ETE sold MEP via redeemed ETP common units
Midcontinent Express Pipeline (MEP)
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 41 of 82
Step Five: Update and Monitor Approved List
On a daily basis, the Analysts access various databases linked to the issuer’s financial reports, adjust the
data to create pro-forma scenario analyses and sensitivity cases which indicate the implied direction of
the issuers' credit ratings under different economic assumptions. The Approved List will then be
revised on the team's consensus as to whether the issuers qualify to remain "Approved," "Suspended,"
or "Special Review." The Credit Analysts also subscribe to a number of NSRO providers of research, as
well as numerous independent services, which are e-linked to provide bulletins to the analyst
throughout the day, including Moody's, S&P, Fitch, Egan-Jones, CreditSights, Wall Street Journal, and
Financial Times. Research reports, government releases and raw statistics are gathered from industry
organizations and national agencies, such as the Conference Board, The Department of Commerce
Bureau of Economic Indicators., and National Bureau of Economic Research
The Credit Department filters the alerts and releases and forwards items of interest or concern
immediately to the Asset Management Department throughout the day. Based on the alerts,
commentaries, and market news of the day, the analysts will then review daily market movements in
Bloomberg and evaluate how the markets and individual issuers are interacting. The Credit Team
provides credit reports on any new issuances under consideration for investment, sector peer group
entities who may not qualify as investment grade candidates (cross-overs) but whose influence in the
group may impact other holdings, and commentary for clients on credit events. After the above process,
issuers which are determined to be on the cusp of further rating change, are then individually researched
in depth. The Analysts proceed to evaluate the company's financial statements and peer group
fundamentals to determine the probability of a credit event. The Approved List is revisited and adjusted
based upon the Analysts' findings.
Trading Buy/Sell Process
Through Ryan Labs proprietary DAILY system, the performance of each maturity cell in a portfolio can
be compared to the performance of the corresponding maturity cell in the Benchmark Index. This is
monitored every single day by the portfolio managers and analysts. SMART calculates individual
bond performance daily, monthly, year to date, and annually. If there is over or underperformance in
any cell, Ryan Labs proprietary SMART system allows our portfolio managers and analysts to pinpoint
the bond or bonds responsible for the performance. These bonds are then held or sold on the basis of:
Sensitivity
Breakeven
Ryan Ratio
Yield Spreads
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 42 of 82
a. Agency RMBS
Within the Agency MBS space the starting point is the universe of assets defined by the Barclays
Aggregate Index. This covers both mortgage pass through securities issued by the US Government
sponsored entities Freddie Mac, Fannie Mae and Ginnie Mae and covers both fixed and floating rate
collateral of various underwritten term but dominated by bonds surrounding the “prevailing current
coupon rate”.
The markets large size (comparable to the Treasury and Agency Debt markets), ample liquidity and a
deep repo financing market make it a key driver of broad interest rates and relative value across the
space. Ryan Labs tracks the markets technical via our SMART product which replicates the universes
on a daily basis allowing us transparence to the key component of risk and return across the space.
MBS Relative Value
1.Treasuries 2.
Agency Debt 3.
Swaps 4.
Swaption
Volatility 5. Repo
finance rates
1. Program
(FNMA, GNMA,
Ect.) 2. Structure
(15yr vs 30yr) 3.
Coupon rate.
Lender requirments, Capasity and Borrower Ability, loan to Value,
Refinancebility underwriting quality Debt to Income, Loan Size
Inventory stock, Growth and
Asset Outlook Home Prices, Employment, Inflation
Turnover
Exposure across coupon stack and
Optimal Prepay Portfolio programs Specified Pools vs. TBS
As Agency MBS implies the full faith and credit of the US Government with respect to timely payment
of principal and interest to the investor, credit risk is not a significant driver of performance.
Performance of the aggregate tends to be largely influenced by relative value across the rate universe
with includes all competing rate products; US Government Bonds, Agency Debt Swaption volatility
and financing rates, all natural substitutes and hedges. Daily replication of these markets allows us to
track supply and demand and the evolution of trends in equilibrium prices and is the first layer of our
Top Down mortgage process.
Where relative value across the rates sectors will determine the allocation to the MBS sector, the
fundamentals of the Prepayment function will determine the inter-sector allocations and security
selection in our optimal prepay portfolio. To enable this process we source the economic indicator key
to the Housing sector, broadly split between those that track loan origination and those that track the
real estate asset. These economic statistics are combined with loan level performance data as the key
inputs for pricing the universe and determine relative value on index constitutions (security level rich
cheap analysis). Sequential and planned amortization classes of agency backed CMO are included in
this analysis. Interest only and principal only classes of CMOS are excluded from our model portfolios.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 43 of 82
b. Non-Agency RMBS,
The Non-Agency RMBS space defined by mortgage loan collateral which would not conform to GSE
underwriting standards due to attributes like loan size, leverage or borrower credit. These securitization
do not derive their credit support from a government sponsored entity rather it is a function of the
subordinations’ structure. Deal structuring has been non-standardized and all potential investments
must be reverse engineered in house based upon the deal prospectus and current collateral performance.
Both RMBS and CMBS deals could have multiple structures, and one structure’s assets could have
multiple collateral groups. This one-to-many relationship is true in most cases, except for master trusts
(applicable to ABS). Credit supports usually come in the form of subordination, overcollateralization
or both. There are other types of credit supports such as bond insurance and guarantees, which Ryan
Labs as a matter of policy does not value. We are primarily looking at two types of credit supports:
subordination and OC(overcollateralization), and we will only purchase it when we can get it as a
significant discount and at several multiples to existing loan performance metrics.
The calculation of credit support and excess spread is conducted on a structure by structure basis. That
is, for a single deal, there could be multiple sets of calculations for credit support and excess spread.
Subordination for a particular tranche measures the size of the tranches that would absorb losses before
the tranche in question does.
OC can be considered as the difference between relevant collateral balance and the sum of all regular
classes. Regular class refers to those classes where “Class_Type” is NOT “IO”, “Residual”, “OC” or
“Prepayment Penalty”. The following exhibits shows a typical 2005 RMBS securitization followed by
an update of the structural change resulting from realized collateral performance (prepayment,
voluntary and defaults liqudations, recoveries and delinquencies).
A two structure Deal: CSFB_ARMT_2005_4
Structure 1 Structure 2
6-A-2-1
Collateral group 1~6
7-A-1-1
7-A-3-1
7-A-3-2
1-A-1
2-A-1
3-A-1
4-A-1
5-A-1
7-A-2
6-A-1
6-A-2-2
7-A-1-2
7-A-4
C-B-1 7-M-1
C-B-2 7-M-2
C-B-3 7-M-3
7A,7B
group
Collateral
C-B-4 7-M-4
C-B-5
C-B-6 7-X
C-B-7
Class AR, AR-L, and P are irrelevant classes in the credit support/subordination picture
Graph 2
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 44 of 82
Certificates for structure 1:
At Securitization (April 2005) Current Stratification (Sept 2009)
Coupon
(Initial Subordination/C Realized Subordination/C
Bonds Class Yield) Original Balance Size (%) redit Support Current Balance Writedowns Rating redit Support
ARMT 2005-4 1A1 1-A-1 4.304021 58,140,000 9.72% 5.60% 18,466,467 - A 9.46%
ARMT 2005-4 2A1 2-A-1 4.998703 110,725,000 18.51% 5.60% 54,622,606 - A+ 9.46%
ARMT 2005-4 3A1 3-A-1 4.947324 69,960,000 11.69% 5.60% 39,966,437 - A+ 9.46%
ARMT 2005-4 4A1 4-A-1 5.271982 116,750,000 19.52% 5.60% 76,351,766 - AA- 9.46%
ARMT 2005-4 5A1 5-A-1 4.162238 69,095,000 11.55% 5.60% 14,960,185 - A 9.46%
ARMT 2005-4 6A1 6-A-1 5.265623 70,035,000 11.71% 5.60% 28,395,698 - A 9.46%
ARMT 2005-4 6A21 6-A-2-1 5.265623 63,030,000 10.54% 15.04% 25,555,520 - A 18.52%
ARMT 2005-4 6A22 6-A-2-2 5.265623 7,005,000 1.17% 5.60% 2,840,178 - A 9.46%
ARMT 2005-4 CB1 C-B-1 4.987027 9,570,000 1.60% 4.00% 9,414,343 - B- 6.20%
ARMT 2005-4 CB2 C-B-2 4.987027 11,665,000 1.95% 2.05% 11,475,268 - CCC 2.22%
ARMT 2005-4 CB3 C-B-3 4.987027 3,290,000 0.55% 1.50% 3,237,575 - CC 1.10%
ARMT 2005-4 CB4 C-B-4 4.987027 1,795,000 0.30% 1.20% 1,768,175 - CC 0.48%
ARMT 2005-4 CB5 C-B-5 4.987027 2,695,000 0.45% 0.75% 1,398,000 - D 0.00%
ARMT 2005-4 CB6 C-B-6 5.048352 2,690,000 0.45% 0.30% - 2,690,000 NA
ARMT 2005-4 CB7 C-B-7 5.286294 1,801,590 0.30% 0 - 1,801,590 NA
Price Average Life Bond Loss
Bonds Base Case Stress Xstress Base Case Stress Xstress Base Case Stress Xstress
ARMT 2005-4 1A1 77.5 52.4 27.5 4.3 5.1 2.9 0.7 8.3 22.4
ARMT 2005-4 2A1 78.1 53.0 28.1 4.4 5.2 3.0 1.1 12.9 34.9
ARMT 2005-4 3A1 80.5 55.5 30.4 4.5 5.3 3.1 1.3 14.9 40.5
ARMT 2005-4 4A1 82.0 56.5 31.0 4.9 5.8 3.5 1.6 17.7 47.3
ARMT 2005-4 5A1 77.5 51.5 26.2 4.1 4.8 2.8 0.5 5.9 15.6
ARMT 2005-4 6A1 77.5 52.1 27.3 4.5 5.3 3.1 0.9 10.8 28.9
ARMT 2005-4 6A21 77.8 54.3 29.0 4.6 5.4 3.1 0.5 8.9 28.0
ARMT 2005-4 6A22 74.0 31.9 11.9 3.5 1.7 0.9 5.0 27.9 36.9
ARMT 2005-4 CB1 22.7 8.9 5.2 4.4 1.3 0.8 89.2 96.5 97.5
ARMT 2005-4 CB2 13.7 6.7 4.8 2.1 1.0 0.7 95.1 97.1 97.6
ARMT 2005-4 CB3 9.1 5.2 4.3 1.2 0.7 0.6 96.7 97.5 97.7
ARMT 2005-4 CB4 7.6 4.7 4.3 1.0 0.7 0.6 97.1 97.7 97.8
ARMT 2005-4 CB5 6.8 4.4 4.3 0.9 0.6 0.6 51.2 51.5 51.5
ARMT 2005-4 CB6 NA NA NA NA NA NA NA NA NA
ARMT 2005-4 CB7 NA NA NA NA NA NA NA NA NA
Base Case : Current value 18 CPR, 13 VPR, 6 CDR, 60+Delq 12, 8 Flcr, 40 Recov
Some key points here are that all classes of the structure have been downgraded and the bottom two
tranches have been completely written down, while subordination on the most senior ones have
improved. However the current collateral performance has deteriorated so drastically that our model
forecasts a principal writedown to the senior bonds in the base case scenario. Note: Ryan Labs only
invests in senior and supersenior sequentials classes expected to maintain an Investment grade rating
over the life of the investment with zero principal write-down.
c. CMBS
Structurally CMBS shares many similar to RMBS in that credit support is derived from class
subordination. One differences is that class claims on collateral cash flows are not rule and trigger
dependant in CMBS as is so often the case in RMBS. Another main difference is that CMBS loan
portfolio performance is far less homogenous in times of stress due in part to the wide variety of tenant
businesses. After the structural components of a CMBS deal are modeled, a fundamental credit analysis
must be completed across three tiers of deal counterparties.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 45 of 82
Top New Loans Added to Watchlist # Curr Bal %
Lakewood Towne Center 1 25200000 0.88 1) The tenants leasing space, payee to the Property
Village Park Apartments 1 16500000 0.58
Aspen Place Apartments 1 7734755 0.27
owner. This analysis begins at the macro level tracking the
200 North Green Briar
Walgreens - Joliet, IL
1
1
7367248
3568966
0.26
0.12
outlook for GDP, Capacity Utilization, personal income and
ALL (7) 7 64434938 2.25 employment, Consumer Spending and Confidence, Sales,
Top New Non-Performing Loans # Curr Bal % Inventory and investment. Emphasis is paid to the
Preston Creek 1 25600000 0.90
Village Park Apartments 1 16500000 0.58 interrelationship between the macro variables and the
Maple & Telegraph Shopping Center 1 7500000 0.26
Surrey Oaks Apartments 1 4257950 0.15 sectors related to CMBS borrowers (Retail, Mult-Family,
ALL (4) 4 53857950 1.88
Office, Hotel, Hospital, Industrial). This analysis is further
Top Loans Due Next 12 mos
Gateway Plaza
#
1
Curr Bal
98780516
%
3.46
disaggregated by MSA’s. The output of this process results
Commons at Temecula
Page Field Commons
1
1
29623024
26853024
1.04
0.94
in cohort pools with a nationwide breakdown by sector,
Jefferson Estates on Maryland
Trenton Crossing
1
1
19740000
19307037
0.69
0.68
benchmarking key metrics of leverage, business unit
ALL (22) 22 331069693 11.58 performance, debt service capacity, refinance bottlenecks
Top MSAs with NonPerf Loans # Curr Bal % and the distribution of underwriting and servicing standards.
Atlanta-Sandy Springs-Marietta, GA 2 26855942 0.94
Indianapolis-Carmel, IN 1 16500000 0.58 The cohort pools are used to determine relative value across
Tallahassee, FL 1 13100839 0.46
Detroit-Warren-Livonia, MI 1 7500000 0.26
the underlying Tenants in individual Bonds.
Eugene-Springfield, OR 1 7035101 0.25
ALL (11) 11 90277920 3.16
Top Property Types with NonPerf Loans # Curr Bal %
2) The property owners, payee to the Trust. Property
Multi Family Housing 5 61,102,208 2.14 owners often take the form of REITS and often span the
Retail Anchored 3 14,791,090 0.52
Office 1 7,035,101 0.25 universe of CMBS securitization, further in some cases due
Hospitality Full Service 1 6,093,579 0.21
Retail Unanchored 1 1,255,942 0.04 to scale the same property may exist in a large number of
ALL (11) 11 90,277,920 3.16
deals increasing a risk layering. Exposure to individual
Top New Loans Added to Watchlist
Lakewood Towne Center
#
1
Curr Bal
25,200,000
%
0.88
properties and owners must be monitored. Apart from
Village Park Apartments
Aspen Place Apartments
1
1
16,500,000
7,734,755
0.58
0.27
exposure our corporate credit team does a full corporate
200 North Green Briar
Walgreens - Joliet, IL
1
1
7,367,248
3,568,966
0.26
0.12
credit analysis on the owners debt when available.
ALL (7) 7 64,434,938 2.25
Top New Loans Added to Watchlist # 3) The Trustee, Servicer (master and special) and
Curr Bal %
Lakewood Towne Center 1 25,200,000 0.88
Village Park Apartments 1 residual owner. A review must be completed on the group
16,500,000 0.58
Aspen Place Apartments 1 7,734,755 0.27
200 North Green Briar 1
assigned the responsibility to represent investor interest.
7,367,248 0.26
Walgreens - Joliet, IL
ALL (7)
1
7
We continually monitor the actions taken by these parties in
3,568,966
64,434,938
0.12
2.25
fulfilling their function to maximize the value of the trust
without distorting the risk profile between senior and subordinate note holder. This review is an
ongoing process allowing for frequent grading of Trustees and Servicers and an open dialogue with
these participants.
At Ryan, ABS investments mean Consumer Credit (Credit Card Trusts, Auto Loan and Lease pass-
through pools and Home Equity pools) and to a lesser extend Commercial Credit (Utility Rate pass-
throughs, fright and airline receivables).
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 46 of 82
There are approximately 200+ names on the approved list of securities which asset management team
would trade on. Analysts access various data bases linked to the issuer’s financial reports, adjust the
data to create proforma scenario analyses and sensitivity cases which indicate the implied direction of
the issuers' credit ratings under different economic assumptions. The Approved List will then be
revised on the team's consensus as to whether the issuers qualify to remain "Approved," "Suspended,"
or "Special Review."
The Credit Analysts also subscribe to a number of NSRO providers of research, as well as numerous
independent services, which are e-linked to provide bulletins to the analyst throughout the day,
including Moody's, S&P, Fitch, Egan-Jones, CreditSights, Wall Street Journal, and Financial Times.
Research reports, government releases and raw statistics are gathered from industry organizations and
national agencies, such as the Conference Board, The Department of Commerce Bureau of Economic
Indicators., and National Bureau of Economic Research. The Credit Department filters the alerts and
releases and forwards items of interest or concern immediately to the Asset Management Department
throughout the day. Based on the alerts, commentaries, and market news of the day, the analysts will
then review daily market movements in Bloomberg and evaluate how the markets and individual issuers
are interacting.
The Credit Team provides credit reports on any new issuances under consideration for investment,
sector peer group entities who may not qualify as investment grade candidates (cross-overs) but whose
influence in the group may impact other holdings, and commentary for clients on credit events.
After the above process, issuers which are determined to be on the cusp of further rating change, are
then individually researched in depth. The Analysts proceed to evaluate the company's financial
statements and peer group fundamentals to determine the probability of a credit event. The Approved
List is revisited and adjusted based upon the Analysts' findings.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 47 of 82
31. Please list portfolio and analytical tools used in the management of this product.
Investment Process: The Ryan Labs investment process is a daily / monthly system of gears. These
systematic steps ensure that the process is clearly defined, repeatable and documented for the client.
Stage Product Purpose
1. Client Objective
2. Index Replication SMART Index Replication Model
3. Sector Analysis
4. Issue Analysis
TOPS Tactical Optimal Portfolio System
5. Credit & Mortgage Research
6. Risk control
7. Attribution PASS Performance Attribution Model
8. Reporting DAILY Daily Performance Measurement Model
MANIFOLD Daily Custom Internet Delivery System
32. In the portfolio construction process, what is the role of macro-economic research?
Macro-economic research is used to develop forecasts of cyclical and secular trends in the US and
global economy. This helps to identify industry and financial sectors which have either an improving,
declining or stable economic outlook. Within the sectors, the financials for specific issuers are then
evaluated to determine their credit-worthiness. An Approved List of investment grade issuers is
developed and maintained daily for portfolio construction.
33. Are there any constraints on duration? What are the typical yield curve strategies that the team
utilizes?
Ryan Labs aims for a duration neutral strategy. We do not add value by speculating interest rate move.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 48 of 82
34. Please describe the credit quality distribution in the portfolio and any restrictions that may apply
noting whether they are by prospectus or simply typical of the process.
All Ryan Labs bond portfolios contain only US investment grade bonds, with credit quality ranging
from AAA to A (see below table), unless otherwise dictated by client’s IPS.
35. What is the initial universe used to screen for potential issues? What methods are used to narrow the
initial universe?
Ryan Labs evaluate all securities found in Barclays Capital Aggregate Universe and dismiss securities
which are not part of client’s investment policy.
Methods of issue selection include:
Bottom to top approach for sector narrowing, credit screening
TOPS and Credit Research for individual security evaluation (please refer to investment decision
process for details)
36. How does the firm determine the relative cheapness/richness of various asset classes (sectors)?
As domestic investment grade fixed income manager, we:
Employing RL proprietary quantitative model (TOPS, SMART, SECTOR), which signal the
relative cheapness/richness of various sector;
Look at various macro/micro economic signals, since different sector inherently reacts differently to
macro/micro events;
Conduct credit research on sector and issue level;
Examine re-financiability and prepayment dynamic as related to the mortgage sector;
Look at the underlying factor of credit and structure within the consumer/asset-backed sectors.
37. What factors initiate a sell? A trim?
SMART (BUY & SELL INDICATOR)
Ryan Labs neutralizes interest rate risk by matching the term structure of the Benchmark Index within a
2 % tolerance by maturity cell. This is accomplished with Ryan Labs proprietary SMART system.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 49 of 82
DAILY (BUY & SELL INDICATOR)
Through Ryan Labs proprietary DAILY system, the performance of each maturity cell in a portfolio can
be compared to the performance of the corresponding maturity cell in the Benchmark Index. This is
monitored every single day by the portfolio managers and analysts.
If there is over or underperformance in any cell, Ryan Labs proprietary SMART system allows our
portfolio managers and analysts to pinpoint the bond or bonds responsible for the performance because
it calculates individual bond performance daily, monthly, year to date, and annually. These bonds are
then held or sold on the basis of:
1. Sensitivity
2. Breakeven
3. Ryan Ratio
4. Yield Spreads
5. Yield History
6. Credit research
Factors initiating a sell or a trim:
Swap securities to realize economic benefit;
Rebalance portfolio so to be in line with the benchmark/client objective;
Take strategic/tactical position versus benchmark (sector, issuer, issue, structure ect.);
Maintain complaint with client IPS.
V. Portfolio Construction
38. Which benchmark does the team use to manage the product?
The Long Liability Enhanced benchmark is customized client liability 7 to 10 years duration.
The Broad Market Enhanced benchmark is Barclays Capital Aggregate Index.
The Intermediate Market Enhanced benchmark is Barclays Gov’t /Credit Intermediate Index.
The Short Duration Enhanced benchmark is Merrill Lynch 1 to 3 Year Index.
39. Any non-benchmark asset classes the team invests in? Any rationale behind the investment?
Unless otherwise instructed by the client’s IPS, Ryan Labs can include up to 20% of non-benchmark
sectors. We add non-benchmark sectors when permitted in an effort to find relative value, capture risk
premiums, and diversify the portfolio in an effort to provide total return above the benchmark.
40. Are there any constraints on exposure to various asset classes (by credit, by duration, by asset
classes, etc.)?
All investment grade securities in the Barclays Capital Aggregate Universe are the base for security
selection, unless dictated otherwise by client IPS. Being duration neutral, the duration of portfolio is +/-
0.5 years the benchmark. Ryan Labs is +/- 20% by sector.
41. How many issues can the product hold?
Number of issues held in the product ranges from 80 to 150.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 50 of 82
42. What is the maximum position size? Initial position size? When would a trim be initiated?
Maximum position is $250 million issue size, unless the issuer has total outstanding funded debt of $1
billion or more. In this case the minimum issue size is reduced to $100 million. For the purchase of
medium-term notes, the minimum issue size is $50 million, subject to the total outstanding funded debt
of at least $1 billion.
43. What is the maximum cash position allowed and how it is managed? What is the typical cash level?
Maximum cash position allowed is 3%, unless liquidity notifications have been sent in advance. Typical
cash levels are around 1%. We aim to keep the cash position minimum, and have all money invested.
44. What is the average turnover for the product? Please note that it is net currency transaction or not.
The table below details product turnover:
Average
Composite Ticker Start Date End Date Turnover
Short Duration Enhanced SDE 9/30/2006 9/30/2011 85.797%
Short Duration Enhanced G/C SGC 6/30/2009 9/30/2011 15.737%
Limited Market Enhanced LIMITED 6/30/2009 9/30/2011 84.831%
Intermediate Market Enhanced IME 9/30/2006 9/30/2011 102.306%
Broad Market Enhanced BME 9/30/2006 9/30/2011 131.037%
Government Credit Enhanced GCE 7/31/2007 9/30/2011 114.898%
Government Enhanced BGE 6/30/2008 9/30/2011 18.580%
Long Market Enhanced LME 12/31/2010 9/30/2011 31.739%
Long Government Enhanced LGE 1/31/2010 9/30/2011 18.769%
Long Credit Enhanced LCE 6/30/2009 9/30/2011 95.241%
Inflation Index Enhanced IIE 9/30/2006 9/30/2011 52.681%
Short Liability Enhanced SLE 9/30/2006 9/30/2011 68.665%
Intermediate Liability Enhanced ILE 9/30/2006 9/30/2011 63.839%
Core Liability Enhanced CLE 9/30/2006 9/30/2011 66.288%
Long Liability Enhanced LLE 9/30/2006 9/30/2011 57.033%
Very Long Liability Enhanced VLLE 9/30/2006 9/30/2011 132.218%
Inflation Index Intermediate III 9/30/2006 9/30/2011 38.107%
45. Are derivatives used in the management of this portfolio? To what extent will these be used? And
under what circumstances will these instruments be used? Can leverage be employed in portfolios?
Derivatives are not used in the management of this product.
46. How are securities handled that have been downgraded from investment grade to non-investment
grade?
Must these securities be sold automatically?
If a security in a client’s portfolio is downgraded to non-investment grade, we will
notify the consultant first, schedule a call to review the security and the reasons for the
downgrade, and determine the most prudent course of action.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 51 of 82
Are there limits on what percentage of the portfolio these non-investment grade
securities can represent?
Ryan Labs does not invest in non-investment grade securities in these strategies.
What is the lowest credit rating (B by S&P for example) that mandates an automatic
sell?
All securities must be rated investment grade by at least two of the three major rating agencies
(Moody’s, S&P and Fitch) to be allowed in the portfolios. The lowest ratings permitted are
Baa3 and BBB-, as shown in below table:
Investment Grade Bond Ratings
Moody’s Grades S&P Grades
Baa3 BBB-
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 52 of 82
47. Portfolio construction parameters - including sector and security constraints; quality, maturity and
duration constraints for fixed income; active risk guidelines (tracking error); etc. Please complete
the table below and enter any additional information in the space provided.
Portfolio Construction / Risk Controls
Average Number of Holdings (issues) (counting
100
funds as individual holdings)
Average Number of Holdings (issues) (include
100
holdings within funds as individual holdings)
Average Number of Holdings (Issuers) 100
Duration range (years) +/- 0.5 Year versus benchmark (soft rule)
Duration range (as percent around index) 5%
Maturity range that is allowed to be held or
0 to 30 years
purchased
Minimum credit quality – average portfolio AA- (S&P grading) / Aa3 (Moody’s grading)
Minimum credit quality – per issue BBB+ (S&P grading) / Baa3 (Moody’s grading)
Minimum credit quality – at purchase BBB+ (S&P grading) / Baa3 (Moody’s grading)
Annual turnover range 50% to 100%
Maximum exposure per issuer/issue 10%
Maximum exposure per issuer/issue at
10%
purchase
Maximum corporate sector exposure (autos,
20%
financials..etc.)
Use of Derivatives No
$250 million issue size unless the issuer has total
outstanding funded debt of $1 billion or more. In
this case the minimum issue size is reduced to $100
Is there a Minimum Issue Size that must be
million. For the purchase of medium-term notes,
outstanding before the issue is considered?
the minimum issue size is $50 million, subject to
the total outstanding funded debt of at least $1
billion.
Liquidity / Volume policy
Maximum cash 3%
Currency Exposure None.
Sector Ranges Min Max Normal
Treasuries 50 100 50
TIPS 50 100 50
Agencies 10 50 25
Pass-throughs
CMOs
CMBS 0 7 3
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 53 of 82
Asset-Backed 0 8 3
Invest. Grade Corporates 60 40
Below BBB
Foreign – Developed
Foreign – Emerging
Cash
Municipals
Other
48. Are the sector percentages listed in the above table formal limits or probable sector ranges?
The sector percentages listed in the above table are probable sector ranges.
VI. Historical Portfolio Data: Please fill out the data of the past 8 quarters in the tables below.
A.) For All products: Product Profile (starting with the most recent quarter from the left).
Long Liability Enhanced (LLE)
9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010 12/2009
Average Maturity
11.76 10.91 10.66 11.49 11.73 11.92 11.10 11.14
(years)
Average Duration
7.94 7.13 7.33 7.51 7.73 7.86 7.45 7.75
(years)
Average Coupon (%) 4.01 4.13 3.97 4.02 4.32 4.16 3.72 3.87
Average Price 104.87 102.36 100.14 100.08 105.54 102.42 96.46 94.31
Yield to Maturity (%) 3.25 3.52 3.63 3.65 3.36 3.70 4.30 4.77
Average Number of
440.00 388.00 387 404 400 354 337 370
Holdings
Average Quality AA AA AA AA AA AA AAA AAA
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 54 of 82
B.) For All Products: Quality Exposures (starting with the most recent quarter from the left).
Please list quality sector exposures as a percent of fixed income holdings
*Please do not include cash in any other categories except “Cash” in the “Quality Sector Exposure”
table.
**Pl. note that % of market value including accrued interest
Quality Sectors 9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010
US Government 30.74 30.59 39.10 35.28 29.63 39.85 51.56
Aaa 2.80 1.66 2.63 4.72 4.96 7.67 9.14
Aa 17.06 16.59 15.46 13.95 12.81 8.96 8.38
A 29.92 31.90 24.99 25.58 26.78 21.70 13.82
Baa 19.47 19.26 17.83 20.46 25.82 21.67 16.85
Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00
C.) For All Products: Maturity Profile (starting with the most recent quarter from the left).
Please include cash in the bucket of “0~1 Yr”. For tax exempt products, pl. skip the second table and go
to Section G.
Maturity
9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010 12/2009
Breakdown
0~1 Yr 6.77 7.30 5.76 6.94 4.08 3.92 4.74 2.75
1-3 Yr 13.26 14.58 15.12 13.91 12.38 8.10 7.16 7.87
3-5 Yr 18.27 19.79 20.79 21.55 22.88 22.72 22.93 20.13
5-7 Yr 6.32 6.64 6.72 7.24 8.51 8.98 8.97 8.37
7-10 Yr 22.64 23.77 23.04 19.11 21.77 26.45 26.77 29.03
10+ Yr 32.75 27.91 28.57 31.25 30.38 29.83 29.43 31.84
Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00
D.) For All Products: Asset Class Exposures (starting with the most recent quarter from the left).
Please do not include cash in any other categories except “Cash”.
Asset Class Exposure 9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010 12/2009
US Treasury 26.4 27.7 37.2 32.7 28.2 41.5 49.9 41.4
US Gov't. Agency 2.0 1.5 1.7 2.6 3.5 3.2 3.8 8.8
Municipal 0.4 0.4 0.5 0.5 0.4 0.4 0.4 0.2
Corporate - Industrials 35.9 32.9 27.9 34.1 40.2 33.4 20.0 22.8
Corporate - Utilities 4.8 4.0 4.0 5.3 5.6 5.9 4.3 5.2
Corporate - Financials 23.1 27.8 23.0 17.8 17.1 12.0 14.1 12.5
Non-Corporate 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Mortgage 2.4 2.2 2.7 2.9 1.7 1.0 0.7 5.7
Asset-Backed 2.0 1.5 2.0 2.2 2.0 1.1 1.5 1.7
Non Dollar 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Cash Equivalents 3.0 1.9 0.9 2.0 1.3 1.5 5.4 1.6
Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00
*Please specify what is included in “Other”
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 55 of 82
Broad Market Enhanced (BME)
9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010 12/2009
Average Maturity 6.74 6.81 7.50 7.26 6.82 6.45 6.70 6.10
(years)
Average Duration 5.08 5.03 5.18 5.01 4.93 4.57 4.62 4.28
(years)
3.65 3.88 4.39 4.08 4.09 4.40 4.15 4.22
Average Coupon (%)
106.15 103.15 102.14 102.66 105.77 104.45 101.12 99.66
Average Price
2.81 3.06 3.75 3.23 2.77 3.37 3.77 4.11
Yield to Maturity (%)
Average Number of 302.00 299 266 299 302 326 242 244
Holdings
AAA AAA AAA AAA AAA AAA AAA AAA
Average Quality
E.) For All Products: Quality Exposures (starting with the most recent quarter from the left).
Please list quality sector exposures as a percent of fixed income holdings
*Please do not include cash in any other categories except “Cash” in the “Quality Sector Exposure”
table.
**Pl. note that % of market value including accrued interest
Quality Sectors 9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010
US Government 61.09 54.32 47.32 54.68 59.11 46.29 60.91
Aaa 11.45 13.85 16.63 16.90 14.04 20.81 12.25
Aa 3.54 4.66 8.13 6.39 5.04 6.54 3.70
A 8.31 8.46 4.98 8.33 7.99 11.91 6.02
Baa 15.60 18.71 22.94 13.70 13.81 12.96 16.54
Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00
F.) For All Products: Maturity Profile (starting with the most recent quarter from the left).
Please include cash in the bucket of “0~1 Yr”. For tax exempt products, pl. skip the second table and go
to Section G.
Maturity
9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010 12/2009
Breakdown
0~1 Yr 19.09 16.28 16.84 19.09 14.47 20.49 23.11 11.88
1-3 Yr 20.89 19.20 18.70 27.69 30.43 23.03 25.71 30.87
3-5 Yr 27.56 32.66 32.44 20.15 25.17 24.12 14.43 20.39
5-7 Yr 9.35 9.36 8.01 6.92 8.40 14.56 15.24 11.47
7-10 Yr 11.36 11.03 10.66 12.17 9.81 6.49 8.72 14.54
10+ Yr 11.75 11.46 13.34 13.98 11.72 11.30 12.78 10.86
Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 56 of 82
G.) For All Products: Asset Class Exposures (starting with the most recent quarter from the left).
Please do not include cash in any other categories except “Cash”.
Asset Class Exposure 9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010 12/2009
US Treasury 41.9 34.4 23.1 30.5 31.8 24.9 36.7 27.8
US Gov't. Agency 5.8 7.1 9.6 11.0 11.9 4.7 4.8 7.3
Municipal 0.9 0.8 1.5 1.6 0.2 0.7 0.9 1.4
Corporate - Industrials 6.8 8.9 12.5 8.4 11.7 17.3 11.4 13.1
Corporate - Utilities 1.4 0.6 0.9 1.0 0.6 0.8 1.0 0.9
Corporate - Financials 7.3 7.2 8.9 9.1 9.1 8.5 10.9 7.2
Non-Corporate 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Mortgage 19.8 25.1 35.6 29.5 27.4 31.2 22.6 30.2
Asset-Backed 12.8 12.2 7.7 5.7 3.1 7.5 9.2 9.5
Non Dollar 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Cash Equivalents 3.3 3.7 0.3 3.2 4.2 4.5 2.5 2.5
Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00
*Please specify what is included in “Other”
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 57 of 82
Intermediate Market Enhanced (IME)
9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010 12/2009
Average Maturity 4.63 4.34 4.48 4.38 4.78 4.48 4.56 4.37
(years)
Average Duration 4.13 3.83 3.93 3.85 4.16 3.88 3.95 3.80
(years)
3.05 3.16 3.36 3.51 3.62 3.88 3.72 3.69
Average Coupon (%)
104.55 103.30 102.47 103.53 106.66 105.34 102.47 101.89
Average Price
1.68 1.83 2.28 2.22 1.83 2.33 2.98 3.08
Yield to Maturity (%)
Average Number of
470.00 463 515 553 551 338 333 301
Holdings
Average Quality AAA AAA AAA AAA AAA AAA AAA AAA
H.) For All Products: Quality Exposures (starting with the most recent quarter from the left).
Please list quality sector exposures as a percent of fixed income holdings
*Please do not include cash in any other categories except “Cash” in the “Quality Sector Exposure”
table.
**Pl. note that % of market value including accrued interest
Quality Sectors 9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010
US Government 62.08 67.49 63.86 63.48 62.33 59.51 66.22
Aaa 2.81 3.22 4.83 3.77 3.43 6.71 5.39
Aa 4.75 3.51 7.35 6.40 5.64 3.23 4.28
A 12.17 10.55 8.78 11.15 12.40 15.96 10.41
Baa 18.20 15.22 15.19 15.19 16.20 14.40 13.50
Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00
I.) For All Products: Maturity Profile (starting with the most recent quarter from the left).
Please include cash in the bucket of “0~1 Yr”. For tax exempt products, pl. skip the second table and go
to Section G.
Maturity
9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010 12/2009
Breakdown
0~1 Yr 24.69 29.46 24.85 22.91 18.79 18.55 19.91 8.58
1-3 Yr 18.71 20.23 23.77 27.38 27.56 28.80 25.56 31.06
3-5 Yr 26.94 21.78 22.09 21.99 23.81 23.05 26.29 29.31
5-7 Yr 7.23 9.93 12.57 9.49 7.15 11.30 9.18 12.24
7-10 Yr 22.42 18.59 16.48 17.99 22.10 18.29 19.03 16.81
10+ Yr 0.01 0.01 0.24 0.24 0.59 0.00 0.04 1.98
Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 58 of 82
J.) For All Products: Asset Class Exposures (starting with the most recent quarter from the left).
Please do not include cash in any other categories except “Cash”.
Asset Class Exposure 9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010 12/2009
US Treasury 56.5 59.0 55.8 53.5 53.1 46.1 52.6 48.9
US Gov't. Agency 5.6 8.3 10.1 11.1 11.3 14.9 14.4 16.1
Municipal 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Corporate - Industrials 20.0 16.6 16.0 15.9 19.9 20.3 12.5 19.0
Corporate - Utilities 2.6 1.9 1.6 1.5 2.1 1.9 0.4 0.3
Corporate - Financials 10.6 9.3 10.6 11.4 10.5 11.1 15.2 7.9
Non-Corporate 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Mortgage 0.4 1.1 3.7 3.0 1.4 1.5 1.1 3.5
Asset-Backed 1.9 1.2 1.3 1.6 0.5 2.7 2.8 3.1
Non Dollar 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Cash Equivalents 2.4 2.6 0.9 2.0 1.2 1.5 1.0 1.1
Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00
*Please specify what is included in “Other”
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 59 of 82
Short Duration Enhanced (SDE)
9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010 12/2009
Average Maturity
1.67 1.73 1.97 1.64 1.74 1.82 1.65 1.85
(years)
Average Duration
1.64 1.69 1.92 1.59 1.69 1.77 1.61 1.78
(years)
Average Coupon (%) 1.68 1.81 1.86 2.00 2.12 2.24 2.49 2.88
Average Price 101.85 101.78 101.22 101.70 102.36 102.23 101.70 101.96
Yield to Maturity (%) 0.55 0.62 0.95 0.69 0.57 0.77 1.06 1.54
Average Number of
131 126 122 122 124 97 111 111
Holdings
Average Quality AAA AAA AAA AAA AAA AAA AAA AAA
K.) For All Products: Quality Exposures (starting with the most recent quarter from the left).
Please list quality sector exposures as a percent of fixed income holdings
*Please do not include cash in any other categories except “Cash” in the “Quality Sector Exposure”
table.
**Pl. note that % of market value including accrued interest
Quality Sectors 9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010
US Government 63.74 65.83 67.83 74.45 74.52 76.23 80.70
Aaa 12.45 12.36 12.05 8.19 7.93 9.09 6.83
Aa 8.22 7.25 6.28 5.86 6.00 5.07 4.72
A 14.34 13.39 12.01 10.31 9.96 8.19 6.39
Baa 1.25 1.17 1.81 1.19 1.58 1.42 1.36
Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00
L.) For All Products: Maturity Profile (starting with the most recent quarter from the left).
Please include cash in the bucket of “0~1 Yr”. For tax exempt products, pl. skip the second table and go
to Section G.
Maturity
9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010 12/2009
Breakdown
0~1 Yr 62.28 57.13 47.15 65.59 63.30 60.69 64.67 16.18
1-3 Yr 37.36 42.53 52.49 33.48 35.73 39.31 35.33 77.23
3-5 Yr 0.01 0.02 0.06 0.57 0.57 0.00 0.00 6.60
5-7 Yr 0.01 0.01 0.01 0.01 0.02 0.00 0.00 0.00
7-10 Yr 0.33 0.31 0.29 0.35 0.38 0.00 0.00 0.00
10+ Yr 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 60 of 82
M.) For All Products: Asset Class Exposures (starting with the most recent quarter from the left).
Please do not include cash in any other categories except “Cash”.
Asset Class Exposure 9/2011 6/2011 3/2011 12/2010 9/2010 6/2010 3/2010 12/2009
US Treasury 39.0 38.4 39.5 56.7 54.8 57.7 65.9 55.5
US Gov't. Agency 36.1 37.8 39.7 24.3 26.8 27.5 21.3 20.9
Municipal 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Corporate - Industrials 14.2 12.3 10.5 9.1 8.8 6.7 5.3 13.2
Corporate - Utilities 0.9 0.7 0.7 0.7 0.7 0.3 0.2 0.6
Corporate - Financials 8.6 8.6 8.6 7.9 7.3 6.7 5.5 7.7
Non-Corporate 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Mortgage 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.5
Asset-Backed 0.0 0.0 0.0 0.0 0.0 0.1 0.4 0.6
Non Dollar 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Cash Equivalents 1.2 2.2 1.0 1.2 1.7 1.0 1.3 0.9
Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00
*Please specify what is included in “Other”
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 61 of 82
VII. Performance
1. Please discuss attribution for the past 5 calendar years, paying particular attention to those years
when the product did not perform in line with expectations.
Performance Attribution (PASS): Compares portfolio vs. Index based on a series of risk/reward
calculations
Ten (10) - Risk Measurements
Five (5) - Return Measurements
Two (2) - Risk-adjusted Return Measurements
Series of graphs comparing portfolio vs. index
Style Analysis report explains return difference
Performance Attribution Report – LLE (since Inception ending 9/30/2011)
Horizon: 06/30/91 to 09/30/11 LLE Composite Custom Liability Index (7 to 10 Year) Difference
(Portfolio) (Benchmark)
RISK
1. Annualized Standard Deviation (Volatility) % 8.49 8.74 -0.25
2. Minimum Periodic Return % -7.60 -7.92 0.33
3. Maximum Periodic Return % 9.48 9.98 -0.50
4. Beta (Sensitivity to Benchmark) 0.95
5. R-Squared % 95.67
6. Correlation % 97.81
7. Annualized Tracking Error bp 164.59
8. Shortfall Frequency % 45.68
9. Average Shortfall bp 16.52
10. Downside Capture Ratio % 90.07 100.00
REWARD
11. Annualized Total Return % 9.61 8.73 0.88
12. Average Periodic Return bp 79.76 73.17 6.59
13. Cumulative Total Return % 541.62 445.04 96.57
14. Excess Return Frequency % 54.32
15. Average Excess Return bp 26.01
16. Upside Capture Ratio % 100.17 100.00
RISK ADJUSTED RETURN
17. Sharpe's Ratio 0.72 0.60 0.12
18. Information Ratio 0.53
All series and calculations are based upon monthly returns
Portfolio = Long Liability Enhanced
Benchmark = Custom Liability Index (7 to 10 Year)
Risk Free Rate = Merrill Lynch 91 day T-Bill
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 62 of 82
Performance Attribution Report – LLE (5 years ending 9/30/2011)
Horizon: 09/30/06 to 09/30/11 LLE Composite Custom Liability Index (7 to 10 Year) Difference
(Portfolio) (Benchmark)
RISK
1. Annualized Standard Deviation (Volatility) % 7.92 8.22 -0.30
2. Minimum Periodic Return % -5.70 -4.97 -0.73
3. Maximum Periodic Return % 9.22 9.82 -0.60
4. Beta (Sensitivity to Benchmark) 0.94
5. R-Squared % 92.32
6. Correlation % 96.08
7. Annualized Tracking Error bp 175.26
8. Shortfall Frequency % 33.33
9. Average Shortfall bp 26.33
10. Downside Capture Ratio % 81.34 100.00
REWARD
11. Annualized Total Return % 9.58 7.69 1.89
12. Average Periodic Return bp 79.05 64.67 14.38
13. Cumulative Total Return % 58.00 44.86 13.13
14. Excess Return Frequency % 66.67
15. Average Excess Return bp 34.73
16. Upside Capture Ratio % 102.99 100.00
RISK ADJUSTED RETURN
17. Sharpe's Ratio 0.99 0.72 0.26
18. Information Ratio 1.08
All series and calculations are based upon monthly returns
Portfolio = Long Liability Enhanced
Benchmark = Custom Liability Index (7 to 10 Year)
Risk Free Rate = Merrill Lynch 91 day T-Bill
Performance Attribution Report – LLE (1 year ending 9/30/2011)
Horizon: 09/30/10 to 09/30/11 LLE Composite Custom Liability Index (7 to 10 Year) Difference
(Portfolio) (Benchmark)
RISK
1. Annualized Standard Deviation (Volatility) % 4.76 4.99 -0.23
2. Minimum Periodic Return % -1.71 -2.18 0.46
3. Maximum Periodic Return % 2.77 2.62 0.14
4. Beta (Sensitivity to Benchmark) 0.94
5. R-Squared % 81.77
6. Correlation % 90.43
7. Annualized Tracking Error bp 83.29
8. Shortfall Frequency % 8.33
9. Average Shortfall bp 14.44
10. Downside Capture Ratio % 68.83 100.00
REWARD
11. Annualized Total Return % 6.33 3.26 3.07
12. Average Periodic Return bp 52.16 27.70 24.46
13. Cumulative Total Return % 6.33 3.26 3.07
14. Excess Return Frequency % 91.67
15. Average Excess Return bp 27.99
16. Upside Capture Ratio % 113.44 100.00
RISK ADJUSTED RETURN
17. Sharpe's Ratio 1.30 0.62 0.67
18. Information Ratio 3.69
All series and calculations are based upon monthly returns
Portfolio = Long Liability Enhanced
Benchmark = Custom Liability Index (7 to 10 Year)
Risk Free Rate = Merrill Lynch 91 day T-Bill
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 63 of 82
Performance Attribution Report – BME (since Inception ending 9/30/2011)
Horizon: 06/30/96 to 09/30/11 BME Composite Barclays Aggregate Difference
(Portfolio) (Benchmark)
RISK
1. Annualized Standard Deviation (Volatility) % 3.91 3.61 0.30
2. Minimum Periodic Return % -3.16 -3.36 0.20
3. Maximum Periodic Return % 3.88 3.73 0.15
4. Beta (Sensitivity to Benchmark) 1.03
5. R-Squared % 89.65
6. Correlation % 94.68
7. Annualized Tracking Error bp 120.03
8. Shortfall Frequency % 42.62
9. Average Shortfall bp 18.30
10. Downside Capture Ratio % 95.83 100.00
REWARD
11. Annualized Total Return % 7.17 6.47 0.70
12. Average Periodic Return bp 58.52 52.95 5.57
13. Cumulative Total Return % 187.57 160.29 27.28
14. Excess Return Frequency % 57.38
15. Average Excess Return bp 23.30
16. Upside Capture Ratio % 106.31 100.00
RISK ADJUSTED RETURN
17. Sharpe's Ratio 1.02 0.92 0.10
18. Information Ratio 0.58
Performance Attribution Report –BME (5 years ending 9/30/2011)
Horizon: 09/30/06 to 09/30/11 BME Composite Barclays Aggregate Difference
(Portfolio) (Benchmark)
RISK
1. Annualized Standard Deviation (Volatility) % 3.69 3.62 0.07
2. Minimum Periodic Return % -2.33 -2.36 0.03
3. Maximum Periodic Return % 3.88 3.73 0.15
4. Beta (Sensitivity to Benchmark) 0.92
5. R-Squared % 78.66
6. Correlation % 88.69
7. Annualized Tracking Error bp 162.11
8. Shortfall Frequency % 33.33
9. Average Shortfall bp 27.16
10. Downside Capture Ratio % 60.79 100.00
REWARD
11. Annualized Total Return % 7.82 6.53 1.30
12. Average Periodic Return bp 63.50 53.35 10.15
13. Cumulative Total Return % 45.72 37.17 8.55
14. Excess Return Frequency % 66.67
15. Average Excess Return bp 28.81
16. Upside Capture Ratio % 103.61 100.00
RISK ADJUSTED RETURN
17. Sharpe's Ratio 1.62 1.30 0.32
18. Information Ratio 0.80
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 64 of 82
Performance Attribution Report – BME (1 year ending 9/30/2011)
Horizon: 09/30/10 to 09/30/11 BME Composite Barclays Aggregate Difference
(Portfolio) (Benchmark)
RISK
1. Annualized Standard Deviation (Volatility) % 2.81 2.96 -0.16
2. Minimum Periodic Return % -0.67 -1.08 0.41
3. Maximum Periodic Return % 1.61 1.59 0.02
4. Beta (Sensitivity to Benchmark) 0.90
5. R-Squared % 75.32
6. Correlation % 86.79
7. Annualized Tracking Error bp 95.35
8. Shortfall Frequency % 33.33
9. Average Shortfall bp 20.51
10. Downside Capture Ratio % 72.05 100.00
REWARD
11. Annualized Total Return % 6.42 5.26 1.15
12. Average Periodic Return bp 52.28 43.18 9.10
13. Cumulative Total Return % 6.42 5.26 1.15
14. Excess Return Frequency % 66.67
15. Average Excess Return bp 23.90
16. Upside Capture Ratio % 107.70 100.00
RISK ADJUSTED RETURN
17. Sharpe's Ratio 2.23 1.73 0.51
18. Information Ratio 1.21
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 65 of 82
Performance Attribution Report – IME (since Inception ending 9/30/2011)
Horizon: 01/31/00 to 09/30/11 IME Composite Barclays Gov't/Corp Intermediate Difference
(Portfolio) (Benchmark)
RISK
1. Annualized Standard Deviation (Volatility) % 3.34 3.35 -0.01
2. Minimum Periodic Return % -2.50 -2.72 0.22
3. Maximum Periodic Return % 3.25 3.27 -0.02
4. Beta (Sensitivity to Benchmark) 0.96
5. R-Squared % 91.57
6. Correlation % 95.69
7. Annualized Tracking Error bp 90.08
8. Shortfall Frequency % 45.00
9. Average Shortfall bp 13.47
10. Downside Capture Ratio % 93.33 100.00
REWARD
11. Annualized Total Return % 6.44 6.04 0.40
12. Average Periodic Return bp 52.61 49.49 3.12
13. Cumulative Total Return % 107.14 98.31 8.83
14. Excess Return Frequency % 55.00
15. Average Excess Return bp 16.71
16. Upside Capture Ratio % 102.73 100.00
RISK ADJUSTED RETURN
17. Sharpe's Ratio 1.17 1.05 0.12
18. Information Ratio 0.44
All series and calculations are based upon monthly returns
Portfolio = Intermediate Market Enhanced
Benchmark = Barclays Gov't/Corp Intermediate
Risk Free Rate = Merrill Lynch 91 day T-Bill
Performance Attribution Report –IME (5 years ending 9/30/2011)
Horizon: 12/31/06 to 09/30/11 IME Composite Barclays Gov't/Corp Intermediate Difference
(Portfolio) (Benchmark)
RISK
1. Annualized Standard Deviation (Volatility) % 3.26 3.43 -0.16
2. Minimum Periodic Return % -1.65 -2.08 0.43
3. Maximum Periodic Return % 3.25 3.27 -0.02
4. Beta (Sensitivity to Benchmark) 0.91
5. R-Squared % 89.16
6. Correlation % 94.42
7. Annualized Tracking Error bp 94.67
8. Shortfall Frequency % 29.82
9. Average Shortfall bp 13.27
10. Downside Capture Ratio % 81.26 100.00
REWARD
11. Annualized Total Return % 6.97 6.01 0.97
12. Average Periodic Return bp 56.78 49.22 7.56
13. Cumulative Total Return % 37.75 31.94 5.81
14. Excess Return Frequency % 70.18
15. Average Excess Return bp 16.41
16. Upside Capture Ratio % 106.02 100.00
RISK ADJUSTED RETURN
17. Sharpe's Ratio 1.66 1.29 0.37
18. Information Ratio 1.02
All series and calculations are based upon monthly returns
Portfolio = Intermediate Market Enhanced
Benchmark = Barclays Gov't/Corp Intermediate
Risk Free Rate = Merrill Lynch 91 day T-Bill
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 66 of 82
Performance Attribution Report – IME (1 year ending 9/30/2011)
Horizon: 12/31/10 to 09/30/11 IME Composite Barclays Gov't/Corp Intermediate Difference
(Portfolio) (Benchmark)
RISK
1. Annualized Standard Deviation (Volatility) % 2.25 2.25 0.00
2. Minimum Periodic Return % -0.19 -0.16 -0.02
3. Maximum Periodic Return % 1.49 1.43 0.06
4. Beta (Sensitivity to Benchmark) 1.00
5. R-Squared % 78.49
6. Correlation % 88.60
7. Annualized Tracking Error bp 18.30
8. Shortfall Frequency % 33.33
9. Average Shortfall bp 3.45
10. Downside Capture Ratio % 64.87 100.00
REWARD
11. Annualized Total Return % 6.97 6.61 0.36
12. Average Periodic Return bp 56.51 53.69 2.82
13. Cumulative Total Return % 5.19 4.92 0.26
14. Excess Return Frequency % 66.67
15. Average Excess Return bp 5.95
16. Upside Capture Ratio % 102.66 100.00
RISK ADJUSTED RETURN
17. Sharpe's Ratio 3.03 2.87 0.16
18. Information Ratio 1.96
All series and calculations are based upon monthly returns
Portfolio = Intermediate Market Enhanced
Benchmark = Barclays Gov't/Corp Intermediate
Risk Free Rate = Merrill Lynch 91 day T-Bill
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 67 of 82
Performance Attribution Report – SDE (since Inception ending 9/30/2011)
Horizon: 12/31/93 to 09/30/11 SDE Composite ML Treasury 1 to 3 Year Difference
(Portfolio) (Benchmark)
RISK
1. Annualized Standard Deviation (Volatility) % 1.68 1.64 0.03
2. Minimum Periodic Return % -1.35 -0.96 -0.38
3. Maximum Periodic Return % 1.80 1.75 0.05
4. Beta (Sensitivity to Benchmark) 0.95
5. R-Squared % 85.51
6. Correlation % 92.47
7. Annualized Tracking Error bp 62.53
8. Shortfall Frequency % 35.68
9. Average Shortfall bp 12.19
10. Downside Capture Ratio % 88.85 100.00
REWARD
11. Annualized Total Return % 5.00 4.59 0.42
12. Average Periodic Return bp 40.89 37.54 3.35
13. Cumulative Total Return % 137.93 121.62 16.32
14. Excess Return Frequency % 64.32
15. Average Excess Return bp 11.98
16. Upside Capture Ratio % 106.43 100.00
RISK ADJUSTED RETURN
17. Sharpe's Ratio 1.00 0.78 0.22
18. Information Ratio 0.67
All series and calculations are based upon monthly returns
Portfolio = Short Duration Enhanced
Benchmark = ML Treasury 1 to 3 Year
Risk Free Rate = Merrill Lynch 91 day T-Bill
Performance Attribution Report –SDE (5 years ending 9/30/2011)
Horizon: 12/31/06 to 09/30/11 SDE Composite ML Treasury 1 to 3 Year Difference
(Portfolio) (Benchmark)
RISK
1. Annualized Standard Deviation (Volatility) % 1.51 1.67 -0.17
2. Minimum Periodic Return % -0.80 -0.79 -0.01
3. Maximum Periodic Return % 1.75 1.74 0.01
4. Beta (Sensitivity to Benchmark) 0.86
5. R-Squared % 88.32
6. Correlation % 93.98
7. Annualized Tracking Error bp 49.62
8. Shortfall Frequency % 35.09
9. Average Shortfall bp 9.88
10. Downside Capture Ratio % 66.11 100.00
REWARD
11. Annualized Total Return % 4.21 3.84 0.36
12. Average Periodic Return bp 34.48 31.59 2.89
13. Cumulative Total Return % 21.61 19.61 2.00
14. Excess Return Frequency % 64.91
15. Average Excess Return bp 9.80
16. Upside Capture Ratio % 102.40 100.00
RISK ADJUSTED RETURN
17. Sharpe's Ratio 1.97 1.57 0.40
18. Information Ratio 0.73
All series and calculations are based upon monthly returns
Portfolio = Short Duration Enhanced
Benchmark = ML Treasury 1 to 3 Year
Risk Free Rate = Merrill Lynch 91 day T-Bill
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 68 of 82
Performance Attribution Report –SDE (1 year ending 9/30/2011)
Horizon: 12/31/10 to 09/30/11 SDE Composite ML Treasury 1 to 3 Year Difference
(Portfolio) (Benchmark)
RISK
1. Annualized Standard Deviation (Volatility) % 0.73 0.75 -0.02
2. Minimum Periodic Return % -0.10 -0.14 0.04
3. Maximum Periodic Return % 0.55 0.44 0.11
4. Beta (Sensitivity to Benchmark) 0.94
5. R-Squared % 73.74
6. Correlation % 85.87
7. Annualized Tracking Error bp 19.49
8. Shortfall Frequency % 22.22
9. Average Shortfall bp 4.39
10. Downside Capture Ratio % 36.28 100.00
REWARD
11. Annualized Total Return % 2.23 1.81 0.41
12. Average Periodic Return bp 18.38 14.99 3.39
13. Cumulative Total Return % 1.67 1.36 0.31
14. Excess Return Frequency % 77.78
15. Average Excess Return bp 5.61
16. Upside Capture Ratio % 107.81 100.00
RISK ADJUSTED RETURN
17. Sharpe's Ratio 2.85 2.22 0.63
18. Information Ratio 2.13
All series and calculations are based upon monthly returns
Portfolio = Short Duration Enhanced
Benchmark = ML Treasury 1 to 3 Year
Risk Free Rate = Merrill Lynch 91 day T-Bill
2. What type of market environment do you feel the product is expected to outperform its benchmark
and/or peers? Underperform?
The fundamental concept of Ryan Labs investment philosophy is to strive to meet client objectives with
the least amount of total risk and total costs. The firm believes that these objectives are best achieved
through the use of structured portfolios with active issue selection and passive interest rate prediction
strategy.
Ryan Labs does not take active interest rate positions; Ryan Labs believes that interest rates are difficult
(if not impossible) to predict, and therefore, need to be neutralized.
Long Liability Enhanced product concentrates its spread risk in the long end of the curve and attempts
to neutralize interest rates. Therefore we do not expect market conditions to materially affect our
performance with respect to a benchmark.
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 69 of 82
3. Do you currently manage any accounts where the client has a relationship with a consultant at
Smith Barney? If so, please list some Financial Consultants with the highest concentration of joint
business.
Contact Client Product Assets Under
Management ($)
9/30/2011
George Cook Acument Global Technologies LCE 42,674,423
Tom Kahle American Municipal Power LLE & VLLE 20,332,695
Alan Feinberg American Lung Association GCE & LLE 43,295,811
Mike Daly Archdiocese of Santa Fe IME 10,120,000
Kent Cox Cenveo VLLE 50,594,756
Lee Morris Charlotte Pipe and Foundry CLE 41,586,144
Bob Greco District Council of Ironworkers GCE 12,076,874
Mary Tomanek Elk Grove Police Pension BGE 11,003,424
Anthony Cristiano Exco Noonan Pension Plan ILE 7,975,513
George Cook Flexible Steel Lacing LLE 9,803,299
Allan Ettinger Galesburg Fire Pension Plan ILE 10,392,795
Phil Shaffer Genesis Healthcare Systems VLLE 7,742,190
Alan L. Feinberg HealthWell Foundation IME 22,520,831
Phil Shaffer Hillsdale College ILE 25,431,417
Edmund Martinez Kinkaid School LCE 10,976,098
Elaina Spilove Luzerne County VLLE 12,239,014
Phil Shaffer Maritz Inc VLLE 44,282,426
Melanie McDonnell Mississippi College ILE 16,593,890
George T. Cook North Country Health Services LCE 9,842,931
Bob Greco Northwest Ironworkers GCE 25,983,243
Alan L. Feinberg Patient Access Network BME 21,134,667
Elaina Spilove PA Workers Compensation Fund ILE 84,781,605
Elaina Spilove PA Workers Insurance Fund LLE 25,778,542
Elaina Spilove PA USTIF IME 21,140,228
Bill Vaculin Shapell Homes IME 24,103,843
Edmund Martinez St. Luke’s Episcopal Hospital SGC 42,534,446
Bill Hendrix Sun Flower Foundation IME 10,680,575
Scott Davis UFCW (Local 1776) SLE 9,659,484
Allan Ettinger University of New Mexico SDE 150,057,688
Tom Robertson United Way of Dayton VLLE 10,518,130
Ron Tomanek Wheaton Police Pension Fund ILE 13,858,863
Total $ 839,595,845
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 70 of 82
Approved by:
Sean McShea President 10/21/2011
Principal or Senior Officer Title Date
PLEASE RETURN TO:
e-mail: darlene.lieberman@citi.com
For future correspondence, please provide:
Contact
Please indicate below the individual(s) responsible for answering routine firm and portfolio questions, assuring
portfolio dissemination and setting up manager interviews when necessary. (Please put “Same” if the individual
is the same as the primary contact listed above.)
Primary Contact Phone Fax Email
Sean McShea 646-708- 8052 646-349-1524 SMcShea@ryanlabs.com
Brad Jacob 646-708-8044 646-349-1524 BJacob@ryanlabs.com
Eva Zhou 646-708-8045 646-349-1524 EZhou@ryanlabs.com
Annette Serrao 646-708- 8051 646-349-1524 ASerrao@ryanlabs.com
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 71 of 82
Appendix
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 72 of 82
F. HARLAN BATRUS
Chairman of the Board of Directors
Harlan was a founding member of Ryan Labs in 1988. The company was established
with the goal of analyzing and solving the challenges of liability management with
innovative solutions and strategies.
Harlan's extensive experience in the fixed income arena includes work at Lehman
Brothers, Kuhn Loeb in the years when Bond Market Analysis was emerging as a
science, and Morgan Stanley under the tutelage of John Mack. Harlan capped his career
with a 27-year stint at Lazard as Head of the Corporate Bond Department.
Experience Education Born 1950
• Ryan Labs • BS, Wharton School, Economics,
• Lazard, Managing Director & Head of Cum Laude
Fixed Income For more information or to
• Morgan Stanley, Fixed Income Sales contact Harlan Batrus at
Ryan Labs, 500 Fifth
• Kuhn Loeb, Fixed Income Avenue, Suite 2520, New
• Forbes Magazine, Bond Columnist York, NY 10110. Please call
• Lehman Brothers, Fixed Income Sales 646-708-8049 or visit our
home page at
www.RyanLabs.com
Registered Representative
SEAN F. MCSHEA
President
Sean McShea joined Ryan Labs in 1993. In June of 2004, Sean was promoted to
President of Ryan Labs. Mr. McShea was previously Chief Operating Officer and Senior
Vice President of Marketing. He is a key professional responsible for the introduction
and integration of new clients for Ryan Labs in asset management, research and indexes.
He has a reputation for assisting clients with their financial objectives and implementing
Surplus Management structures. Sean is a frequent speaker at financial seminars
involving asset allocation, custom indices, performance attribution, and risk
management.
Mr. McShea previously served as a Management Consultant at Accenture in their
financial services practice. He graduated from the Worcester Polytechnic Institute in
1987 with distinction in Industrial Engineering. He received his Masters in Business Born 1965
Administration from Columbia Business School with concentrations in finance and
accounting in 1993.
Experience Education For more information or to
contact Sean McShea at
• Ryan Labs • MBA, Columbia (1993) Ryan Labs, 500 Fifth
• Accenture Specialties in Accounting & Finance Avenue, Suite 2520, New
York, NY 10110. Please call
• BS, Worcester Polytechnic Institute, 646-708-8052 or visit our
Speaker Graduated with distinction home page at
www.RyanLabs.com
• Asset Allocation
• Risk Management
• Fixed Income
Registered Representative
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 73 of 82
GERALDINE MICHALIK, PH.D.
Chief Operating Officer
Dr. Geraldine Michalik joined Ryan Labs in 1990 and is currently Chief Operating
Officer. She is responsible for oversight and administration of the firm. Dr. Michalik
was previously the Director of Credit/Sector Research and Portfolio Manager and was
responsible for the corporate and agency credit review process and sector analysis.
Prior to joining Ryan Labs, she was Manager of Investments, responsible for managing
the fixed income portfolio of Coltec Industries pension assets. She also held positions of
Assistant Manager, Treasurer’s Department (Pension Group); Senior Financial Advisor
(Investment Banking Group); and Senior International Economist at the Mobil
Corporation. Dr. Michalik also held analytical positions at the Exxon Corporation and as
an Economist at Townsend & Greenspan.
Born 1949
Experience Education
• Ryan Labs • Ph.D. , Pacific Western University,
• Coltec Industries Inc. Financial Management For more information or to
• Mobil Corporation • MBA, New York University, contact Dr. Michalik at Ryan
Labs, 500 Fifth Avenue,
• Exxon Corporation Economics, and International Business Suite 2520, New York, NY
• Townsend & Greenspan • BA, St. Peter’s College, 10110. Please call 646-708-
Economics, Cum Laude 8049 or visit our home page
at www.RyanLabs.com
Registered Representative
MICHAEL DONELAN, CFA
Director of Asset Management
Mike joined Ryan Labs in 2003 as Portfolio Manager and Director of Trading. His
experience includes fundamental and technical research as well as trading a wide
spectrum of fixed income securities.
Prior to joining Ryan Labs, Mike held positions as Principal Investment Officer for the
New York State Insurance Fund, Director of Asset Management at Native Nations Asset
Management, Senior Portfolio Manager with Butterfield Asset Management in
Bermuda, Portfolio Manager and Trader at ABN-AMRO Bank, and trader at Brown
Brothers
Harriman.
Born 1966
Experience Education For more information or to
contact Mr. Donelan at
• Ryan Labs • CFA Charterholder Ryan Labs, 500 Fifth
• NY State Insurance Fund • MBA, Fordham University Avenue, Suite 2520, New
• Native Nations Asset Management • BS, Seton Hall University, Finance York, NY 10110. Please
call 646-708-8041 or visit
• Butterfield Asset Management our home page at
• ABN-AMRO www.RyanLabs.com
• Brown Brothers Harriman
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 74 of 82
RICHARD FAMILETTI, CFA
Senior Portfolio Manager
Rich joined Ryan Labs in 2009 as a portfolio manager specializing in corporate credit and
fixed income asset allocation. He has experience with various investment strategies in all
sectors of the fixed income markets employing a combination of fundamental and technical
analysis.
Prior to joining Ryan Labs, Rich held positions at Halbis Capital Management as a hedge
fund manager, Calyon Bank in proprietary trading, and Credit Suisse Asset Management as
a Managing Director. Rich joined Credit Suisse as a result of the sale of a small, successful
partnership called Brundage, Story and Rose, Investment Management. Before this, Rich
traded Mortgages, CMO’s, and ABS for Lazard Freres Asset Management.
Born 1964
Experience Education For more information or to
contact Mr. Familetti at Ryan
• Ryan Labs • CFA Charterholder Labs, 500 Fifth Avenue,
• Halbis Capital Management • MBA, Fordham University Suite 2520, New York, NY
• Calyon Banks • BA, Hofstra University 10110. Please call 646-708-
8058 or visit our home page
• Credit Suisse Asset Management at www.RyanLabs.com
• Brundage, Story and Rose
• Lazard Freres Asset Management
PHILIP MENDONCA
Senior Portfolio Manager
Philip joined Ryan Labs in March of 2003 as a quantitative analyst. In March 2004, he
joined the asset management team as a trader and analyst. Since joining the asset
management team Philip has been promoted to Portfolio Manager and subsequently Senior
Portfolio Manager responsible for all the firms structured product investments and activities.
Philip has successful headed the portfolio management team’s investments in levered and
unlevered investments in Mortgage, Asset Backed and interest rate/inflation linked
strategies. Philip directs the firms credit strategy as is related to mortgages (residential and
commercial) and a myriad of asset backed securities; involving fundamental and technical
analysis and is both top down and bottom up, requiring continuous monitoring of collateral
performance and development of credit models. Philip directed the firm TALF investments
and continues to guide the portfolio strategy and construction as it relates to changing
custom client solutions. During his tenure at Ryan Labs, Philip developed several indices Born 1976
and was heavily involved in the development of custom client solutions ranging from asset
liability analysis, custom benchmarks creation and portfolio structuring.
For more information or to
Philip was an active duty Marine for 4 years serving in posts throughout Asia, North contact Mr. Mendonca at Ryan
Africa and the Middle East. Philip majored in Operations Research and minored in Labs, 500 Fifth Avenue, Suite
Finance and Mathematics at Pace University. 2520, New York, NY 10110.
Please call 646-708-8053 or
Experience Education visit our home page at
www.RyanLabs.com
• Ryan Labs • BBA, Pace University
Operations Research
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 75 of 82
DANIEL LUCEY JR., CFA
Portfolio Manager
D.J. joined Ryan Labs in 2009 as an Institutional Portfolio Strategist. In that role, D.J. was
responsible for LDI/Fixed Income research, strategy and communicating Ryan Labs’
investment philosophy, capital market climate and underlying positions to institutional
clients. He also assisted Ryan Labs with asset/liability strategies and credit research. In
2010, he became a Portfolio Manager, focusing on structured product sector. His prior
experience includes actuarial analysis, pension fund asset and liability valuation, and
pension industry research.
Prior to joining Ryan Labs, D.J. was a Senior Research Analyst with Cerulli Associates, a
strategy research and consulting firm specializing in the financial services industry. His
primary research focus was on the institutional fund management industry. Past research
and articles he has authored have covered institutional asset allocation and asset/liability
management, liability-driven investment strategies and the use of alternatives in pensions. Born 1981
Before joining Cerulli Associates, D.J. was an actuarial analyst at Fidelity Investments,
performing defined benefit asset and liability valuation and consulting plan sponsors on
For more information or to
plan design. Prior to joining Fidelity, he was an executive at the May Company. contact Mr. Lucey at Ryan
Labs, 500 Fifth Avenue, Suite
Experience Education 2520, New York, NY 10110.
Please call 646-708-8046 or
• Ryan Labs • CFA Charterholder visit our home page at
• Cerulli Associates • BA, College of the Holy Cross www.RyanLabs.com
• Fidelity Investments Economics
• The May Company
NICHOLAS FINKELMAN, CFA
Portfolio Manager
Nicholas joined Ryan Labs in May 2003 as a quantitative analyst. In February 2005, he
joined Ryan Labs’ Asset Management team as a trader/analyst. In March of 2007 he was
promoted to portfolio manager.
Nicholas trades across all sectors in short, intermediate, long, very long maturities. He
regularly performs proprietary technical, fundamental, capital structure and relative value
analysis on issuers / sectors. He is heavily involved in portfolio construction process for
market and custom benchmarks. Nicholas plays an integral role in developing strategies
designed to outperform market indexes and helps with portfolio attribution.
Nicholas graduated from Pace University with a BBA, with majors in Finance, Operations
Research and minors in Economics, Mathematics. Born 1981
Experience Education For more information or to
contact Mr. Finkelman at
• Ryan Labs • CFA Charterholder Ryan Labs, 500 Fifth
• BBA, Pace University, Avenue, Suite 2520, New
Graduated Cum Laude York, NY 10110. Please call
646-708-8043 or visit our
Finance, Operations Research home page at
www.RyanLabs.com
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 76 of 82
MATT SALZILLO
Trader
Matt’s primary responsibilities on the Asset Management team are trading across asset
classes in the fixed income markets, working with the portfolio management team to
develop and implement strategy, and monitoring portfolio and trade compliance. Matt
focuses on getting best execution across Ryan Labs’ separately managed account
strategies, attempting to maximize risk adjusted returns through favorable execution and
timing. Matt also monitors the new issue market for the asset management team. Matt
joined Ryan Labs in 2004 in the Asset Management department.
Matt graduated with a B.S. in Marketing from the Stillman School of Business at Seton
Hall University.
Born 1982
Experience Education For more information or to
contact Mr. Salzillo at Ryan
• Ryan Labs • BA, Seton Hall University Labs, 500 Fifth Avenue,
Business & Marketing Suite 2520, New York, NY
10110. Please call 646-708-
8055 or visit our home page
at www.RyanLabs.com
YULIA MININA
Credit Analyst
Ms. Minina joined Ryan Labs in 2009 and currently serves as Fixed Income Analyst. She
covers corporate, sovereign and industry analysis. Previously Yulia was responsible for all
aspects of fundamental and structured credit analysis and modeling for Magnetar Capital, a
global alternative investment hedge-fund, and fundamental credit and equity analysis at
OTA Asset Management.
She also held a management consultant position for Silver Oak Solutions. Ms. Minina has a
Masters degree from Massachusetts Institute of Technology.
Born 1976
Experience Education
• Ryan Labs • MBA, Massachusetts Institute of
• Magnetar Capital Technology For more information or to
• OTA Asset Management contact Ms. Minina at Ryan
Labs, 500 Fifth Avenue, Suite
• Silver Oak Solutions 2520, New York, NY 10110.
Please call 646-435-9512 or
visit our home page at
www.RyanLabs.com
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 77 of 82
KEN SZAL
Analyst
Ken joined Ryan Labs as an Analyst in February of 2009.
He is responsible for assisting the Asset Management desk with back office operations
including reconciliation, trade settlement, and reporting.
Ken graduated from the College of the Holy Cross in 2008. While there, he earned B.A.
degrees in both Economics and Religious Studies.
Born 1986
Experience Education For more information or to
contact Mr. Szal at Ryan
• Ryan Labs • BA, College of the Holy Cross Labs, 500 Fifth Avenue,
Economics Suite 2520, New York, NY
10110. Please call 646-708-
8048 or visit our home page
• BA, College of the Holy Cross at www.RyanLabs.com
Religious Studies
DAVID AUDLEY, PH.D.
Research Strategist
David joined Ryan in 2008 in an advisory role for strategy and research and, in conjunction
with his faculty position at Johns Hopkins, conducts research in fixed income strategy and
portfolio management. These research results respond to the immediate needs of Ryan’s
clients. Current research addresses LDI strategies, term structure modeling, and
quantitative credit strategies.
David is on the faculty of Johns Hopkins University and is executive director of the
graduate curriculum in Financial Mathematics. Since 1987, David has been portfolio
manager, research analyst and technologist at a variety of firms. He spent 7 years at
Prudential Securities in Financial Strategies and proprietary trading, five years at the Tiger
hedge fund of Julian Robertson, and has had appointments at Merrill Lynch and the Clinton
Group. In 2003, David founded an electronic fixed income trading platform for MBS/ABS
that continues in the market today. David spent 16 years in the regular Air Force in a Born 1944
variety of operational assignments and was on the faculty at the US Air Force Academy.
Experience Education For more information or to
contact Mr. Audley at Ryan
• Ryan Labs • B.S. The Citadel, 1968 Labs, 500 Fifth Avenue, Suite
• Watch Hill Investment Partners, 2004 • M.S. The University of Southern 2520, New York, NY 10110.
• Beacon Capital Markets, 2003 California, 1969 Please call 646-708-8054 or
• Clinton Group, 2002 • Ph.D. The Johns Hopkins University, visit our home page at
www.RyanLabs.com
• Merrill Lynch, 1999 1972
• Tiger Management, 1994
• Prudential Securities, 1987
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 78 of 82
DOUGLAS A. LOVE, PH.D.
Senior Advisor
Dr. Love’s joined Ryan Labs in 1995 as Managing Director and Portfolio Manager. Doug
and Michael Donelan develop the model portfolio strategy for Ryan Labs fixed income
composites.
Doug was the founder and former Chairman of Buck Investment Services, a money
management search and selection firm where he also developed advanced performance
analytics and modeling technologies. He has been a consultant to the PBGC and World
Bank, has participated in Financial Accounting Standards deliberations, served as
Chairman of the Employee Benefits Research Institute, been project manager for the
Council of Economic Advisors for the White House, and a member of the Grace
Commission.
Currently Dr. Love is chairman of the Investment Subcommittee of the New Jersey Born 1935
Investment Council, which oversees the state’s public employee pension assets, and a
principal in Stronghold Group. Ltd a global group of insurance and investment companies
and chairman of Devonshire Darwin a quantitative hedge fund. For more information or to
Experience Education contact Doug Love at Ryan
Labs, 500 Fifth Avenue,
• Ph.D., Columbia Economics
• Ryan Labs Suite 2520, New York, NY
• MBA, MS, NYU Finance 10110. Please call 646-708-
• Investors Guarantee
• BME, Cornell University 8054 or visit our home page
• Matrix Capital at www.RyanLabs.com
Research Publications
• BEA Associates
• Yield Curve Dynamics
• Buck Investment Services • Computers, Science, and Management
Dynamics
• Georgia Law Review
THOMAS KIRCH
Senior Advisor
Mr. Kirch has over 37 years of experience in the financial services industry as a senior
executive and policy maker. From 1979 to 1990, Mr. Kirch held various management
positions with The First Boston Corporation ("First Boston"), a major financial services
firm.
He was a member of the Executive Committee, Senior Managing Director, responsible for
Global Fixed Income and Chairman of the Capital Commitment Committee of the Credit
Suisse First Boston Group. In these capacities, Mr. Kirch was responsible for sales and
trading of taxable fixed income and derivative products; sales, trading, and capital market
underwriting of government, corporate, foreign, mortgage and municipal bonds; derivative
products, including interest rate and currency swaps; proprietary trading; public mortgage
and asset finance; and risk measurement group and risk management systems for fixed
income and derivative products. Born 1944
Experience Education For more information or to
contact Tom Kirch at Ryan
• Ryan Labs • BA, University of Delaware Labs, 500 Fifth Avenue, Suite
• First Boston (Credit Suisse) 2520, New York, NY 10110.
• Loeb, Rhoades, Hornblower Please call 646-708-8054 or
visit our home page at
• Morgan Stanley & Co. www.RyanLabs.com
• Columbus Circle Investors
• Bank of Delaware
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 79 of 82
BRADLEY D. JACOB
Vice President – Marketing & Client Services
Mr. Jacob joined Ryan Labs in 2008 as a Vice President of Marketing & Client Service. He
actively works in communicating applicable fixed income strategies to clients and
consultants, and oversees client service efforts. Brad assists clients and consultants with the
implementation of fixed income solutions using custom liability indexes, as well as market
driven mandates.
Previously, Brad worked at MorganStanley SmithBarney, where he was part of an
institutional consulting team. His primary responsibilities were marketing the group’s
services, managing client relationships, and overseeing day-to-day management of
accounts. His focus was working with corporate and public defined benefit pension funds,
universities, hospitals, Endowments & Foundations, and other institutional clients.
Prior to entering the asset management and financial services industry, Mr. Jacob was Born 1979
actively involved in politics, working in campaign fundraising, strategy, and coordinating
field/get-out-the-vote programs at the local, state, and federal levels.
Experience Education For more information or to
contact Brad Jacob at Ryan
• Ryan Labs • BS, DePaul University Labs, 500 Fifth Avenue, Suite
• MorganStanley SmithBarney Consulting Management 2520, New York, NY 10110.
Please call 646-708-8044 or
Group
visit our home page at
www.RyanLabs.com
EVA ZHOU
LDI Analyst
Eva joined Ryan Labs Marketing division in 2007 as a quantitative analyst.
Eva’s primary responsibilities involve developing custom client solutions, ranging from
conducting asset liability analysis to creating custom benchmark. During her tenure at
Ryan Labs, Eva improved the asset/liability study model, and consolidated historical
composite data into a single comprehensive database which enhanced the management of
the firm’s account database. As part of the Marketing team, Eva also assists in preparing
responses for prospect’s RFP, as well as due diligence.
Eva is a graduate of Baruch College, where she earned a Baccalaureate of Business
Administration degree from the Zicklin School of Business, with a major in Finance and a
minor in Economics. Born 1975
For more information or to
Experience Education contact Eva Zhou at Ryan
• BBA, Baruch College Labs, 500 Fifth Avenue,
• Ryan Labs
Suite 2520, New York, NY
Finance 10110. Please call 646-708-
8045 or visit our home page
at www.RyanLabs.com
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 80 of 82
ANNETTE SERRAO
Marketing Analyst
Annette joined Ryan Labs Marketing division in July 2010 as a marketing analyst.
Annette’s primary responsibilities include conducting asset liability analysis and providing
asset portfolio details to clients and consultants. As part of the Marketing team, Annette
also assists in preparing composite presentation, quarterly performance data and
maintaining investment consulting databases.
Annette previously served as an Associate for two (2) years at Tata Consultancy Services,
India, Banking, Financial Services and Insurance sector (BFSI), leading data warehousing
projects related to credit cards, mortgages, personal loans and auto loans across different
geographies. She also holds a Six Sigma (Green Belt) certification.
Annette is a graduate of Pace University, where she earned her Master of Business
Administration (MBA) degree from Lubin School of Business, with a major in Finance. Born 1984
She
additionally holds a Bachelors degree in Computer Engineering from Mumbai University,
India. She is a CFA Level 2 candidate. For more information or to
Experience Education contact Annette Serrao at
• MBA, Pace University Ryan Labs, 500 Fifth Avenue,
• Ryan Labs
Suite 2520, New York, NY
Financial Management 10110. Please call 646-708-
• B. Engineering, India, 8051 or visit our home page at
Computers www.RyanLabs.com
RAGHAVA VUDATA
Index Analyst
Raghava K. Vudata joined Ryan labs in 2008 as an Index Analyst.
Raghava is primarily responsible for Index creation and Maintenance. He updates, verifies
and analyzes the index data to maintain all the Ryan Labs Indexes. Raghava is actively
involved in all daily and monthly operational procedures and co-ordinates with operational
personnel on maintaining and improving RL systems & Software. Raghava also has
responsibilities in Web development and Client Service.
Raghava holds a Masters degree in Engineering Management from New Mexico Tech and
a Bachelor of Technology degree from J.N.T University, India.
Born 1981
For more information or to
Experience Education contact Raghava Vudata at
• Ryan Labs • MEM, New Mexico Tech Ryan Labs, 500 Fifth Avenue,
Suite 2520, New York, NY
Engineering Management ,Finance 10110. Please call 646-708-
• B.Tech., J.N.T. University, India 8040 or visit our home page at
Mechanical Engineering www.RyanLabs.com
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 81 of 82
LUIS LOPEZ DUCRET
Operations Manager
Mr. Ducret joined Ryan Labs in September of 2007 as an Operations Manager, Luis is
responsible for all aspects of the Ryan Labs network infrastructure. Luis is integral to Ryan
Labs' plans to continually upgrade systems in anticipation of greater business and
regulatory requirements. He is responsible for expanding and upgrading Ryan Labs’
network infrastructure including servers, client workstations, software and expanding
network
capabilities. Luis oversees enhancing the technical infrastructure of Ryan Labs systems,
focusing on improving bandwidth, performance and system reliability. His daily
responsibilities include the maintenance and support of the firm’s systems, hardware,
software, and mobile platform.
Prior to joining Ryan Labs, Luis worked as a system engineer at a well respected, medium Born 1971
sized hedge fund. He holds a Baccalaureate in computer science from Baruch College.
For more information or to
Experience Education contact Luis Lopez Ducret at
• Ryan Labs • BA, Hunter College Ryan Labs, 500 Fifth
Avenue, Suite 2520, New
• Duquesne Capital Computer Science York, NY 10110. Please call
646-708-8050 or visit our
• AA, Technical Career Institute home page at
Network Engineering www.RyanLabs.com
For Use By the MorganStanley| SmithBarney Consulting Group Only
Page 82 of 82
