QuandamentalTM Approach to Fixed Income Management

Ron D’Vari, CFA, Managing DirectorState Street Research and Management

Fixed Income Forum, San Diego

July 19, 2002

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Traditional Fixed Income Management Styles Need To Be Augmented

Macro Shop– Interest rates and curves are not as trendy and predictable– Shocks are frequent and can ruin several years of performance– Bets need to become tilts: calculated, diversified, mild, and

gradual

Credit Shop– Credit markets shocks are becoming unavoidable– Concentrated credit portfolios have unacceptable risks– Credit risk need to be evaluated in the portfolio context

Mortgage Shop– True arbitrage opportunities are few and far in between– No strategic value in writing options– Bets need to be explicit and become tilts

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QUANDAMENTALTM Process

Ensure value is added consistently over time using disciplined processes

– Formulation of consistent winning strategies

– Product templates and maps• sources of alpha and tracking error

• Probabilistic evaluation of tactical and strategic portfolio biases

Facilitate creative decision making process – Blend creative fundamental thinking with quantitative methods

– Disciplined forecasting

– Consistent cross sector relative value Risk adjusted

– Portfolio optimization and construction

– Risk management

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Common Themes

Full integration of risk management and portfolio management processes

Common process for all products and portfolios– Mass customization?

• Core, Core Plus, Intermediate, Long, and Structured Products

Both Top-down and Bottom-up

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Role of Quants in the Organization

Product definition and design

Process definition and tools• Design and conceptualize tools to be implemented by IT

Add value by blending smart ideas and quantitative concepts

Challenges:

Cultural

Finding people with both quantitative and fundamental strength

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Cross-Sector Relative Value Process

SectorInformation

- Fundamental- Technical- Valuation

Bond Policy- Optimized curve and sector

exposures- MAC, IG Corp, HYLD and EMG

sector allocation versus normal- Portfolio maps

Bond Policy Curve and Swap Spread Forecast- Quantitative tools- Fundamental judgment- Risk/reward reconciliation

Risk-Controlled Sector Optimization

Bottoms-Up Analyst/Sector Evaluation

- Factor Sheets- Analyst rating- Spread forecast

Macro Environment- Factors affecting U.S. economic

growth (Economic, Monetary, International, Political, Asset Markets)

- Economic scenarios and probabilities (GDP, Inflation, FF)

Quantitative Cross-Sector Relative Value Tools

- Relative Statistics- Volatilities- Relative Z scores and ranges- Cross plots- Market snapshot- Internal and LehmanLive

Sector Teams- Optimal implementation plan- Intra-sector relative added-value- Security selection- Monitoring and re-evaluation- Bond policy feedback

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Normal WeightTactical

Activities Added Value

Strategic Bias* Added

Value

Total Expected

Alpha Contribution

Expected Tracking Error Contribution

Expected Information Ratio

Turnover Estimates

Duration and Curve N/A 25 bp 0 bp 25 bp 38 bp 0.67 45.0%Agencies -10.0% 0 bp -5 bp -5 bp 6.8 bp -0.74 0.0%MAC 10.0% 5 bp 11 bp 16 bp 27 bp 0.58 15.0%

Corporates 5.0% 11 bp 7 bp 18 bp 27 bp 0.67 21.5%

High Yield 10.0% 0 bp 30 bp 30 bp 50 bp 0.60 0.0%Emerging Markets 2.5% 0 bp 15 bp 15 bp 30 bp 0.50 0.0%Nondollar 0.0% 7.5 bp 0 bp 8 bp 12 bp 0.63 6.0%

Total Portfolio 17.5% 48 bp 58 bp 106 bp 190 bp 0.56 Security Turnover 87.5%

* Intermediate to long term TBAs 60.0%Future 0.0%

Sample Product Sources of Added Value

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Product Definition

Product Templates - Long Term– Tactical

– Strategic

Product Maps– Detailed targets per sector/credit/duration bucket

– Daily monitoring of absolute and relative Exposures• Portfolio vs. Target

• Portfolio vs. Benchmark

Transparency of Risk/Reward Goals Throughout Organization

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Quantitative Models

Quantitative models are used to support key decisions and are an integral part of the overall process

– Interest and Curve Models• Interest rate forecast

• Curve forecast

• Treasury hump (20 to 25 year part of the curve)

– Swap Spread

– Value-at-Risk and Risk-Constrained Optimization

– Credit driven scenario models for structured products

– Prepayment and credit scoring for ABS securities

– Specific and portfolio credit risk models

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Risk-Constrained Optimization Model

Proprietary model creates robust framework for comparing risk and reward across sectors

Model Objectives: Within the context of forecast scenarios, define maximum-return portfolio subject to acceptable risk levels.

– Inputs:• Expected yield/spread changes

• Historical pricing data for sectors

• Current benchmark structure and portfolio holdings

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Our Idea of QuandamentalTM Fixed Income Investment Process

Research-driven– Highly product focused and designed to deliver

Value-oriented– Flexible relative value framework

Quandamental– Robust quantitative framework to support every major

decision

Balanced– No single factor drive overall performance over time