New Oak Creating An Effective Risk Modeling Framework (Pensions Risk Management)

Liability Driven Investing (“LDI”)
Effective Risk and Asset Modeling Requirements

Various Approaches to Managing to Liabilities

Dodd-Frank

LDI Financial Technology and Infrastructure Needs

31 October 2011
For more information please contact:
Ron D’Vari, CEO/Co-Founder
(212) 209-0855
rdvari@newoakcapital.com

Or visit us on the web at:
www.newoakcapital.com/solutions

TABLE OF CONTENTS 1

I | Various Approaches to Managing to Liability Benchmarks
I I | Liability Driven Investing and Alpha Strategies
I I I | Relatively New Alpha Strategies
I V | An Example of a Scalable Strategy: Quantitative Global Equity
V | Dodd-Frank and Its Impact on LDI
V I | LDI - Solutions and Infrastructure Needs
Appendix I| OpenRisk M
Appendix II| Investment Support Services

PROPRIETARY AND CONFIDENTIAL
©2011 NewOak Capital LLC. All rights reserved.

CREATING AN EFFECTIVE RISK MODELING FRAMEWORK FOR LDI 2

Comprehensive approach can meet complex institutional, product lines, and regulatory requirements
 Asset Liability Management Approach
 Various Styles
 Basic cash-flow matched, key rate duration matched to full liability-driven investment with sophisticated asset allocation for
active management of surplus
 Surplus Optimization
 Using alternative, real and uncorrelated assets and styles
 Unique long dated assets: Life settlements, Structured settlements
 Real Assets: Real estate, Commodities
 Dollar Neutral Strategies: Long/Short global equities, Long/Short ETF
 Unique liquidity management: Short High Yield (“SHYLD”) Strategies (REO Finance, Supply Chain Finance, Asset Based
Finance)
 Customized Solutions
 Customized style and benchmark construction consistent to funding status and institutional profile
 Separate accounts or commingled funds
 Broad array of fixed income, equity, and alternative asset types and strategies including esoterics
 Liquid Fixed Income: All liquid fixed income (Short Duration, Core, Core+, Long Duration)
 Illiquid Fixed Income: Loans , structured products, specialty finance
 Equities: Long/Short, Event Driven, International Quant Equities, ETFs, High Frequency, Private Equities
 Real Investing: Real Estate, Land, Commodities
 Multi-Strat Macro: Free-to-roam
 Ongoing Risk Management and Reporting
 Ongoing in-depth risk assessment, valuation, performance monitoring
 Daily benchmark variance analysis and marked-to-market
 Full cash flow scenario analysis
 Periodic benchmark performance attribution


3

I. Various Approaches to Managing to Liability
Benchmarks


4
CHALLENGES OF MANAGING TO LIABILITY BENCHMARKS

Role of the benchmark
What risk to manage?
An Illustrative Case Study
Traditional liability benchmarks and choice of discounting
Static spread
Dynamic spread
How do you measure the manager’s performance in A/L
framework?
Impact of spread volatility on performance measurement
Distortion due to static spread assumption
Manager behavior and its impact on expected returns
Case for dynamic-spread liability benchmark
Role of Min-VAR Optimization in Asset/Liability Management
Key-rate-duration matched dynamic spread benchmarks
Key-rate-duration matched market-based benchmarks

©2011 NewOak Capital LLC. All rights reserved. 4

5
WHAT RISK(S) TO MANAGE TO?

Definitions
The following risks measure variability of:
Absolute Return Risk = Std. Dev. (Portfolio Return)
Relative Risk = Std. Dev. (Portfolio Return - Benchmark Return)
Relative-to-Liability Risk = Std. Dev. (Portfolio Return - Liability
Return)
Basis Risk = Std. Dev. (Benchmark Return - Liability Return)
How Should Risk Be Measured?
Portfolio vs. Cash (Total Return Risk),
Portfolio vs. Benchmark (Relative Risk), or
Portfolio vs. Liability (Relative-to-Liability Risk)?


6
WHAT IS RELEVANT?

Choice of benchmark can be a critical determinant of returns
Market-based benchmarks - Basis Risk
Liability-based benchmarks - Absolute Risk
What seems to be most relevant?
The answer is “it depends!” or “it is regime dependent”
Short-Run  Total/Absolute (sponsor) or Relative Risk
(manager)
Long-Run Relative-to-Liability Risk (sponsor)
Is there a pattern?
In down-markets there is reversion to liability-based approach
Absolute returns look ugly
Relative returns look horrific because liabilities outpace
markets
In up-markets market-based benchmarks rule


7
RECENT EXPERIENCE

Up-market Period: 1984-2000, 2003-2007, 2009-2010
Market-based strategies outperformed liability benchmarks
Basis risk was profitable and led to huge pension surpluses
Sponsors tended to down play relative risk to liability
benchmarks
Contributions to pension plans were kept at minimum
Down-Market Period: 2000- 2003, 2007-2009, 2011
Liabilities have significantly outperformed portfolios and
market-based benchmarks
Basis risk has materialized and has led to huge pension deficits
Sponsors are re-evaluating relative risk to liability benchmarks
Contributions to pension plans are resuming and a must
 Sponsors are reneging on their liabilitities
Extension of retirement age
Reducing post retirement health benefits
Cutting off defined benefit (e.g. California)


OPTIMAL ALLOCATION OF ASSETS - DIFFERENT APPROACHES 8

Modern portfolio management ignores risks vs. liabilities

Optimal Utility Function Approach
Optimization is generally cast in absolute risk-return space
Inter-temporal risk is measured in absolute terms
rather than relative to the liabilities Based on some
form of efficient frontier
Market-based benchmarks
Choice of benchmark is driven by risk-tolerance
(utility)
Liabilities ignored for the most part
Liability Immunization Approach
Optimization is cast in relative-to-liability risk-return space
Inter-temporal risk is measured relative to the
liabilities
Estimation of liabilities are key
Discounted-liabilities form the benchmark
 Discounting methodology varies
Choice of discounting methodology can influence
results significantly

OPTIMAL UTILITY FUNCTION APPROACH 9

Establish Efficient Frontier and Utility Function
Select investable asset classes and corresponding indicative
market indices
Establish length of time and frequency of measurement most
relevant
Identify risk tolerance or a risk-return utility function
 Establish Optimal Benchmark/Asset Mix
Optimize Sharpe Ratio by solving for optimal asset class on
efficient frontier and risk tolerance
Actively Manage
Optimize information ratio, i.e. alpha/tracking error
Risks vs Liabilities Are Ignored

Benchmark - Optimal Sharpe Ratio
Management - Optimal Information Ratio


10
TRADITIONAL LIABILITY IMMUNIZATION APPROACH

Establish Liability Benchmark
Liability Cash Flows: Establish realistic liability (RL) or
participating liability (PL) cash flow stream
Discounting Methodology: Establish a discounting
methodology
Curve - Zero coupon curve + some spread
Treasury, agency, or swap
Tail Rate - A discount rate for flows past 30 years
Spread - Sufficient spread that meets the liabilities
in the long run and provide with additional risk-
adjusted return
Manage Assets vs. Benchmark
Add alpha over liability benchmark through
Actively manage key-rate duration around liability
benchmark
Actively manage spread exposure
Discounting methodology affects funding status
Static spread discounting of liabilities could distort funding status significantly

11
TRACKING ERROR ATTRIBUTION IN ASSET LIABILITY

Asset and Liability Performance
Asset = Duration/Curve Move+ Spread Moves + Credit Blow Ups
Liability = Cash Flow Changes + Duration/Curve Move
Asset/Liability Return Differences
Actuarial gain or loss
Mismatch in duration/curve exposure
Spread volatility
Credit blow ups

Management performance may be hard to isolate


AN EXAMPLE OF A STUDY RUN IN APRIL 2001 12

Various Allocations Considered
Immunized Portfolio Liabilities
Date: April 01 Aggressive Moderate* Conservative Moderate
Spread to Treasury (bp) 150 125 100 125
Average Quality A-/BBB+ A- A A-
Minimum Quality BB BB BBB- BB
Effective Duration 11.4 11.6 11.8 11.6
Portfolio Expected Return (IRR) 7.3% 7.1% 6.8% 7.1%
Relative Expected Return 0.2% 0.0% -0.2% 0.0%
Relative Volatility 2.3% 0.0% 1.2% 0.0%
Absolute Volatility 8.0% 7.6% 7.1% 7.6%

Efficient
Frontier
Portfolio
Cash 0.0%
Equity 50%
Fixed - Core 40%
High Yield 10%
Portfoli Expected Return 10.18%
Relative Expected Return 3.08%
Relative Volatility 14.17%
Portfolio Standard Deviation 9.34%


BASIC RISK/RETURN DATA 13

Cash
Expected Return 4.50%
Equity
Expected Return 9.0%
Standard Deviation 17.5%
Correlation to Core 0.3
Correlation to High Yield 0.4
Correlation to Long Bond 0.15
Relative Std Dev to Liability 17.97%
Economic Downturn Stress Senario -29.2%
Fixed Income
10 year T reasury Yield 5.30%
30 year T reasury Yield 5.85% Long Duration Liability
10s Yield Beta to 30s Yield 1.20 Core High Yield Aggressive Moderate Conservative (Moderate)
Spread over T reasury (bp) 0.75% 3% 1.50% 1.25% 1% 1.25%
Expected Return 6.05% 7.80% 7.35% 7.10% 6.85% 7.10%
Duration 4.5 4 11.44 11.63 11.82 11.63
T reasury Yield Standard Deviation 0.50%
Spread Standard Deviation 0.25% 0.45% 0.40% 0.25% 0.20% 0.25%
Spread Correlation to T reasury 0.40 0.50 0.2 0.4 0.4 0.4
Return Standard Deviation 2.89% 3.29% 8.01% 7.47% 7.19% 7.47%
Sharpe Ratio 0.54 1.00 0.36 0.35 0.33 0.35
Expected Relative Return to Liabilities -1.05% 0.70% 0.25% 0.00% -0.25% 0.00%
Relative Return Standard Deviation 6.64% 6.81% 2.29% 0.00% 1.18% 0.00%
Information Ratio -0.16 0.10 0.11 n.a -0.21 n.a

Economic Downturn Stress Senario
Equity Return -29%
Fixed - Yield Changes
10 yr Treas Yield Change -1.00% Long Duration Liability
30Yr Treas Yield Change -0.75% Core High Yield Aggressive Moderate Conservative Moderate
Spread Change 0.25% 0% 0.35% 0.25% 0% 0.25%
Fixed - Returns 9.43% 10.20% 11.92% 12.91% 13.35% 12.91%


14
COMPARISON OF DIFFERENT STRATEGIES

Initially 15% Overfunded Example
Immunized
Aggressive Immunized & Aggressive Immunized & Aggressive Immunized +
Market Based
Tail+Surplus in Equity Surplus in Equity Surplus in Equity
Approach
(Future O verlay) (Future O verlay) (No Future O verlay)

Portfolio Weights - % Liabilities

Cash 0.0% -25.0% -15.0% 0.0%
Equity 58% 25.0% 15.0% 15.0%
Fixed - Core 46% 0.0% 0.0% 0.0%
High Yield 12% 0.0% 0.0% 0.0%
Long Duration 0.0% 0.0% 0.0% 0.0%
Aggressive 0.0% 115.0% 115.0% 100.0%
Moderate 0.0% 0.0% 0.0% 0.0%
Conservative 0.0% 0.0% 0.0% 0.0%
Total - % Liabilities 115.0% 115.0% 115.0% 115.0%

Long Term Expectations
Liability Expected Return 7.10% 7.10% 7.10% 7.10%
Portfoli Expected Return - % Liabilities 10.18% 9.58% 9.13% 8.70%
Relative Expected Return - % Liabilities 3.08% 2.48% 2.03% 1.60%
Relative Volatility 14.17% 8.31% 8.29% 8.28%
Relative Information Ratio 0.22 0.30 0.24 0.19
Sharpe Ratio 0.47 0.41 0.40 0.40

Economic Downturn Scenario
Portfolio 1-Yr Return - % Liabilities -11.30% 5.28% 8.65% 7.54%
Liability 1-Yr Return - % Liabilities 12.91% 12.91% 12.91% 12.91%
Relative 1-Yr Return - % Liabilities -24.21% -7.63% -4.26% -5.37%
Ending Surplus (Deficit) - % Liabilities -9.21% 7.37% 10.74% 9.63%


RESULTS SUMMARY 15

Optimal Sharpe ratio allocation, when viewed from relative
stand point, is
Highly risky in economic downturn scenario
Not highest information ratio
Variations of immunized strategy can lead to
Superior relative risk profile
Modest give up in expected return
Much lower exposure to economic downturn scenario


DISTORTION DUE TO STATIC-SPREAD DISCOUNTING IN VOLATILE SPREAD MARKETS 16

Introduces
Funding status mismeasurement
Measurement tracking error
Makes it harder to distinguish impact of
Credit calls/mistakes
Curve bets/mismanagement
Leads to sub-optimal spread allocation
Tracking error risk leads to risk avoidance
Managers may under invest in spread products and miss
opportunities to earn higher yields

Static spread discount rates distorts funding status and leads to sub-optimal
sector allocation


0
100
200
300
400
500
600
700
800
Agency 1-3

24
Agency 3-7

44
Jan-03
Agency 7-10

54
Agency 10+

51
Max

Agency TOT

39
Credit Cards

72
75%

Disc MBS (P<=100)

0
Prem. MBS (P>=100)

86
Mean

15-Year MBS
Source: Salomon Yield Book and State Street Research

90
Monthly Spread History - Jan 1989 to Jan 2003

Agency MBS

86
25%

AAA/AA Corporates 1-3

60
Min

100

167

AAA/AA Corporates 10+

AAA/AA Corporates TOT
113 105

A Corporates 1-3
119

A Corporates 3-7

A Corporates 7-10
142 145

A Corporates 10+
154

A Corporates TOT
141

BBB Corporates 1-3
302

17

BBB Corporates 3-7
318

BBB Corporates 7-10
280

BBB Corporates 10+
267

BBB Corporates TOT
291

BB Corp.
707
CASE FOR DYNAMIC-SPREAD LIABILITY BENCHMARKS -HISTORICAL SPREAD VOLATILITIES 17

18
TRADITIONAL ALTERNATIVES TO STATIC SPREAD DISCOUNTING

Two Alternatives
Market-based Spread
Examples include:
Single-A long corporates
Swap spread
High-grade corporate option-adjusted
spread
Portfolio Spread
Some use duration-weighted option
adjusted spread of the portfolio
Both Alternatives May Not Be Optimal
Market and portfolio asset mix may not be
necessarily optimal from absolute volatility
standpoint

Traditional alternatives to static spread discounting are not necessarily optimal


19
OPTIMAL RISK-CONSTRAINED DYNAMIC SPREAD METHODOLOGY

Benefits
Minimizes tracking error and other forms of risk
such as VAR vs. static-spread liability benchmark
Based on an optimal allocation among spread
sectors across all maturities
Downside risk constraints can be used to control
allocation of risk
It is equivalent to highest Sharpe ratio portfolio in
absolute space

Optimal Dynamic-Spread methodology leads to benchmarks with minimum
variance w.r.t. static-spread liabilities


20
OPTIMAL RISK-CONSTRAINED DYNAMIC SPREAD METHODOLOGY - BASIC STEPS

Step 1: Target Return Over Treasury
– Establish required long term spread to meet long term
liabilities
– Add a target strategic added value

Step 2: Define Investible Fixed Income Universe
– Treasuries, Agencies, ABS, CMBS, AAA-AA Corporates, A
Corporates, BBB Corporates, BB Corporates, Mortgage Pass-
Throughs

Step 3: Collect appropriate historical volatility of option-
adjusted spreads (OAS) for all sectors

Step 4: Define Allocation Constraints


OPTIMAL RISK-CONSTRAINED DYNAMIC SPREAD METHODOLOGY - BASIC STEPS 21

Step 5: Perform Risk Constrained Optimization
– Objective: Min VAR (or Single Downside Risk)
– Constraints:
• Duration Weighted OAS = Target Return Over Treasury
• Other constraints such as
 Duration Spread < x1
 Spread Product % < x2
 ABS and CMBS % < x3
 High Grade Corporates <x4
 High Yield % <x5
 Etc.
Step 6: Mark-to-Market Duration Weighted Spread
Periodically
• Keep sector weights constant
• DWLOAS = Duration-Contribution Weighted Liability OAS


ONGOING EVALUATION OF DYNAMIC-SPREAD LIABILITY BENCHMARK 22

Dynamic Spread Liability Return For Each Period
– DSLV1 = Cash flows discounted at Treasury+ beginning DWLOAS1
– DSLV2 = Cash flows discounted at Treasury+ ending DWLOAS2
– Return Liability = DSLV2/DSLV1 - 1
– Note: Process has to be unitized to each cash flow disbursement

Review Funding Status and Surplus/Deficit Status
– Portfolio - DSLV
– Required return over treasuries
– Appropriateness of VAR


HISTORICAL SPREAD SUMMARY 23


OPTIMIZATION FRAMEWORK 24


RISK OPTIMIZATION RESULTS 25


26
ISSUES NOT CAPTURED BY DYNAMIC-SPREAD LIABILITY BENCHMARK

Duration Weighted Liability OAS (DWLOAS) does not
reflect downgraded issues leaving the benchmark each
month!

This can lead to significant over-statement of liability
benchmark returns

Solution: Key-rate-matched Market Based Benchmarks


KEY-RATE-MATCHED MARKET-BASED BENCHMARKS 27

i n
Blended Benchmark Wi * MktSeci
i 1

Definitions
– Sum of Square of Key Rate Errors = Sum (BB_Kduri minus Liab_KDuri)^2
– BB_KDuri = Blended Benchmark Key-Rate Duration I
– Liab_KDuri = Static Spread Liability Key-Rate Duration I

Solve for Wi’s
– Minimize Sum of Key Rate Errors Squared
– Subject to chosen constraints

Revisit optimization periodically
– Key-rate drift
– Funding level
– Risk tolerance


KEY-RATE-MATCHED MARKET-BASED BENCHMARKS 28

• Marking-to-Market Liabilities
– Discount liability cash flows at
Treasury + Duration-Weighted OAS of the Benchmark
• Benchmark Return = RB = Σ { Wi * Ret Secti }
• Benefits
– Better Reflects Market Conditions – Less subject to
market spread volatility
– Clear Mandate - Managers are more accustomed to
managing portfolios against market-based
benchmarks
– Transparent – More transparency of manager’s
active management added value
– More Observable – Can be independently measured


29
SUMMARY

Optimal portfolios in absolute space can lead to significant risk vs.
liabilities
Static-spread liabilities can introduce significant mismeasurement
of funding status and distort active management
Dynamic-Spread Liability Benchmarks improve funding distortions
but introduces credit migration and performance measurement
ambiguities
Key-Rate-Matched Market-Based Benchmarks mitigate many
issues related to funding status and performance measurement
Should lead to clearer definition of risk and more optimal
active management in volatile markets


30

II. Liability Driven Investing



LDI == Disciplined Approach to Investing
 Level I: Comprehensive portfolio strategy and capability analysis
 Asset-Liability Assessment
 Various Fund Due Diligence
 management and operational evaluation
 risk measures, scenario analysis, drawdown, performance analysis and attribution
 Level II: Liability-Driven Investing
 Asset and strategy allocation
 Portfolio construction & optimization

 Level III: Ongoing asset management and evaluation of emerging asset classes
 Distinguished by thoughtful and in-depth ongoing risk assessment, valuation, performance
monitoring and attribution for broad array of fixed income, equity, and alternative asset
types and strategies including esoterics

 Customized Strategies:
 Fixed Income – Short duration, Core, Core+, Long Duration, Immunization,
 Equity – Quant Equity (US, Non-US, Global), Long Only130/30, Long/Short
 Alternatives - Structured Products, Asset-based Lending, Specialty Finance, Esoterics



LDI Challenges
 Asset Management Infrastructure
 Tailored and Integrated Front To Back Office Solutions - Full turn-key front-to-back solutions and services
 Front Office: Decision support infrastructure, portfolio management workstation, up-to-date portfolio risk analytics & reporting, trade order
management and execution, valuation, asset liability management and relative value analysis tools
 Middle Office: Trade capture and processing, services, interface with depository and custodial services, collateral management, counterparty
management, performance attribution and benchmark comparison
 Back Office: Investor reporting, integration with third party administrators, performance attribution

 Solution Elements
 Quantitative and fundamental valuation, pricing and risk analysis of:
 equities, fixed income, real estate, commodities
 Hedge fund strategies, fund of funds
 Private equities
 Structured products
 Derivatives
 Esoterics
 Emerging assets
 Valuation of hard -to-value assets including residential, commercial, consumer, equipment, project finance loans and structured products
 Cash flow forecasting, sensitivity analysis, stress testing , scenario analysis, relative hedge analysis, economic/rating agency/statutory capital
 Daily, weekly, monthly portfolio and security valuation and risk analytics for broad array of fixed income, equity, structured products,
derivatives, and alternative asset types


KEY LDI REQUIREMENT - KNOWLEDGEWARE 33

Market Experience, Technology and Process

Core Competencies: Experienced professionals providing independent and transparent solutions

Experienced
Disciplined Processes Advanced Technology
Professionals
• Team comprised of traditional and • Transparent • Accessible throughout the entire
emerging assets as well as geo-political • Well tested process – allocation, portfolio
experts with deep experience in • Understood throughout organization management, risk management
trading, portfolio and risk management • Open technology to provide
• Scalable
• Quantitative and fundamental skills • Focused on both assets and liabilities customized analytics, data
• Deep understanding of intrinsic values management an actionable reporting,
• Covering both liquid and illiquid assets
• Comprehensive - asset and liability • Complex liability structures
sides

Decision
Traditional and Making
Emerging Assets

Integrated Reporting
Infrastructure
Evaluation, I Asset
nvesting, and Liability Risk Analysis
Trading Management


KEY LDI REQUIREMENT -KNOWLEDGEWARE 34

Enablers

Knowledge-
Asset Management, Risk
Management, Solutions, Kno Driven
Experience wledge-Driven Support Advice and
Services Services

Seasoned Senior
Management with Scalable Integrated
Management Deep Operating and Team of
Cross Functional Expertise

Integrated Technology,
Granular Data, Open Analytics
Infrastructure Platform, Flexible Reporting
Process and Workflow

Transparent Disciplined

Disciplined Processes
Scalable Customizable Solutions
Efficient


35

III. Relatively New Alpha Strategies


EXAMPLES OF RELATIVELY NEW ALPHA STRATEGIES 36

Emerging Sectors (New Media , Renewable)

Equity - High Frequency, Global Quant Equity

Merchant Banking

Distressed and/or Illiquid Fixed Income

Distressed Real Estate

Specialty Finance

Esoterics

Frontier Investing


ALPHA STRATEGIES AND STYLES 37

 Market-Based Fixed Income
 Short-Duration, Core, Core+, Long Duration, High Yield, Emerging Markets, Real Portfolios
 Global Quant Equities
 Long only, Long/Short, 130/30 US-only, Non-Us, or Global for small, medium, large and all cap
 Hedge Funds and Fund of Funds
 Myriad of strategies
 PRIVATE EQUITY
 Renewable
 New Media
 Cloud-computing
 Merchant banking


ALPHA FIXED-INCOME AND REAL ESTATE STRATEGIES 38

Broad Based Asset Expertise Is Utilized Through Internal and External Resources
 Active Trading
 High Quality; High Yield; Leveraged Loan; Emerging Markets
 Distressed Debt and Real Estate
 Structured Products
 Residential: REO Bridge Finance, Nonperforming Loans; REO Equity
 CRE Recapitalization
 Consumer Finance
 Specialty Finance
 Asset-based Finance
 Supply Chain Finance
 Insurance Linked: Premium finance, life settlement, longevity swaps
 Esoterics: Structured settlement, Intellectual Property, Litigation
 Real Estates
 Debt, Equity, Distressed
 Operating Companies and REITS
 Core, Value Add, Opportunistic


EMERGING STRATEGIES: MANAGING COMPLEX PRODUCTS FROM LOANS TO SECURITIES 39

Credit crisis has created unique opportunities within structured credit universe
Spectrum of issues within structured credit leads to highly attractive and
scalable skill-based asset management opportunities

Structured product expertise, technology and process knowledge
is highly specialized and leads to significant operational leverage

Residential
Real Estate

Commercial
Exotics
Real Estate

Structured
Credit Expertise
and Tools

Specialty Consumer
Finance Credit

Leveraged
Finance


40

IV. An Example of a Scalable Strategy:
Quantitative Global Equity


41
GLOBAL QUANTITATIVE EQUITY
Example of Equity Investment Philosophy
Well-defined investment philosophy and well disciplined process.

 We term our Philosophy Fundamental Objective
 We believe human behavioral biases drive many existing market inefficiencies
 We use both quantitative and qualitative research methods to exploit these inefficiencies
 Our Philosophy’s practical and analytical process dominates “emotionally driven”
approaches
 Our Process manages multi-dimensional risks by using rigorous risk controls

Fundamental  Quantitative  Practical

41

42
Quant Equity Investment Experience and Approach
We have vast expertise in equity valuation techniques across equity asset classes. Our
team have outperformed their benchmarks in long only, long short, and market neutral
strategies. We have experience in both public and private equity analysis throughout
the world and across company size.

 Factor Analysis
 Valuation
 Long/Short Relative Value
 Proprietary Nonlinear Transaction Cost Analysis
 Portfolio Optimization and Trading
 Includes transaction cost management
 Risk Management
 Scenario Testing
 Time Series
 Attribution Analysis

42

43
Quant Equity Investment Process

We base our Investment Process upon three main concepts:
 Alpha Driven
 High alpha stocks are purchased and held – except when alpha data is suspect

 Stocks become sell candidates when alpha drops below the top quintile

 Risk Controlled
 Stocks chosen to replace stocks sold are chosen to help control risk as well as to
raise portfolio average alpha

 Market, Size, Style, and Energy risk are kept close to benchmark exposure –
Northfield, BARRA, Axioma are useful tools

 Region, Sector, and Region/Sector weights are kept to within +/-10% of benchmark
weights

 Transaction Cost Sensitive
 Alpha must exceed estimated transaction costs

 Transaction costs are non-linear as trade sizes increase

43

44
Quant Equity Investment Experience and Approach
We Believe Human Behavioral Biases are the key to Quantitative Modeling.

Cause of Inefficiency Factor Group Factor Group Description

How attractively is the stock priced
Emotional Investor Behavior Relative Value relative to industry peers?

Imperfect Reaction to New Momentum/Sentiment Are analysts and investors upgrading
Information their view of the stock?

Are insiders at the company acting
Separation of Ownership and Insider/Management as if the stock is cheap in a
Management
shareholder-friendly way?

Has the stock appreciably
Impatient Trading and/or Short-term Short-Term/Technical out/underperformed its industry
Overreaction
peers recently?

News Analytics Does stock price reflect qualitative
Incomplete Information Set
information?

44

45

We divide the world into 90 categories by Region and Economic Sectors.

Region 0 1 2 3 4 5 6 7 8
Australi Middle
United Europe UK & Asia Latin
Sector FTSE AWI Weight a & New Japan Canada East &
States ex UK Ireland Pacific America
Zealand Africa
0 Oil & Gas 4.23% 1.27% 1.55% 0.18% 0.78% 0.12% 0.83% 0.71% 0.66%
1 Basic Materials 1.20% 1.38% 1.13% 0.88% 0.99% 0.61% 0.76% 0.48% 0.83%
2 Industrials 4.80% 2.45% 0.42% 0.23% 1.73% 1.64% 0.22% 0.15% 0.21%
3 Consumer Goods 4.25% 3.02% 1.05% 0.08% 1.24% 1.85% 0.05% 0.08% 0.34%
4 Health Care 4.50% 1.71% 0.74% 0.10% 0.09% 0.43% 0.00% 0.21% 0.01%
5 Consumer Services 4.93% 0.98% 0.79% 0.37% 0.53% 0.65% 0.17% 0.22% 0.26%
6 Telecommunications 1.39% 1.24% 0.59% 0.05% 0.70% 0.35% 0.11% 0.26% 0.30%
7 Utilities 1.45% 1.21% 0.35% 0.09% 0.36% 0.41% 0.03% 0.10% 0.22%
8 Financials 6.80% 4.43% 1.83% 1.48% 3.34% 1.37% 1.32% 0.63% 0.92%
9 Technology 6.75% 0.63% 0.10% 0.00% 1.43% 0.56% 0.12% 0.01% 0.00%

Portfolio Weights are controlled, relative to these categories, as part of a rigorous risk
control process which also controls for market beta, style, and size risks.

45

46

We believe experience-driven insights into the data are critical to the Process.

 Bad Earnings Data: Spreadsheet Manual Entry
 Conditions Change: Morning Earnings Surprise
 Conditions Persist: Short-Term Price Reversal Window
 Complex Industry Schemes: Japanese Financials, European Industrials
 Global Correlations: Oil and Financials

Good managers confirm the quantitative results, they don’t obey it.

46

47
Quant Equity Team’s Investment Performance
Our team has outperformed their benchmarks since 1996
 Managed 5-star Morningstar international equity long-only fund

 Responsible for $10 billion in long-only mandates

 Demonstrated value-add from both long and short positions

Time Strategy Benchmark Period
Asset Class Benchmark Period Return Return Alpha

International BNY 2004 to 9.8% 7.1% 2.7%
130/30* ADR/FTSE 2010
Long Only MSCI EAFE 1996 to 5.9% -0.9% 6.8%
International** 2002q1

US Large Cap*** S&P 500 1996 to 9.4% 6.8% 2.6%
2010

US SMid Cap*** Russell 2500 1996 to 17.5% 9.3% 8.2%
2010
* Returns are gross of fees.
Note on the Benchmark and Universe: The fund Benchmark changed from the Bank of New York ADR Index to the FTSE All-World ex US Index on
1/1/2007 to reflect the expansion of the portfolio’s composition. Through November 2006, our universe consisted of the 650 most liquid ADRs and US
GDRs. On December 1, 2006, our universe expanded to include 4,000 of the most liquid common equity shares on local exchanges in the global markets
ex-US. Data referring to excess return over a “Benchmark” refers to the Benchmark that was in effect at the time in question.
** Long Only International performance was produced at ING/Aeltus Investment Management in mutual fund and institutional separate account vehicles
including a five star Morningstar rated mutual fund.
*** Large Cap and Smid Cap performance was produced at ING/Aeltus Investment Management in mutual fund and institutional separate account vehicles
from 1996 until 2004.

47

48
Quant Equity Product Research & Development
We have developed a superior International Small Cap Model:

Global
SC Fund Alpha Predicted Actual

9/30/2003 Tracking Error Tracking Error

Inception 2003 14.63% 16.50% 1.88% 3.9% - 4.1% 6.0%

2004 30.42% 43.22% 12.80%

2005 22.51% 50.62% 28.11% Periodicity Hit Rates

2006 32.55% 45.15% 12.60%

2007 13.56% 23.21% 9.65% Monthly 69%

2008 -52.03% -46.02% 6.02% Quarterly 93%

2009 61.24% 69.32% 8.09% Annually 100%

Part Year - Nov 2010 14.13% 19.81% 5.67%

Annualized Since Inception 13.21% 24.90% 11.69%

Time Period September 2003 to November 2010;

48

49
Quant Equity Product Research & Development

An additional model for the US market:

Annualized Alpha
14.0%
12.5%
12.0%
9.8%
10.0%
8.6%
7.7%
8.0%

6.0%

4.0%

2.0%

0.0%
International v FTSE AWI Smid Cap v Russ 2500 Large Cap v S&P 500 Index Large Cap v Russ 1000
ex US Index Index

Annualized Alpha

Top Decile Versus Benchmark
Time Period 2001 to 2010

50

V. Dodd-Frank and Its Impact on LDI


THE DODD-FRANK WALL STREET REFORM AND CONSUMER PROTECTION ACT 51

The Dodd-Frank Wall Street Reform and Consumer Protection Act ("Act") passed in July
2010 and required several regulatory agencies including the SEC, CFTC and FDIC to
propose and finalize more than 500 rules in order to give shape and structure to the
sweeping reform of the financial regulatory system envisioned by the Act.
Several key regulations under Title VII of the Act related to the $600+ trillion
derivatives market are being finalized in 2011
General objectives are transparency, reducing systematic risk, ensuring orderly
markets OTC derivatives markets
Significant objective is to move the OTC derivatives transactions (“Swaps”) activities to
the regulated exchanges with clearing through central clearing houses
Use of clearinghouses “mutualize “ the counterparty risks among members hence
reduce the systematic risks
 Implications:
The definition of “swap” is very broad
All parties will be affected and need to assess the relevant compliance rules,
operational risks, business costs, and how it affects them.
No one is exempted from record keeping, reporting, and rules of conduct

Fund Managers Under Dodd-Frank 52

Challenges and Requirements Ahead for OTC Derivatives Activities
Collateral management requirements including
Counterparty risk management
Liquidity management
Risk-based margining
•Marked-to-market and Value-At-Risk
•Collateral optimization
 Operational
•Collateral amount verification
•Collateral movements mechanism and costs
 Administrative
•Record keeping and reporting
•Rules of conduct
Hedge Fund Transparency
Fund-of-fund position aggregation
Collateral management validation and optimization
Hard-to-value assets and investor reporting

Fund Managers Under Dodd-Frank 53

Methodical Steps to Take
Types of Transactions
 Currently involved in (“on the book”)
 Contemplated transactions
 Entity Classification
 Highly Regulated – depends on level of activity as well as purpose
•SD – Swap Dealer
• MSP – Major Swap Participants
 Eligible Financial Participants –ECP
•Can do bilateral transactions
•Must have a level of sophistication and financial means
Less Regulated - Commercial End Users (“CEU”)
• Must be using it for hedging or mitigate risk
•Cannot be a financial entity!
 Execution and Clearing Requirements
 Not all swap types require centralized execution and clearing but most do

COLLATERAL MANAGEMENT FOR INSTITUTIONAL ASSET MANAGERS 54

Integral part of risk and liquidity management

CREDIT RISK EXPOSURES
• SECURITIES LENDING
• PORTFOLIO LOANS
• OTC DERIVATIVES
• IF NOT ALREADY WILL BE 100% SUBJECT TO ISDA, CSA, AND COLLATERAL POSTING
COLLATERAL MANAGEMENT MITIGATES COUNTERPARTY CREDIT RISK BUT INTRODUCES
OPERATIONAL RISKS
CREDIT RISK MANAGEMENT LEADS TO COLLATERAL MANATEMENT
 OPERATIONAL ISSUES
TIMELY FORECAST OF VARIATION MARGINS
• DERIVATIVES AND COMPLEX SECURITIES PRICING
SENARIO ANALYSIS
 VALUATION AGENT AND DISPUTE MECHANISIM
COMPLEX DOCUMENTAION
OPTIMIZATION
TIMELY EXECUTION
REHYPOTHECATION CAN LEAD TO CASCADING EFFECTS

WHO NEEDS COUNTERPARTY AND COLLATERAL RISK MANAGEMENT CAPABILITIES 55

VAST ARRAY OF FINANCIAL INSTITUTIONS WITH COUNTERPARTY EXPOSURES

Banks • Global and Domestic Banking Institutions

Insurers
, REITS, Specialty • Life and P&C Insurance Companies, Reinsurers, REITS, Specialty Finance
Finance

Asset
Managers/Treasurers • Traditional and Alternative Asset Managers, Treasurers

Governmental Agencies • Central Banks, Sovereign Funds, Supra-nationals, Government Agencies

Pension & Endowments • Pension Funds, Foundations and Endowments


56

VI. LDI - Solutions and Infrastructure Needs


LIABILITY DRIVEN INVESTING 57

LDI REQUIRES AN NTEGRATED APPROACH TO RISK, ASSET AND FINANCIAL MANAGEMENT

Front Office:
Portfolio
Workstation, Risk
& Trade
Management, AL
M

STRUCTURED: Middle
GLOBAL FIXED FIXED INCOME RMBS, CMBS, Office: Trade
INCOME DERVIATIVES ABS, CDO, CLO, Regulatory Reporting & Processing, Cleari
Compliance
ng, Valuation, Col
CSO, SIVS lateral
Management

INTEGRATED
APPROACH TO
WHOLE LOANS REAL ESTATE ALTERNATIVES ASSET
MANAGEMENT
SERVICES

GLOBAL EQUITIES PRIVATE Counterparty Back Office:
and Collateral Reporting, Performance
EQUITIES DERIVATIVES EQUITIES Measurement, Attribution
Management

Liquidity, Credit & Asset
Liability Management


ASSET MANAGEMENT/RISK MANAGEMENT ENVIRONMENT 58

INFRASTRUCUTURE REQUIREMENTS RAPIDLY RISING WITH THE SIZE OF OPPORTUNITIES

The environment is ideal penetrating and Well-Defined
capturing market share in regimented Strategies:
Fixed, Equities, Asset-
global fixed income, equity, and alternative Based
Lending, Specialty
asset management Finance

Front Office:
• The mounting importance of asset liability Counterparty and
Collateral Management Portfolio, Risk & Trade
Management
and credit management
• The growing demand for global fixed
income and diversified equity products
• Increase in fixed income-focused
financial institutions Asset/Risk
• Global quant equity opportunities
• Global growth of multi-family offices Regulatory Reporting &
Management Middle Office:
Trade
Processing, Clearing, V
Compliance
• Ever increasing demand for articulated and aluation, Collateral
Management
transparent asset management by pension
plans, private wealth and financial
institutions
• The mounting complex regulatory risk
Back Office:
management and reporting requirements Credit Risk & Asset
Liability Management
Reporting, Performance
Measurement, Attribution


ANALYTICAL PLATFORMS NEEDS 59

TRANSPARENT, COMPREHENSIVE, AND SCALABLE
TM
Must be designed to leverage the best technology and expertise to provide best-in-class solutions to
optimize the following key concerns:
 Transparent and comprehensive
 Embracing modern technologies to overcome legacy platform issues
 Incorporate valuation, attribution, scenario analysis & reporting

Performance Scalability
Fixed Income Equities
Customization Usability
Portfolio Alpha
Mgmt Models

Web-based Reporting

Credit Risk
Customizable Risk Models
Analytics Mgmt
Complex
Rapid Deployment
Securities & Derivatives
Loans
Multi-Entity

High Availability

Hosted Services, Cloud Computing


WORLD OF COMPLEXITY 60

Sophisticated Analytical & Execution Platform Needed

Cross-Asset Class Capability Is Required for A Comprehensive Counterparty and Collateral Management System

COMPLEXITY

COMPLEX SECURITIES
DERIVATIVES ILLIQUID LIQUID CONTINGENT
CLAIMS

SECURITIES AND DERIVATIVES
RMBS CMBS Consumer ABS HY & IG Bonds Esoteric Assets

LOANS/CREDITS
Residential Commercial Consumer / Student Corporate Esoterics Contracts
Mortgage Mortgage Loans Credit

GRANULARITY

Comprehensive state-of-the-art large scale analytical systems needed for valuation and risk management of complex securities and
portfolios .
 Credit intensive analysis is needed for most instruments to uncover risks not apparent from traditional analysis.
 Forward-looking views and scenarios to
 Multivariate stresses needed to be applied around forecasts to capture alternate future states of the world
 Interest rates, currencies, defaults,


OPEN RISK SOLUTIONS 61

Next Generation Portfolio and Risk Management Platform

 Integrated platform – open, flexible, connecting risk management, portfolio management, trading,
collateral management, financial management and reporting
 Multi-asset class covering, liquid, illiquid, complex and derivatives, US and international
 Proprietary plus open-interface credit and factor models supporting risk management, alpha generation,
TM
and asset allocation

Fixed Income Equity Derivatives

Complex Stratus - Loan
Portfolio Risk Alpha & Risk Portfolio Electronic Risk & Collateral
Securities & Collateral
Management Management Models Management Trading Valuation Management
Esoterics Management


NEWOAK SOLUTIONS OpenRisk™ - OpenFixed 62

Next Generation Valuation & Risk Services
 NewOak OpenRisk provides a comprehensive capabilities to managing multi-asset-class portfolios
 Leveraging NewOak’s superior credit analytics and technology, NewOak can provide cost effective services across a variety of
important functions:

Deep-Dive Credit •See-through valuation, loss, cash flow analysis of structured products – RMBS, CMBS, CDO.
CLO, Esoterics
Analysis
Risk Reporting •Risk reporting across first and second order sensitivities

Cash Flow •Projected interest and principal (maturity, calls and prepayments) cash flows provided for static
Forecasting (fixed-rate) and user defined dynamic scenarios (customizable shocks)

Reinvestment Rate •The impact of changes in fixed rate and spread to benchmark upon projected cash flows
Analysis

Inflation Risk •Portfolio and asset class sensitivities to changes in realized and projected inflation rates

Horizon Analysis •Projected return and forward-looking risk profile from user-defined interest rate shocks

Drilldown Capability •Aggregate analytics provided at sector, subsector and cusip levels

 With a customizable service model, NewOak can multiple deployment options:
 Data Services
 Hosted “Software-as-a-Service”
 In-House installation and management.


COUNTERPARTY RISK MANAGEMENT 63

Opportunities and Perils In Counterparty and Collateral Management

Spectrum of complex documentation
COUNTERPARTY
interpretation, computation, valuation, optimi CREDIT ANALYSIS
zation, and execution leads to challenges and
opportunities for state-of-the-art collateral
management systems and operations CREDIT
TIMELY EXPOSURES
EXECUTION DERIVATIVES &
LOANS

COUNTERPARTY
Future RISK
Today MANAGEMENT

Legacy
OPTIMIZATION ISDA & CSA

VALUATION &
Monitoring


FLEXIBLE SYSTEM APPROACH TO REDUCE OPERATIONAL RISK 64

Collateral Management Capabilities Is Becoming A Requirement

Systems to consolidate data across multiple
Documentation
Valuation/ platforms, sources and formats into a single
Sensitivities integrated framework.
CSA, Master Method
ISDA, Scripti
ng Agent

Position
Monitoring Tracking Cross Collateral Capability
Dispute Simulation
Resolution Liquidity Integrate Data from multiple sources and formats
Management
Optimization/
Credit
Netting
Rules-based workflow engine

Customizable Reporting and Stratification of Portfolio

Real-time reporting and status update

Collect

Collateral Web-based for global distribution
Management & Analyze

Reporting
Execute


New Oak Creating An Effective Risk Modeling Framework (Pensions Risk Management)

New Oak Creating An Effective Risk Modeling Framework (Pensions Risk Management)

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