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PURSUANT TO AN EXEMPTION FROM THE COMMODITY FUTURES TRADING COMMISSION IN CONNECTION WITH POOLS AND/OR ACCOUNTS WHOSE PARTICIPANTS ARE LIMITED TO QUALIFIED ELIGIBLE PERSONS, AN OFFERING MEMORANDUM FOR THIS POOL AND/OR THIS BROCHURE OR ACCOUNT DOCUMENT IS NOT REQUIRED TO BE, AND HAS NOT BEEN, FILED WITH THE COMMISSION. THE COMMODITY FUTURES TRADING COMMISSION DOES NOT PASS UPON THE MERITS OF PARTICIPATING IN A POOL AND/OR TRADING PROGRAM OR UPON THE ADEQUACY OR ACCURACY OF AN OFFERING MEMORANDUM AND/OR COMMODITY TRADING ADVISOR DISCLOSURE. CONSEQUENTLY, THE COMMODITY FUTURES TRADING COMMISSION HAS NOT REVIEWED OR APPROVED THIS OFFERING OR ANY OFFERING MEMORANDUM FOR THIS POOL AND/OR THIS TRADING PROGRAM OR THIS BROCHURE.
Reinventing Risk Management in the Wake of the Financial Crisis
Insurer Investment Forum IX
April 1, 2009
David Lee, CFASenior Fixed Income Portfolio ManagerGoldman Sachs Asset Management
2
Key Questions
What is ERM and why is it important?
What happened in the markets and how might ERM have helped?
What are the key components needed to implement a strong ERM program?
How does ERM integrate with day-to-day investment management?
3
An ERM program comprehensively applies Risk Management:
Across ALL significant risks of the Enterprise
Consistently across the risks
Consistent with the fundamental objectives of the enterprise
With the purpose of increasing the organizational value
4
Why is ERM important?
Evolution of the Credit Crisis 2007-Present
Fed and Government Policy Responses help stabilize the market
Housing and Economic Recovery Act
Initial signs of stabilization
Govt’s takeover of the GSEs
Intensified distress within financials
Lehman, Merrill, WAMU, Wachovia
TARP
FDIC Temporary Liquidity Guarantee Program
Capital Purchase Program
TARP focus shifts
Fed MBS Purchase Program
Homeowner Affordability and Stability Plan
TALF announcedPri
ce A
BX
(A
AA
, CM
BX
)
Price (A
A)
Govt InterventionFinancial Institutions Problems
Liquidity CrisisGlobal Credit Crunch
Market withdrawal
Start of the vicious credit cycle
Subprime originator problems
Higher credit losses leading to rating instability
Origination market closing
Tighter underwriting standards
Losses on subprime-related investments in portfolios of banks and hedge funds globally
Liquidity crisis fueled by crisis of confidence and global deleveraging
Funding markets deteriorate
Deleveraging intensifies
The collapse and rescue of Bear Stearns
Source: JPMorgan, GSAM, as of March 5, 2009. This information discusses general market activity, industry or sector trends, or other broad-based economic, market or political conditions and should not be construed as research or investment advice. Please see additional disclosures.
25
35
45
55
65
75
85
95
Jan-
07
Feb
-07
Mar
-07
Apr
-07
May
-07
Jun-
07
Jul-0
7
Aug
-07
Sep
-07
Oct
-07
Nov
-07
Dec
-07
Jan-
08
Feb
-08
Mar
-08
Apr
-08
May
-08
Jun-
08
Jul-0
8
Aug
-08
Sep
-08
Oct
-08
Nov
-08
Dec
-08
Jan-
09
Feb
-09
0
10
20
30
40
50
60
70
80
90
100
ABX.HE 07-1 AAA (LHS) CMBX.NA.3 (LHS) ABX.HE 07-1 BBB- (RHS)
5
All sectors other than swaps underperformed significantly in 2008
Non-government-backed sectors underperformed in February, giving back some of January’s strong gains
Concerns about the health of financial institutions and increased government intervention caused riskier segments of the market to sell off
Yields continued to rise in February, albeit at a slower pace than January, as renewed investor concerns about the state of the economy caused the flight-to-quality trend to reemerge
Going forward, the Fed is expected to pursue unconventional easing methods to stimulate aggregate demand, such as direct purchases of longer-dated Treasuries
Sector Excess Returns Over Treasuries (%)US Yield Curve Changes
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
3mo
1 3 5 25
Yie
ld (
%)
31-Dec-08
31-Jan-09
28-Feb-09
US Treasury 3 Month 6 Month 2 Year 5 Year 10 Year 30 Year
Yield as of 31-Feb-09 (%) 0.25 0.45 1.02 2.02 3.03 3.72
Yield as of 31-Jan-09 (%) 0.24 0.36 0.94 1.87 2.84 3.61
Yield as of 31-Dec-08 (%) 0.14 0.27 0.76 1.53 2.22 2.69
Feb-09 Change (%) +0.01 +0.09 +0.08 +0.15 +0.19 +0.11
Feb-09 Return (%) 0.02 0.02 0.00 -0.39 -1.29 -1.90
2009YTD Change (%) +0.11 +0.18 +0.26 +0.49 +0.81 +1.03
2009YTD Return (%) 0.02 0.04 -0.15 -1.41 -5.80 -16.16
5.4
-1.1 -2.3
-22.2
-32.7
-19.9
-38.3
-25.0
-2.1
0.7 0.7
-0.7-3.6
-1.4 -2.7
-0.4-0.4 0.7 1.3
6.6
-5.6
2.34.7 3.7
-45
-40
-35
-30
-25
-20
-15
-10
-5
0
5
10
10-yrSw ap
AGY MBS ABS CMBS Corp -IG
Corp -HY
EMD -Sov
2008
Feb-09
2009YTD
This information discusses general market activity, industry or sector trends, or other broad-based economic, market or political conditions and should not be construed as research or investment advice. Please see additional disclosures.
6
Sectors have become extremely dislocated – causing solvency problems for certain investors, but also an opportunity for others
31-Dec-06 (Pre-Crisis)
30-Sep-08 31-Dec-08 27-Feb-09 (Current)
Change (Pre-Crisis vs.
Current)
Non-Agency ARMs (Alt-A) 46 1,452 1,650 2,634 +2,588
Agency ARMs 8 137 171 104 +96
Agency Passthroughs -18 23 79 24 +42
CMBS 23 390 855 1,220 +1,197
Investment Grade Corporate 48 369 516 477 +429
High Yield 236 1,009 1,745 1,649 +1,413
Bank Loan 255 936 1,842 1,564 +1,309
CLO AAA 24 350 600 650 +626
CLO AA 40 700 1,500 2,000 +1,960
EMD 114 306 558 506 +392
ABX 07-1 AAA 100.0 52.1 39.7 29.0 -71%
ABX 07-1 AA 100.0 11.8 5.5 4.6 -95%
ABX 07-1 BBB- 97.5 5.5 3.0 2.5 -95%
LIB
OR
OA
S (
bp
s)P
rice
($)
CMBS spread is swap spread. Bank loan: Discount Margin (3-year life). Source: GSAM, Barclays, JP Morgan, Yieldbook, Credit Suisse, Merrill Lynch. This information discusses general market activity, industry or sector trends, or other broad-based economic, market or political conditions and should not be construed as research or investment advice.
7
Key Characteristics of Effective Risk Management
Corporate culture that views risk management as a core strategic value, delivering significant competitive advantage to the firm
Policies that elevate risk management responsibilities to the highest ranks within the organization
Effective frequent communication between senior management, business lines, and independent risk management functions
Devotion of significant time and resources to independent risk management and monitoring process
Comprehensive data collection and risk assessment processes to assess aggregated risk
8
Policies that elevate risk management responsibilities to the highest ranks within the organization
Board of Directors
CFOCEOCRO
Risk Management Dept. 1 Dept. 2 Dept. 3 Dept. 4
Enterprise Risk Management Committee
Department 1
Department 2
Department 3
Department 4
Department Heads
Targets
Limits
Capital Allocation
Processes
Risk & Return Estimates
Process Evaluations
Reporting and Feedback
…..strong buy-in from the top is essential
Example of Organizational Risk Structure
RiskManagement
9
Effective and frequent communications among senior management, business lines and independent risk management functions
Oversight & Governance
Enterprise Risk Management Committee Establishes overall risk framework and limits across departments
Limits set at levels we expect to breach, forcing conversation
Risk Analysis & Decision Making
Department Risk Committee Establishes sub-limits within the Enterprise Risk Management Committee limits
Allocates limits to individual businesses/products/asset classes
Execution Individual Units within Departments Make risk-based decisions within established constraints
Aggregation & Reporting
Risk Management Group Exposure aggregation by product, departments, and region
Conduct stress tests, scenario analyses, and other risk assessments
Reporting to Board/Audit Committee, senior management, department control functions, regulators, rating agencies, and auditors
Daily:
Urgent and/or high risk issues to senior
management
Weekly:
Aggregate Exposures and significant
issues
Quarterly: Comprehensive Portfolio Review
Ad Hoc:
Updates on topical issues
Example of the communication loop
10
ERM is an integrated governance, measurement, and management of the risk-taking of an organization
Common definition
Data
Technology
Process
Organized acceptance of risk management control principles and the development of a “language” of risk
High-integrity, integrated position data, analytics and historical returns
Implementation of a system that accurately captures, analyzes and distributes risk information
Establishing appropriate responsibilities, limits, policies, and procedures
3 Key Components for Success
Effective ERMFrameworks
Supported by key building blocks
11
ERM Frameworks comprehensively apply risk management across all risks consistently and with the fundamental objectives of the organization
Goldman Sachs does not provide accounting, tax, or legal advice. Notwithstanding anything in this document to the contrary, and except as required to enable compliance with applicable securities law, you may disclose to any person the US federal and state income tax treatment and tax structure of the transaction and all materials of any kind (including tax opinions and other tax analyses) that are provided to you relating to such tax treatment and tax structure, without Goldman Sachs imposing any limitation of any kind. Investors should be aware that a determination of the tax consequences to them should take into account their specific circumstances and that the tax law is subject to change in the future or retroactively and investors are strongly urged to consult with their own tax advisor regarding any potential strategy, investment or transaction.
Enterprise Risk Identification
Investment & Counterparty Risk
MarketRisk
OperationalRisk
UnderwritingRisk
Fixed income
Equity
Alternative Investment
Counterparty
Currency
Interest Rate
Business
Legal / Compliance
Fraud
Systems
Tax
Underwriting
Catastrophe
Claims
Property
Reinsurance
Sample Attribution by Risk Type
Understanding concentration and how risks diversify one another is critical
For illustrative purposes only
12
ERM can be applied in the investment management context with a three step process
Insurance Portfolio Managers
Duration
Country
Currency
Cross-Sector
Government/Agency
Mortgages/Asset-Backed
Investment Grade Corporate
High Yield
Emerging Market Debt
Municipal
Strategy/Alpha Teams
STEP 1: STEP 2: STEP 3:
Insurance Portfolio Managers and
Risk Team
Risk BudgetingPortfolio Construction &
Risk ManagementReturn Attribution
Routinely updated for changing objectives, rating agency concerns, tax situation and market conditions, etc.
13
1 Targets are subject to change and are current as of the date of this presentation. Targets are objectives and do not provide any assurance as to future results. Please see additional disclosures. For Illustrative purposes only.
Step 1 – Risk budgeting Client risk tolerance and return objectives are used to create a detailed investment roadmap (the risk budget) to guide trading activities
Targeted Excess Returns by Source (Typical)
Sector allocation
Corporate
MBS/ABS
Govt / Agency
Duration / Yield Curve
Return Objective
Typical “moderate to high risk” intermediate duration mandate
Target risk-adjusted excess return
Strategies with high historical risk-adjusted returns are allocated higher risk budgets
This example has an active duration strategy. Strict ALM requirements would result in a much lower tracking error target.
141 Targets are subject to change and are current as of the date of this presentation. Targets are objectives and do not provide any assurance as to future results. Please see additional disclosures. For Illustrative purposes only.
Step 2 – Portfolio ConstructionOpportunities in dislocated market sectors
Sector Sub-sector Weight UpsideBase
StressHigh
StressBurn
Dow n
MBS SS Option ARMs 26 43 36 29 20
SS Alt-A Hybrid ARMs 26 24 20 16 11
Senior Prime ARMs 8 10 10 9 8
ABX 15 9 3 -3
FNMA 5.5's 4 4 4 4
SS CMBS 3 12 13 13 10
ABS Consumer ABS 3 6 6 7 2
Corporate IG non-f inancials 5 6 6 6 6
HY_B 4 9 7 6 3
HY_C 2 15 9 6 -3
HY EUR 10 7 5 1
Bank Loans 3 11 9 6 1
Basis 7 6 6 6 6
CLO AAA CLO 10 12 12 12 8
AA CLO 27 28 27 -8
A CLO 49 48 34 -100
EMD Sovereign Ext Debt (HQ) 8 8 8 8
Sovereign Ext Debt (LQ) 9 8 7 5
Local Mkt Debt (HQ) 4 2 -1 -5
Local Mkt Debt (LQ) 1 2 -2 -5 -11
EM Corps (HQ) 2 11 8 4 0
EM Corps (LQ) 18 7 0 -12
Totals 100 15 13 11 8
Loss-Adjusted YTM
The data shown is of a hypothetical model portfolio, is for informational purposes only and is not indicative of future portfolio characteristics/returns. Actual results may vary for each client due to specific client guidelines and other factors. Expectations are set under 4 different scenarios: “Optimistic”, “Base”, “High Stress”, and “Pessimistic”. The scenarios are intended to encompass a broad range of potential outcomes in an effort to bracket the uncertainty about the future. Please note that strategic long-term assumptions are subject to high levels of uncertainty regarding future economic and market factors that may affect future performance. They are hypothetical indications of a broad range of possible returns. Please refer to the appendix for a more expanded description of the various scenarios. The above data represents a good faith estimate of fair market value as of the date herein. Simulated performance results do not reflect actual trading and have inherent limitations. Please see additional disclosures.
Considerations
Non-agency RMBS: likely ratings downgrades to below investment grade, very high yield, possibility of additional mark-to-market losses. RBC charges may make RMBS inefficient for insurers.
Super-Senior CMBS: may retain AAA, more ratings stability than RMBS, however negative technicals due to increasing delinquencies
Corporates: less volatile than CMBS or RMBS, spread high enough to compensate for significant defaults, but exposed to continued “jump-to-default’ risk due to deteriorating credit markets
AAA CLOs expected to be fairly ratings stable, structural protections are good. AA and lower CLOs have more binary payouts, possibility of high losses
Emerging market debt not favored for insurance due to both ratings and limit on “basket clause” investments for calculating admitted assets
15
Step 3 – AttributionAccountability for Risk Adjusted Returns
Integrated risk systems deliver detailed performance attribution
As of April 30, 2008. Past performance is not representative of future results, which will vary. The returns presented herein are gross and do not reflect the deduction of investment advisory fees, which will reduce returns. The data shown is of a representative account, is for informational purposes only and is not indicative of future portfolio characteristics/returns. Actual results may vary for each client due to specific client guidelines and other factors. For illustrative purposes only to show our risk reporting capabilities. Targets are subject to change and are current as of the date of this presentation. Targets are objectives and do not provide any assurance as to future results. Please see additional disclosures.
Portfolio Manager Responsibility
Sector Team Responsibility
16
Questions?
17
General disclosures
Definition of Scenarios in the context of HPA and GDP
For RMBS
Our “Optimistic”, “Base”, “High Stress”, and “Pessimistic” scenarios are intended to encompass a broad range of potential outcomes in an effort to bracket the uncertainty about the future.
Our scenarios are driven by projections for Home Price Appreciation (HPA). In the current environment our projections are for regional and national price declines over the next two years, followed by a gradual recovery in home prices. In each scenario, our home price projections differ by metropolitan area1. Because of the geographical dispersion in our projections, no single number for home price declines adequately summarizes any scenario.
Dispersion in home prices by metropolitan area allows the scenario analyzer to produce mortgage default and prepayment projections that vary based on the geographical concentration for a security. Each mortgage in the security is mapped to a geographical area. The historical home price path since loan origination is combined with the HPA projection to compute an HPA adjusted LTV for each loan in each time period. This HPA adjusted LTV is one of the main determinants of prepayment, default, and loss severity. Because HPA projections are applied by metropolitan area, mortgage pools with identical state-level concentrations will have different default projections if the concentrations by city within each state differ across the mortgage pools.
Please note that the scenario analyzer does not consider the impact of any of the widely publicized loan modification programs that were recently introduced by several large mortgage servicers. These modification programs, when implemented, could result in meaningful changes in security valuations. As a final note, scenarios are only produced on securities for which LoanPerformance provides updated loan level information.
FHFA Peak to Trough Changes
Optimistic Base High Stress Pessimistic
USA -9% -20% -30% -39%
US GDP Vectors YOY Change (%)
12/31/08 0.32 0.32 0.32 0.32
12/31/09 0.75 -1.00 -2.75 -4.25
12/31/10 0.75 -1.00 -2.75 -4.25
Forward projections for FHFA indices & GDP under each scenario:
1Home price projections are based on Federal Housing Finance Agency (FHFA) Metropolitan Statistical Area price indices.
18
General disclosures
This material is provided for educational purposes only and should not be construed as investment advice or an offer or solicitation to buy or sell securities.
Simulated Performance
Simulated performance is hypothetical and may not take into account material economic and market factors that would impact the adviser’s decision-making. Simulated results are achieved by retroactively applying a model with the benefit of hindsight. The results reflect the reinvestment of dividends and other earnings, but do not reflect fees, transaction costs, and other expenses, which would reduce returns. Actual results will vary.
References to indices, benchmarks or other measures of relative market performance over a specified period of time are provided for your information only and do not imply that the portfolio will achieve similar results. The index composition may not reflect the manner in which a portfolio is constructed. While an adviser seeks to design a portfolio which reflects appropriate risk and return features, portfolio characteristics may deviate from those of the benchmark.
Indices are unmanaged. The figures for the index reflect the reinvestment of dividends but do not reflect the deduction of any fees or expenses which would reduce returns. Investors cannot invest directly in indices.
The strategy may include the use of derivatives. Derivatives often involve a high degree of financial risk because a relatively small movement in the price of the underlying security or benchmark may result in a disproportionately large movement in the price of the derivative and are not suitable for all investors. No representation regarding the suitability of these instruments and strategies for a particular investor is made.
Views and opinions expressed are for informational purposes only and do not constitute a recommendation by GSAM to buy, sell, or hold any security. Views and opinions are current as of the date of this presentation and may be subject to change, they should not be construed as investment advice.
Opinions expressed are current opinions as of the date appearing in this material only. No part of this material may, without GSAM’s prior written consent, be (i) copied, photocopied or duplicated in any form, by any means, or (ii) distributed to any person that is not an employee, officer, director, or authorized agent of the recipient.
Although certain information has been obtained from sources believed to be reliable, we do not guarantee its accuracy, completeness or fairness. We have relied upon and assumed without independent verification, the accuracy and completeness of all information available from public sources.
These examples are for illustrative purposes only and are not actual results. If any assumptions used do not prove to be true, results may vary substantially.
Tracking Error (TE) is one possible measurement of the dispersion of a portfolio’s returns from its stated benchmark. More specifically, it is the standard deviation of such excess returns. TE figures are representations of statistical expectations falling within “normal” distributions of return patterns. Normal statistical distributions of returns suggests that approximately two thirds of the time the annual gross returns of the accounts will lie in a range equal to the benchmark return plus or minus the TE if the market behaves in a manner suggested by historical returns. Targeted TE therefore applies statistical probabilities (and the language of uncertainty) and so cannot be predictive of actual results. In addition, past tracking error is not indicative of future TE and there can be no assurance that the TE actually reflected in your accounts will be at levels either specified in the investment objectives or suggested by our forecasts.
The portfolio risk management process includes an effort to monitor and manage risk, but does not imply low risk.
No part of this material may, without GSAM’s prior written consent, be (i) copied, photocopied or duplicated in any form, by any means, or (ii) distributed to any person that is not an employee, officer, director, or authorized agent of the recipient.
This material has been prepared by GSAM and is not a product of the Goldman Sachs Global Investment Research (GIR) Department. The views and opinions expressed may differ from those of the GIR Department or other departments or divisions of Goldman Sachs and its affiliates. Investors are urged to consult with their financial advisors before buying or selling any securities. This information may not be current and GSAM has no obligation to provide any updates or changes.
Copyright © 2009, Goldman, Sachs & Co. All rights reserved. Compliance Review #: 20529.SA.OTU