December 4, 2008
Asset Liability Management
performance metrics and risk attribution
Asset Liability Management
Review of traditional approach Developments in the risk management landscape
Integrating ALM with Enterprise Risk Management
Performance metrics and risk attribution
Leveraged liability cash flow profile
2008 2013 2018 2023 2028 2033 2038 2043 2048 2053 2058
Liability Cash Flow Profile
Traditional risk metrics
Probability weighted measures
Static exposure at risk measure provide limited information
> Duration/convexity are based on simple premises and may give false sense of comfort
> Partial duration need to be supplement with covariance structure
Probability weighted measures prone to RAROC calculations
> Allows quantification of yield curve “bets” within a principled risk framework
> Multi factor interest rate model or Principal Component Analysis (PCA)
Objectives of PCA
> Reduce the number of explanatory variables
> Find hidden patterns in data and simplify interpretation
Traditional approach still prevalent
Asset management executed separately
Focus of asset management is on assets
> maximize total return > maximize book yield > simple ALM risk metrics
Investment (i.e. asset-only) objectives specified by insurance company / client
Assets managed and performance measured against benchmark
> asset-only benchmark > liability-driven benchmark
Attribution performed against benchmark
Traditional performance metrics
No risk attribution corresponding to performance ALM risk metrics focus on interest rate risk
> Level of mismatch
• Duration mismatch: DA – DL
– Partial Duration, Effective Duration, Dollar Duration
• Convexity exposure: CA – CL
> CALM prescribed interest rate risk provision > Deterministic Scenario Testing
> Regulatory Capital C3
> Stochastic Modeling / Risk Profile > Economic Capital
No mention of financial objectives or performance
Shortcomings undermine performance
Financial objectives are not being achieved
Fundamental flaw:
Beating benchmark and/or achieving investment objectives does not necessarily mean financial objectives will be met
No separation of sources of value-added from ALM and active asset management decisions
Capital and risk-adjusted performance cannot be properly factored in
Performance measures lack transparency
Not clear where value-added comes from
Active asset management bets not explicitly disclosed ex ante nor measured ex post
Unintended, implicit bets not recognized
Result – may reward a poorly matched position
Conflicts between ALM and Asset Management
Resistance to moving away from traditional approach
Benchmark may be inappropriate
> benchmark and or targets frequently oversimplified for benefit of asset manager
Entire process may cater more to needs of asset manager, not client
> asset manager requires specification of investment objectives, not financial objectives
> asset manager requires benchmark and targets that may bear little resemblance to actual liabilities
> value-added ALM strategies may disrupt performance measurement of asset manager
Traditional asset management divorces assets from liabilities for benefit of asset manager
Developments in risk management
Companies starting to execute ALM at strategic level
Rating Agencies and Regulators evaluating quality of risk management
Recent losses and failures drawing greater attention to effectiveness of risk management
Greater recognition of value of executing ERM as a strategic decision-making framework
Most companies run ALM at a tactical level
Integrating ALM with ERM
ALM conceptual framework consistent with ERM
Replace traditional benchmarks with actual liabilities Replace focus on narrow investment objectives with
focus on overall financial objectives
Change process so that ALM drives investment decisions
ALM Conceptual Framework
ERM defines how performance measured
Performance metrics based on financial objectives
Performance metrics based on financial objectives
> maximize accounting earnings (CGAAP, future earnings) > maximize embedded value (EEV, MCEV)
> maximize economic surplus
> maximize investment income / total return > minimize economic capital
> minimize required regulatory capital
ALM attribution analysis focuses on change in performance metric over the period
> quantifies impact on performance metric for each source of risk > most companies focus on change in interest rates for ALM
ALM attribution analysis
Creates awareness of impact of financial variables
US Treasury Yield Curve
Economic Surplus BOP 111,673
Change due to Yield Curve 2,292 Change due to Liabilities (19,982) Change due to Assets 26,718
Total Change 9,028
Economic Surplus EOP 120,701
Change due to Assets 26,718
New Business 14,399
Asset trades 2,244
Change due to aging of cash flows 10,075 Change due to assumptions changes
-Change due to Liabilities (19,982)
New Business (12,413)
Change due to aging of cash flows (7,569) Change due to assumptions changes
-ALM attribution analysis
Recognizes sources of value added
Identify value from both ALM and active management
> ALM strategies (excluding tactical credit views, security selection, rate anticipation, etc)
Active asset management can adds value on top of ALM optimized portfolio
> Any bets (i.e., active positions) are recorded ex ante and measured ex post – thus fully transparent
> Measure actual value added from active management, not just value against a benchmark
Attribution not restricted to a particular measurement basis
> could be change in ES, accounting results or other financial objective(s)
Quantifying sources of value added
ALM attribution analysis is a valuable tool to separate the value added from ALM and asset management
ALM strategies are on a default-free basis
Active asset management can add further value by taking bets within risk limits
Incremental value added from active asset management
Impact of ALM Strategies
Change in ES Before Rebalance (5,045) Change in ES After Rebalance 9,028
Total 14,073
Impact of Active Asset Management
Change in ES due to rate anticipation 1,213 Change in ES due to credit selection 750
How well do risk metrics predict impact?
Change due to Yield Curve 2,292
Change predicted by Duration (190) Contribution predicted by Convexity (205) Change predicted by -D(∆i)+.5C (∆i)2 (395)
Change predicted by Partial Duration 2,606 Change predicted by Effective Duration (1,700) Change predicted by Effective Convexity (1,026) Change predicted by -D(∆i)+.5C (∆i)2 (2,726)
Simplifying assumptions wrt interest rate risk can be way off
US Treasury Yield Curve
Limitations of simple risk metrics
> can be poor predictors of actual risk
> if limitations not understood or naively applied can lead to unexpected results
Attribution gives greater insight
Impact on financial objectives broken down by source Bets are made explicit
> duration or rate anticipation > credit selection
> backing fixed income liabilities with non-fixed income assets
Value added by asset manager is transparent
Performance measurement is more meaningful but difficult to implement in practice
Some companies feel that performance measurement of asset management is less important than successful execution of ALM
Thank You!
Contact info:
Charles L. Gilbert, FSA, FCIA, CFA, CERA Nexus Risk Management
+ 1 416 593 9645
