2. 1 OVERVIEW OF AN INTEGRATED QUANTITATIVE FRAMEWORK IN FIXED-INCOME PORTFOLIO MANAGEMENT February 17, 1999 Global Association of Risk Professional Boston Ron D’Vari, Ph.D., CFA

3. Ron D'Vari2 The Three Pillars of Fixed-Income Portfolio Management Relative Valuation and Process Honing Ex Post Market Monitoring and Performance Attribution Ex Ante Market Expectations and Risk/Exposure Measurement Portfolio Synthesis & Optimization

4. Ron D'Vari3 Uniform and Consistent Implementation of Market Views on Risk/Return  Multiple accounts  Distinct investment guidelines  Varied benchmarks Proper Integration of  Sector views in portfolio synthesis  Changing view of risk environment  Performance attribution in process improvement Uniform Framework for Portfolio Positioning Standardized Multivariate Risk Reports  Transparent and frequent (daily)  Comprehensive yet easy to understand  Address multidimensionality of risk Separation of Trading from Portfolio Management ROLE OF MULTI-FACTOR MODELS IN FIXED-INCOME PORTFOLIO MANAGEMENT

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6. 5  Factor Move Estimation and Monitoring  Factor Return Attribution Consistent with Risk Measurement  Portfolio Re-optimization  Sector/Quality Relative Valuation  Tactical SectorAllocation  Strategic Asset Allocation  Overlay Risk Hedges  Investment Process Honing  Evaluation of Asset Mix Policy Ex-Post Market Move Monitoring and Decomposition Feedback Into The Investment Process

7. Ron D'Vari6 Elementary Risk Models

8. Ron D'Vari7 Multi-Factor Risk Models

9. Ron D'Vari8 Traditional Approaches  Decoupled Macro (overall plan) vs. Micro (Portfolio)  Macro: Highest risk-adjusted return via asset allocation  Micro: Focus on highest return but often ignore incremental risk (stock/bond picking)  No Integrated Risk Management  Static Approach Using Forecast Returns  Relies on historical volatilities and correlations  Neglects short horizon risk  Ignores risk premium fluctuations  Does not take advantage of short term mispricing

10. Ron D'Vari9  Breaks up risk in to its lowest common denominators  Integrates risk management with active management strategies  Use forward-looking view of expected returns, volatilities and correlations  Dynamic Approach  Forecast both expected returns and volatility  Focus on forecast risk-adjusted returns  Considers environment where expected returns are constant but volatility might have risen  Portfolio risk/return characteristics vs. Benchmark State-of-the-Art Approach

11. Ron D'Vari10 FIXED INCOME RISKS CURVE SHAPE - Parallel - Twist - Butterfly - Higher Principal Components - Residual VOLATILITY - Short End - Long End - Volatility Correlations - Historical vs. Implied CREDIT - Spread Term Structure - Spread Volatilities and Correlations - Per Sector/Quality - Residual Per Issuer OTHERS - Prepayment - Currency (V/C) - Sovereign - Liquidity Premium - Model - Legal - Political - Taxes

12. Ron D'Vari11 EQUITY RISKS MARKET - Domestic Equities - Foreign Equities - Beta Risk - Correlations Risk - Return Momentum - Size - Earnings: P/E - Value: B/P - Growth - Dividend Yield - Leverage [D/(D+E)] - Liquidity - Foreign Exposure - Technology - Financial - Services - Telecommunications - Transportation - Utilities - Energy - Healthcare - etc. VOLATILITYFUNDAMENTALSSECTORS - Domestic - Foreign - Volatility Correlations - Historical and Option-Implied

13. Ron D'Vari12 HARD TO QUANTIFY RISKS EMERGING MARKETS - Insufficient Data/ Information - Insufficient Credit Legal/Political Risk Methodology - Data Incomparability - Convertibility - Expropriation - Tradability STRUCTURED PRODUCTS - All Other Risks - Basis Risk - Liquidity Risk - Counterparty Risk CUSTODIAL - Accurate Accounting - Settlement & Disposition - Discrepancy Reporting - Information Accuracy - Timely Monitoring - Tradable Pricing - Securities Lending, Cash Management, etc. - Credit - Administration Errors MODEL - Insufficient Basis - Oversimplification - Missing Significant Factors - Implementation Errors - Insufficient Data - Unaccounted Structural Changes

14. Ron D'Vari13 ADDED-VALUE FINANCIAL RISK MANAGEMENT FORWARD VIEW REAR VIEW SYNTHESIS RISK MODELS BENCHMARK COMPARISON BENCHMARK VARIANCE SCENARIO ANALYSIS (STRESS TESTING) VAR (NONLINEAR) PERFORMANCE ATTRIBUTION RISK ADJUSTED RETURN RELATIVE VALUATION STRATEGIC/TACTICAL ASSET ALLOCATION SCENARIO OPTIMIZATION RELATIVE VALUE ANALYSIS

15. Ron D'Vari14 INTEGRATED FIXED-INCOME MULTI-FACTOR MODEL

16. Ron D'Vari15 MARKET

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19. Ron D'Vari18 VOLATILITY Volatility Risk  Volatility Sensitivity Prepayment and Call Risk  Function of Interest Rates and Volatility  Can be measured and managed by Prepayment Elasticities and Convexity

20. Ron D'Vari19 CREDIT Default  Spread  Measured and Managed by Effective Spread Duration (Sprdur) OTHERS Currency, Liquidity, Model, Operational, Counterparty, etc.

21. Ron D'Vari20 FACTORS

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23. Ron D'Vari22 FIXED-INCOME ANALYTIC Accurate Stochastic Interest Rate Term Structure Models  Arbitrage Free One-Factor Models Arbitrage Free Lognormal with Mean Reversion Term Structure of Volatility Stable Forward Curve Efficient and Accurate Implementation  Arbitrage Free Two-Factor Models Term Structure of Volatility Mortgage Passthroughs, CMO’s, Special Securities Monte Carlo Simulation  Yield Curve Estimation Methodology (Fitting)  Volatility Forecasting Methodology

24. Ron D'Vari23 FIXED-INCOME ANALYTIC, cont. Option Adjusted Sensitivity Analysis Curve Reshaping Spread Volatility Prepayment Models for Agency and Non-agency Mortgages Extensive Security Modeling Tools Call, Put, Conversion, Sinking Fund Structures, Make-Whole Calls CMO’s, Asset-backed Securities, Floating Instruments with Caps/Floors/Collars, Multi-index Floating Derivative’s Structuring Tools Exchange and OTC Traded Fixed for Floating, CMT, and Fixed-for-Fixed Swaps Forward Swaps and Swaptions Credit Derivatives

25. Ron D'Vari24 Option Adjusted Risk Factors Absolute, Relative, Target Relative Curve Sensitivities by Sector  Effective Duration to Parallel Shift of Spot curve  Effective Twist Duration (yield curve steepenning)  Effective Barbell Duration (yield curve bulging)  Effective Convexity Sensitivity to Key Rates Sensitivity to Prepayment Factors Sensitivity to Volatility Spread Duration Risk Sensitivity to Currencies Sensitivity to Country Correlation Assumptions (for tracking error)

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27. Ron D'Vari26 DAILY RISK REPORTS Relative Curve Exposures, Yield, OAS, Convexity Absolute Curve Exposures Absolute and Relative Sector Exposures  % Invested and Duration Contribution Duration/Sector/Quality Bucket Exposure Full-Valuation Scenario Returns by Sector  Absolute and Relative  Factor Returns

28. Ron D'Vari27 FIXED-INCOME PERFORMANCE ATTRIBUTIONS Two Approaches: Periodic Performance Attribution  For selected accounts with special benchmarks  Division to sub-periods (portfolio & benchmark) Portfolio action Market moves Cash Flows Daily Performance Attribution  For all portfolios and composites

29. Ron D'Vari28 GENERAL METHODOLOGY Detailed sub-period return attribution to:  Yield, roll-down, convexity, curve, sector/quality, selection, and trading Bottom-Up Approach Geometric Linking Accounts for Cash Flows at sub-period levels

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31. Ron D'Vari30 YIELD/ AGING Beginning portfolio return under unchanged yield curve, OAS, and volatility scenario Includes accrued as well as accretion (aging) CURVE Beginning portfolio return with end period curve and volatility under OAS unchanged scenario less yield Decomposed to convexity, duration, twist, and butterfly Curve residual/selection component for periodic attribution

32. Ron D'Vari31 NONCURVE (OAS+VOL) Beginning Portfolio’s Buy-and-hold Total Return Minus [(Yield+Aging)+Curve Returns] Attributed to Credit Sector factor move (OAS) Security specific OAS move Selection/Residual

33. Ron D'Vari32 INTRA-PERIOD TRADING Calculated only for periodic approach Difference of the actual return of the portfolio from the buy-and-hold Portfolio’s actual total return (accounting) includes the effect of client-directed cash flows

34. Ron D'Vari33 PERFORMANCE ATTRIBUTION PITFALLS  Plain bad pricing  Non-contemporaneous pricing  Benchmark and Portfolio  Sectors  Curve calculation  Coarse generic pricing  Insensitive to sector specific factors, e.g.  WAM, WAC, seasoning, age, volatility

35. Ron D'Vari34 PERFORMANCE ATTRIBUTION PITFALLS, cont.  Client-directed actions & cash flows that affect performance  Over Linking and Cross Factor Returns  Benchmark Changes and Inaccuracies  Sponsor initiated changes  Benchmark pricing  Forward benchmark vs. Backward benchmark  Exclusion/Inclusion of new asset classes

36. Ron D'Vari35 CONCLUSIONS Comprehensive Multi-Factor Model  Intuitive Factors  High Fidelity Yield Curve Sensitivity Model  Detailed Sector/Benchmark Comparison Analysis (BCA)  Scenario Analysis (SA) and Optimization (SO) Uniform Measurement of Risk and Implementation of Market Views  Across Hundreds of Portfolios with Different Benchmarks and Investment Objectives  Consistent Reporting

37. Ron D'Vari36 CONCLUSIONS (Cont’D) Other Benefits  Performance Attribution Multi-factor Accurate Consistent with Risk Model  Quantitative Security and Sector Valuation Framework Multi-factor valuation Accurate Consistent with risk and performance attribution models