“Active” vs. “Passive” Management Good Governance = Managing Alpha and Beta Dr. Arun Muralidhar

2 OPERS’ Investment Philosophy  Asset allocation is the key determinant of return  Ranges will be maintained through a disciplined rebalancing program  Diversification by and within asset class is the primary risk control element  Passive alternatives to actively managed portfolios are suitable investment strategies, especially in highly efficient markets OPERS Statement of Investment Objectives and Policies, June 2003; pg 5

3 Key Conclusions  Clients are separating “alpha” from “beta” - Too much alpha focus, not enough on the beta  Not enough focus on the impact versus liabilities  All portfolio decisions (including “passive” rebalancing) impact returns and risks; Must make decisions in an informed manner  Evaluate every decision in context of portfolio  The Greater Fool Theory of Asset Management

4 The Pension Fund Balance Sheet Future Contributions Current Assets Future Returns LIABILITIES = Funded ratio = assets/liabilities + + =

5 Key to Success – Effective Decisions  Traditional Approach – Alpha from External Managers  New Approach – Add Alpha from Informed Decisions  Governance/Oversight of Decisions - Transparency Measure Risk Evaluate Performance Outperform Benchmark Determine Benchmark Set Objectives Annual Daily Monthly

6 Portfolio: Many Embedded Decisions Total Portfolio/Liabilities LC SC ACWI EMG SCPassive Active Equity - 64%Cash - 0% Alternatives 13% Fixed Income - 23% Non US - 24%Dom. - 40% CoreHYEmerging PE - 4%RE - 9% Benchmark Misfit Risk Asset Allocation Decision Manager Selection and Allocation Important to manage/monitor each decision and understand individual and aggregate contribution to risk/return

7  Strategic  Passive = Simple calendar or range-based rebalancing  True passive (Dutch model): benchmark includes drift until range is met or calendar period is completed  OPERS Policy Gives Discretion = Tracking Error  +/- 3% range for most assets; 4% for Real Estate  When range hit, go either to range or target or in- between The “Old” Active-Passive Framework

8  Manager Level  Usually restricted to a tracking error budget  Usually with a single asset class focus  Optimize information ratio on active component  Developed a performance measure (M 3 ) to show why this is incorrect (for single and multi-manager portfolios)  Could hire a negative IR manager!! Modigliani insight  Will not focus on today (See Appendix, pgs 24-27) The “Old” Active-Passive Framework

9 Passive Rebalancing: Can Be “Risky”*  OPERS Buy and Hold: 0.16% ann. Return; 1.09% tracking error; Worst drawdown = -2.15% over a multi-year period  +/-3% range for most assets; 4% for RE** –Impact: 0.01% annualized for 0.21% risk –Worst drawdown: much lower at –0.43% (multi-year period) –No transactions cost: 0.02% ann. (1% turnover) –On $ 60 bn = $90 mn/year impact, but lower risk! –Does not capture Asset-Liability risk or impact *Rebalancing was evaluated from 01/99 – 04/05. Only tested at the highest portfolio benchmark level. Proxied Lehman Universal with Lehman Composite and Custom Real Estate Index with NAREIT – data not provided by OPERS and hence can differ from true results. Transactions costs (one way) = 15 bps for equity; 10 bps for fixed income; 0.5% for alternatives **Range-based rebalancing = if any asset drifts to the range limit, all assets are rebalanced to benchmark

10 “Passive” Rebalancing: Not Cost/RiskNeutral Buy and Hold Rebalancing

11 Informed Decisions within Ranges  Portfolio rebalancing is an “active” decision  Pension funds experience cash flows – use them to structure fund appropriately  Asset class structuring also creates opportunity  Large cap vs. Small cap (+/-2%)  Core vs. HY vs. EMG (+/-2%)  EAFE vs. EMG vs. Small (+/-2%) Can OPERS staff use discretion to create value? Key is to have a robust, transparent, consistent process

12 Improving the Quality of Decisions  Institute consistent evaluation and performance metrics  Test variety of rules to use for specific decisions  Many resources can be tapped  Internal staff – have ideas that are unused  Research – lots of research on when asset classes do well  Leverage external managers/relationships – Verizon model  Transparency and process are key for good governance “Prudence is Process”

13 Portfolio: Focused on a Few Decisions Total Portfolio/Liabilities LCACWIEMGSC Equity 64% Cash 0% Alternatives 13% Fixed Income 23% Foreign 24% Domestic 40% CoreHY Chose a few decisions to make the point Developed multiple rules to diversify the risk for each strategy Asset Allocation - Equity vs FI Foreign Equity - ACWI vs EMG Domestic Equity - LC vs SC Fixed Income - Core vs HY Asset Allocation - Equity vs Cash

14 Informed Decisions/Managing Beta: Improved Risk/Return *  At highest level of fund, keep return (relative to “Buy and Hold”, lower risk relative to Rebalancing  Every decision is within passive rebalancing guidelines  Intelligent decisions contribute return at every level of fund – alpha can compound… *All Decision regimes were evaluated from 01/99 – 04/05. Transactions costs were higher for sub-asset class level. Decision making frequency was monthly Excess Annualized Return Tracking Error Information Ratio Worst Drawdown Confidence in Skill Success Ratio Asset Allocation level0.16%0.19% %98%57% Domestic Equity Foreign Equity Fixed Income 0.08%0.19% %85%55% 0.04%0.12% %82%53% 0.04%0.07% %92%56%

15 Comparing Impact on Entire Fund Excess Annualized Return Tracking Error Information Ratio Worst Drawdown Confidence in Skill Success Ratio Buy and Hold 0.16%1.09% %69%51% Strict +/-3% Rebalancing 0.01%0.21% %53%42% Informed Decisions 0.32%0.21% %99%64%  At total fund level, can get better return with lower risk  Drawdown at total fund level is also lower  Translates into meaningful dollars = $180 million/year!

16 Managing Beta = “Alpha” ($) + Risk Management = Good Governance Informed Decisions Rebalancing

17 Informed Decisions can Lower A-L Risk Annualized Growth in Surplus Volatility of Ann. Growth in Surplus Correlation of asset returns with Liabilities Probability that Funded Ratio < 105% (y/e 2006) Max Drawdown of Surplus Static SAA -0.71%6.7% %-8.6% Annual Rebalancing -0.58%6.85% %-8.59% Informed Decisions 0.27%6.99% %-8.11% Annualized Liability Return (Benchmark) = 8.2% Note: These results are indicative and were obtained from another fund using the “informed decision” approach ( )  Showed another client how informed decisions can lower asset-liability risks beyond standard rebalancing  Similar liability target to OPERS (8% annualized)

18 Summary  Can use current Statement of Objectives to add meaningful value from “managing beta”  Being “active” within “passive” range = good governance  Can also control risk in a meaningful way  Cheaper source of excess return at total fund return (than any other “alpha” option)  Easy to adopt by leveraging external relationships

Appendix

20 Where Should a Fund Take Risk? Tracking error Excess return Tracking error vs. excess returns (net of fees) US Equity Large Cap US Fixed Income High Yield Non-US Equity EAFE - Japan Lite Emg Mkt Equities Non-US Fixed Income US Equity Small Cap US Equity Mid Cap Non-US Fixed Income - Japan Lite Source: Muralidhar (2001), Innovations in Pension Fund Management  Consistent with OPERS philosophy – WHO IS THE MUG? From 12/87 to 12/97

21 The Wilshire U.S. Large Cap Universe: Zero Average Alpha Source: Muralidhar (2001), Innovations in Pension Fund Management  Can OPERS beat the pack with a dynamic manager strategy?

22 Should managers be constrained? The case for conservative management From 12/87 to 12/ Information ratio Tracking error Wilshire U.S. Fixed Income Universe

23 The Greater Fool Theory of Asset Management  If average alpha is zero, must believe that another sponsor is selecting a bad manager….  The average alpha in international came from a bet on Japan – will the future have another?  Does not negate the case for active management – need to be smart about “managing managers”  New performance measures give new insight on optimal portfolio construction (cash vs passive vs active)

24 Riskless asset Return Active portfolio Standard deviation of active portfolio Benchmark Standard deviation Market risk Active portfolio An Evaluation of the M 2 Measure

25 Riskless asset Return Benchmark Standard deviation Market risk An Underperforming Manager Has a Higher Risk-Adjusted Return!!! Information ratio is a bad measure of performance!! M 2 provides allocation information between cash and active manager

26 The M 3 -adjustment – Normalize for Tracking Error FundReturn (%) Standard deviation (%)  r(RAP) (%) TE(basic) (%) TE(RAP) (%) r(CAP) (%) (1)(2)(3)(4)(6)(7)(8)(12) F B Get a totally different ranking of external managers

27 M 3 Gives Information on Allocation to Cash, Passive and Active Managers RankingUnadjusted Skill using raw returns M 2 or Sharpe Skill using M2M2 M3M3 M3M3 Information ratio (1)(2)(3)(4)(5)(6)(7)(8) First Second Third Fourth Fifth Sixth Seventh Eighth Ninth Tenth Have shown that M3 is only measure consistent with skill-based rankings Can use same technique for multi-manager portfolios

28 Caveats and Disclaimers  Data was not provided by OPERS – we used our own and hence actual analysis by OPERS will differ. Data was used to make a hypothetical study of the fund to show the impact of different investment options and was not meant to be an investment recommendation.  We have developed some intelligent allocation rules across various asset classes and sub-asset classes. These are purely research ideas, tapped from publicly available research, and there is no guarantee that they will generate performance in the future for OPERS.  We have attempted to use very onerous transaction costs assumptions to see if these ideas would still be beneficial. Again, OPERS’ own experience will differ because of the size of the fund and other institutional constraints.