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Quantitative Core Equity Quantitative Management Associates November 2004.

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Presentation on theme: "Quantitative Core Equity Quantitative Management Associates November 2004."— Presentation transcript:

1 Quantitative Core Equity Quantitative Management Associates November 2004

2 2 SP\QC 9-04 Table of Contents I.Organization & People II.Quantitative Core Equity Overview III.Underlying Research IV.Investment Process V.Trading VI.Results Appendix F Technical Information F Biographies F Fee Schedule F Composite Performance Returns

3 I. Organization & People

4 4 SP\QC 9-04 Quantitative Management Associates Investment Manager Firmly Grounded in Academic Theory F Highly experienced, stable team of investment professionals F Time-tested investment principles F psychology of investor behavior F financial valuation theory F Proprietary quantitative research recognized by industry publications F Insights and empirical research incorporated in quantitative processes Assets Under Management $47 Billion* * Quantitative Management Associates LLC (QMA) directly manages more than $36 billion and allocates approximately $10 billion (assets as of 9/30/04) to other Prudential Investment Management, Inc. units. QMA operated for many years as a unit within Prudential Financials asset management business, known today as Prudential Investment Management. On July 1, 2004, QMA became an SEC-registered investment adviser. No changes in investment professionals and processes occurred as a result of this change in legal structure. ** Includes approximately $10 billion in assets for which equity and balanced management services are provided

5 5 SP\QC 9-04 F Stable, dedicated team of experienced investors F Research driven investment culture F Theoretical underpinning F Rigorous testing F $47 billion under management* F Quantitative Core Equity ($11.8 billion) F Value Equity ($2.0 billion) F Balanced Management ($19.9 billion)** F Equity Index Management ($22.6 billion) F Other ($0.1 billion) Quantitative Management Associates Senior Team Focused on Research and Implementation As of 9/30/04 * Quantitative Management Associates (QMA) directly manages more than $36 billion and allocates approximately $10 billion (assets as of 9/30/04) to other Prudential Investment Management, Inc. units. ** Includes approximately $10 billion in assets for which equity and balanced management services are provided. James Scott, PhD President Portfolio Manager 17 Margaret Stumpp, PhD Chief Investment Officer Portfolio Manager17 Ted Lockwood Managing Director Portfolio Manager16 John Van Belle, PhD Managing Director Portfolio Manager21 Mitch Stern, PhD Vice President Portfolio Manager7 Peter Xu, PhD Principal Portfolio Manager 7 Max Smith, PhD Senior Associate Research Analyst15 Dan Carlucci, CFA Senior Associate Research Analyst20 Betty Tong Associate Research Analyst23 Rich Crist Vice President Trader21 QuantitativeYears Core Equityat ProfessionalsRoleFirm

6 II. Quantitative Core Equity Overview

7 7 SP\QC 9-04 * There can be no guarantee that this objective will be achieved. Quantitative Core Equity Objective* Achieve total return of 1.0 –1.5% over the benchmark with about 2% tracking error Philosophy F Investors make systematic, exploitable mistakes F They fall too easily for stock stories F They fail to react sufficiently to material news F The most effective way to exploit these mistakes is with a diversified, objective process F Different selection criteria are effective for different types of stocks F Risk should be focused on areas of greatest confidence

8 8 SP\QC 9-04 Results Consistently Achieved Objective Over Time Quantitative Core Equity Annualized Performance as of 9/30/04 Quantitative Core Equity (Gross)S&P 500 IndexDifference Tracking Error Information Ratio 1 Year16.03%13.87%+216 bps–– 3 Years % Years Since Inception (1/1/97) Please see Composite Performance Returns section of the Appendix for full disclosures. Source of all data: QMA, Standard & Poors

9 III. Underlying Research

10 10 SP\QC 9-04 F Overconfidence Bias in International Stock Prices, The Journal of Portfolio Management, (Winter 2003) Compelling Research Recognized by Industry Publications F Behavioral Bias, Valuation and Active Management, Financial Analysts Journal, Vol 55 (July/August 1999) F News, Not Trading Volume, Builds Momentum, Financial Analysts Journal, (March/April 2003) F Enhanced Equity Indexers: Common Traits and Surprising Differences, Journal of Investment Management, (September 2003)

11 11 SP\QC 9-04 Conceptual Framework F Value of companies with no growth opportunities depends on normalized earnings. P =E/k F Value of rapidly growing companies depends primarily on expectations of future growth. P =E/k + profitable growth Valuation Theory Shows Where to Find Opportunities P = Stock Price E = Normalized Earnings Per Share k = Equity Discount Rate

12 12 SP\QC 9-04 Slow Growth Stocks Valuation Works Best for Slowly Growing Companies … Quarterly Excess Returns* Fast Growth Stocks P/E Quarterly payoff to stocks grouped by P/E and Long-Term EPS Growth P/E * Based on the difference between each group of stocks returns and the average of all stocks returns. Source: Quantitative Management Associates, based on the largest 3000 US stocks (based on market cap valuation) in each quarter from 3/ /2003. Past performance is not a guarantee of future results. Returns are gross of management fees and are only provided to illustrate the information implicit in our stock selection methodology.

13 13 SP\QC 9-04 Slow Growth Stocks … While News Is More Important for Rapidly Growing Companies Fast Growth Stocks Quarterly payoff to stocks grouped by Estimate Revisions and Long-Term EPS Growth Negative Revisions Positive Revisions Neutral Revisions Negative Revisions Positive Revisions Neutral Revisions Quarterly Excess Returns* * Based on the difference between each group of stocks returns and the average of all stocks returns. Source: Quantitative Management Associates, based on the largest 3000 US stocks (based on market cap valuation) in each quarter from 3/ /2003. Past performance is not a guarantee of future results. Returns are gross of management fees and are only provided to illustrate the information implicit in our stock selection methodology.

14 14 SP\QC 9-04 Valuation Framework Also Works Internationally Source: Scott, J., Stumpp, M., and Xu,P. Overconfidence Bias in International Stock Prices Journal of Portfolio Management, 29(2), Winter Past performance is not a guarantee of future results. This is shown for illustrative purposes only. Valuation Is More Important For Slow Growth High E/P - Low E/P (% excess Total Return) Strong News minus Weak News (% excess Total Return) Good News Is More Important For High Growth SlowAverage Fast

15 IV. Investment Process

16 16 SP\QC 9-04 Three-Step Process Adds Value Classify Stocks Calculate Expected Return Construct Portfolio STEPInputsOutputs Nightly download of data for approximately 3,000 US stocks Internally built optimizer F Overweight high expected return stocks F Limits exposure to other risks Stocks classified by growth rate into categories Expected return for each stock and portfolio, calculated daily Periodically rebalance each portfolio to reflect risk/reward objectives Models for each category F Slow growth: emphasize valuation F Fast growth: emphasize news

17 17 SP\QC 9-04 Steps 1 and 2: Classify Stocks and Calculate Expected Returns Classify Stocks Calculate Expected Return Construct Portfolio Emphasize valuation F Forward Price/Earnings F Change in Price/Earnings F Adjusted Price/Book Equal emphasis on both valuation and news Slow GrowthFast GrowthAverage Growth Emphasize news F EPS Estimate Revisions F Price-Volume Behavior F Insider Trading F New Issues/Buybacks F Earnings Quality 3000 Stock Universe

18 18 SP\QC 9-04 Higher Expected Return Stocks Have Outperformed Average quarterly equal-weighted sector-adjusted gross returns for all stocks in universe, 1998-Q1 through 2004-Q2. Source: Quantitative Management Associates, using data provided by Factset Data Systems. Past performance is not a guarantee of future results. Returns are gross of management fees and are only provided to illustrate the information implicit in our stock selection methodology. Classify Stocks Calculate Expected Return Construct Portfolio

19 19 SP\QC 9-04 Our Process Adapts to Changes in a Firms Business Source: Quantitative Management Associates using data provided by Factset. Shown to illustrate the stock selection methodology and not intended to be a recommendation. Not all stocks held in the portfolio perform similarly. Past performance is not a guarantee of future results. Slow Growth but Cheap (Buy) – Negative EPS revisions; – Low P/E, P/B; – EPS Quality OK. Fast Growth but bad news (avoid) – Negative EPS revisions; – Insider Selling; – Weak EPS Quality.

20 20 SP\QC 9-04 Step 3: Construct Portfolios Mindful of Risk Classify Stocks Calculate Expected Return Construct Portfolio Data integrity review Select portfolio with appropriate risk/return profile Review transactions before trading Expected Returns F Calculated Daily Expected Returns F Calculated Daily Estimated Trading Costs Estimated Trading Costs Risk Constraints F Market capitalization F Industry F Sector F Active stock position F Liquidity F Style Risk Constraints F Market capitalization F Industry F Sector F Active stock position F Liquidity F Style Proprietary Optimizer Proprietary Optimizer Portfolio 1 Portfolio 10 This is shown for illustrative purposes only.

21 21 SP\QC 9-04 Factor Restrictions Representative Optimization Parameters Liquidity F Industry ± 0.75% F Sector ± 0.75% F Growth/Value (by growth bucket) ± 3.0% F Size (by cap bucket) ± 3.0% F No more than 20% of average daily trading volume F No more than 10% in an individual trade F More liquid stocks favored Stock Restrictions F No more than 0.75% underweight F No more than 0.75% overweight Levels vary under normal market conditions. Precise bounds may vary without notice. Classify Stocks Calculate Expected Return Construct Portfolio

22 22 SP\QC 9-04 Key Attributes of Portfolio In Line With Market Classify Stocks Calculate Expected Return Construct Portfolio Quantitative Core Equity Representative Portfolio Characteristics As of 9/30/04 Large Cap Quantitative Core Equity S&P 500 Index Size ($ bil) $ Weighted Average $ Weighted Median Median Valuation Price/Earnings (excluding neg)17.6x18.5x Price/Earnings (I/B/E/S 1 yr Forecast 1 )14.8x15.9x Price/Book 2.7x 2.9x Yield 1.7% 1.8% Growth and Profitability Long-Term Forecast %12.0% Return On Equity19.9%20.6% Earnings Per Share Growth-5 Yrs. 10.7% 9.6% Beta 2 Versus S&P Turnover typically % As of 9/30/04 1 There is no guarantee that forecasts will be met. This is shown for illustrative purposes only. 2 Historical Beta calculated in Zephyr Style Advisor using monthly returns since inception (1/97 – 3/04). Sources of data: QMA, Frank Russell Company, Standard & Poors.

23 V. Trading

24 24 SP\QC 9-04 Optimizer Timely Data Market Access Ongoing Research Carefully Manage Trading Costs Trading (Agency, Principal, Electronic Crossing Network) Post trade analysis Evaluation of broker performance Evaluation of our trading techniques Estimation of trading costs Expected returns/ Risks characteristics Estimated trading costs

25 25 SP\QC 9-04 Ongoing Research Has Reduced Transaction Costs Incorporated real- time bid-ask spreads Enhanced transaction- cost modeling Intra-day principal trading Average Transactions Costs for All Quantitative Core Equity Trades, May 2001 – December 2003 Quarterly average of total transaction costs including commission, spread, impact and delay. Results include both agency and principal trades. Data begins 5/15/01 Past trends are not a guarantee of future results. Source: QMA

26 26 SP\QC 9-04 Ongoing Research Leads to Periodic Model Enhancements F Replaced earning surprises with analyst estimate revision as measure of news F Product Inception F Changed optimizer from BARRA to CPLEX F Incorporated real-time bid-ask spread and transaction costs in optimization to evaluate brokers and trading strategies F Added insider trading, share repurchase/issues and earnings quality F Additional data integrity screens F Introduced international models F Refined market capitalization risk control F Introduced Long-Short Market Neutral model

27 VI. Results

28 28 SP\QC 9-04 Quantitative Core Equity Composite Investment Performance Quantitative Core Equity Annualized Gross Returns As of 9/30/04 (1/1/97 – 9/30/04) Past performance is not a guarantee of future results. Please see Composite Performance Returns section of the Appendix for full disclosures. Source of Benchmark: Standard & Poor's Source of all other data: Quantitative Management Associates % Quantitative Core Equity Composite S&P 500 Year(Gross) Index Difference 2004 (1/1-9/30) 3.22%1.51%+171 bps Annual Returns

29 29 SP\QC 9-04 Performance in One-Year Rolling Periods # of Rolling One-Year Periods Times that Quantitative Core Underperformed S&P 500 Times that Quantitative Core Outperformed S&P to -6% -4 to -5% -3 to -4% -2 to -3% -1 to -2% 0 to -1% S&P 0 to 1%1 to 2%2 to 3%3 to 4%4 to 5%5 to 6% 500 Relative Performance of Quantitative Core vs. S&P 500 Relative Gross Performance of Quantitative Core vs. S&P 500 (Account Performance Minus S&P 500) (79 Month-end Observations From 12/31/97 – 6/30/04). Past performance is not a guarantee of future results. Source: Quantitative Management Associates and Standard & Poors.

30 30 SP\QC 9-04 Outperformance in Up Markets and Down Markets % of times Quantitative Core (Gross) Outperforms S&P 500 Return-10% or Less-10 to +10%+10% or More Average Added Value 1.0% 2.0%1.4% # of Observations Percent of the Time Quantitative Core Outperforms S&P 500 in Up and Down Markets (Rolling One-Year Periods; 79 Month-end Observations from 12/31/97- 6/30/04) Past performance is not a guarantee of future results. Source: Quantitative Management Associates and Standard & Poors.

31 31 SP\QC 9-04 Outperformance in Growth, Value and Neutral Markets -10% or Less-10 to +10%+10% or More Average Added Value (Quantitative Core minus S&P 500) 1.8%1.1%1.2% # of Observations Growth FavoredNeutralValue Favored (Defined as Russell 1000 Value minus Russell 1000 Growth) Percent of the Time Quantitative Core Outperforms S&P 500 in Growth and Value Markets (Rolling One-Year Periods; 79 Month-end Observations from 12/31/97- 6/30/04) % of times Quantitative Core (Gross) Outperforms Past performance is not a guarantee future results. Sources: Quantitative Management Associates, Standard &Poors and Frank Russell

32 32 SP\QC 9-04 Value Added Primarily Through Security Selection Attribution Analysis 6/30/1999 – 6/30/2004 Source: Factset. 5-Year consensus forecasted EPS growth rates from IBES. P/E calculated using latest 12 month trailing EPS. Annualized Value Added (%) --Attribution Factor --

33 33 SP\QC 9-04 Strategy Adds Value Across Capitalization Range and Internationally Annualized Value Added (Gross) Inception through 9/30/04 Past performance is not a guarantee of future results. An investment cannot be made directly in an index. Source of data: QMA, Standard & Poors, Frank Russell and Morgan Stanley. (1/1/1997) S&P 500 (1/1/2000) Russell 3000 (7/1/1996) S&P 400 (6/1/2000) S&P 600 (1/1/2002) MSCI EAFE Inception Date Benchmark (%) (4/1/2002) MSCI World (Free)

34 34 SP\QC 9-04 Why Quantitative Core? F Experienced, stable, dedicated team F Captures major insights of growth and value management into one portfolio F Adds value in different market environments F Quantitative approach ensures discipline and objectivity F Continuing research keeps process fresh

35 Appendix F Technical Information F Biographies F Fee Schedule F Composite Performance Returns

36 36 SP\QC 9-04 No Black Box: Review Transactions Before Trading Recommended Trades – Client X TickerName Trade SharesTrade $Dir BOP Weight EOP Weight Market Weight BOP Active EOP Active Last Price $ Size, Growth News, d(E/P), E/P, B/P Insiders, Buyback, Quality Expected AlphaExchange% ADVFlag ADVPAdvancepcs Com16,200428,328B0.17%0.22%0.00%0.17%0.22%26.44(3/3)(1/0/0/0)(1/0.4/0.6)3.0NASDAQ1.2%0 AHCAmerada Hess Corp Com1,40062,020B0.24%0.25%0.05%0.19%0.20%44.30(3/1)(0.9/0/1/1)(0/0/0.6)2.1NYSE0.2%0 AINAlbany Intl Corp Cl A60013,482B0.00% 22.47(4/1)(1/0.3/1/0.8)(0/0/0.5)2.1NYSE0.5%0 AMGNAmgen Inc Com20,4001,196,052B0.59%0.73%0.93%-0.34%-0.21%58.63(2/3)(1/-0.7/0/0)(-0.5/0/1)1.3NASDAQ0.2%0 AMHAmerus Group Co Com2,50062,725B0.04%0.05%0.00%0.04%0.05%25.09(4/0)(0/1/1/1)(0.5/0/0)2.3NYSE1.3%0 APAApache Corp Com21,8001,283,802B0.05%0.19%0.12%-0.07%0.08%58.89(3/1)(1/1/0.8/0.1)(0/0/0.2)1.9NYSE1.5%0 ATHAnthem Inc Com1,900125,248B0.07%0.08%0.12%-0.05%-0.03%65.92(3/2)(1/-1/0/-1)(1/0.8/0.3)2.1NYSE0.2%0 BBBYBed Bath & Beyond Inc Com90032,904B0.00% 0.13%-0.13% 36.56(2/3)(1/0.8/-1/-1)(-0.5/0/0.1)1.3NASDAQ0.0%0 BBTBb&t Corp Com7,000227,360B0.07%0.10%0.19%-0.12%-0.09%32.48(2/0)(-1/1/0.8/0.6)(0/0.4/0)1.5NYSE0.6%0_B BBYBest Buy Inc Com67,7002,002,566B0.00%0.22%0.12%-0.12%0.10%29.58(3/2)(1/1/-0.1/0)(-0.1/0/0.8)2.2NYSE1.5%0 BMYBristol Myers Squibb Co Com34,200770,526B0.61%0.70%0.54%0.07%0.16%22.53(2/0)(-0.8/1/1/1)(0/0/0.5)2.0NYSE0.5%0 REEverest Re Group Ltd Com3,200186,432S0.26%0.24%0.00%0.26%0.24%58.26(3/2)(1/-1/1/0)(0/0/0)0.5NYSE0.7%0 RHIRobert Half Intl Inc Com6,90094,323S0.01%0.00%0.03%-0.02%-0.03%13.67(3/3)(-1/-0.6/-1/-1)(0/0/0.4)-1.2NYSE1.0%0*** RKYCoors Adolph Co Cl B40019,684S0.02% 0.00%-0.01%49.21(3/1)(-1/0/1/1)(0/0/-0.2)0.3NYSE0.1%0 RSGRepublic Svcs Inc Com2,00040,220S0.13%0.12%0.00%0.13%0.12%20.11(3/1)(-1/0/0.3/0)(0/0/0.5)0.2NYSE0.4%0 SSears Roebuck & Co Com23,400587,340S0.19%0.13%0.10%0.09%0.03%25.10(3/1)(-1/-1/1/1)(0/0/-0.2)-0.4NYSE0.5%0 SHWSherwin Williams Co Com90024,192S0.02% 0.05%-0.03% 26.88(3/1)(-0.3/0/0/0)(0/0.2/0.2)0.2NYSE0.2%0 SPCSt Paul Cos Inc Com8,600290,336S0.07%0.04%0.09%-0.02%-0.05%33.76(3/1)(-1/-1/0.4/0)(1/0/0)0.0NYSE0.9%0 STESteris Corp Com1,50036,645S0.13%0.12%0.00%0.13%0.12%24.43(3/3)(-1/1/0/0)(0.5/0/1.4)1.3NYSE0.4%0 Understand what drives transactions Ranges Size (1-5): 5 = Small Growth (0-3): 3 = Fast Contribution to from news, (E/P), E/P and B/P Contribution to from insider trading, buybacks and earnings quality Classify Stocks Calculate Expected Return Construct Portfolio Stocks shown to illustrate the investment process. They are not intended as recommendations or as a complete listing. Source: QMA Anticipate trading costs Monitor data integrity

37 37 SP\QC 9-04 Industry Portfolio Before Benchmark Portfolio AfterDifference Multiline Retail3.51%4.23%3.48%-0.75% Chemicals0.82%1.53%0.78%-0.75% Electric Utilities1.51%2.20%1.47%-0.74% Energy Equipment & Services0.08%0.79%0.08%-0.71% Diversified Financials7.01%7.90%7.24%-0.65% Machinery0.56%1.19%0.60%-0.59% Biotechnology0.59%1.29%0.73%-0.56% Real Estate0.00%0.40%0.00%-0.40% IT Consulting & Services0.00%0.29%0.00%-0.29% Hotels Restaurants & Leisure1.01%1.08%0.79%-0.29% Electronic Equipment & Instruments 0.10%0.37%0.09%-0.28% Multi-Utilities & Unregulated Power 0.03%0.30%0.05%-0.26% Automobiles0.31%0.57%0.31%-0.25% Personal Products0.26%0.60%0.36%-0.24% Road & Rail0.24%0.47%0.24%-0.23% Food & Drug Retailing 0.90%1.11%0.90%-0.21% Evaluate Impact of Each Recommended Trade on Alpha and Risk Characteristic Portfolio Before Benchmark Portfolio AfterDifference Expected Alpha Tracking Error Number of Stocks P/E P/B IBES EPS %Growth Size Bucket 120.9%22.2%20.4%-1.8% Size Bucket 216.9%17.7%17.0%-0.8% Size Bucket 320.8%20.7%21.4%0.6% Size Bucket 420.3%19.7%20.2%0.4% Size Bucket 521.1%19.6%21.1%1.5% IBES EPS Growth Bucket 023.1%24.1%23.0%-1.1% IBES EPS Growth Bucket 138.0%37.3%38.6%1.3% IBES EPS Growth Bucket 223.4%25.9%22.9%-3.0% IBES EPS Growth Bucket 315.5%12.8%15.5%2.7% Non-Benchmark Positions 6.0%0.0%6.0% Sector Portfolio Before Benchmark Weight Portfolio After Difference Materials2.02%2.69%1.94%-0.75% Utilities2.07%2.80%2.05%-0.75% Industrials10.75%11.44%10.74%-0.70% Energy5.33%5.95%5.56%-0.40% Financials19.92%20.30%20.01%-0.29% Consumer Discretionary14.41%14.00%14.18%0.18% Consumer Staples9.46%9.03%9.47%0.44% Information Technology15.49%14.78%15.53%0.75% Health Care16.22%15.39%16.14%0.75% Telecommunication Services 4.33%3.62%4.37%0.75% Classify Stocks Calculate Expected Return Construct Portfolio Shown for illustrative purposes, and not intended to be a recommendation or as a complete listing. Source of Data: QMA

38 38 SP\QC 9-04 Analyze Every Broker Broker Name Total Cost (%) Excess Cost Spread (%) Commission (%) Impact (%) Daily Volume # of Stocks # of Programs $ Value TradedShares Mean Price $ Broker #10.07%-0.17%0.04%0.07%-0.04%1.48% ,559,8477,882, Broker #20.09%-0.07%0.05%0.06%-0.02%0.60%283325,933,500826, Broker #30.14%-0.04%0.04%0.07%0.02%0.57% ,796,0732,390, Broker #40.20%-0.04%0.04%0.07%0.09%1.26% ,112,3616,654, Broker #50.16%-0.04%0.05%0.06% 1.00%1, ,647,6147,987, Broker #60.14%-0.03%0.04%0.06%0.04%0.74%1, ,285,0353,764, Broker #70.17%-0.03%0.05%0.06% 0.95%1, ,820,4627,814, Broker #80.23%-0.03%0.04%0.07%0.12%1.46% ,584,5684,663, Broker #90.13%-0.01%0.04%0.06%0.04%0.37%156214,146,285463, Broker #100.16%-0.01%0.05%0.07%0.03%0.47%137215,467,011613, Broker #110.22%-0.01%0.06%0.05%0.11%1.49%1, ,385,5075,795, Broker #120.26%0.00%0.05%0.07%0.13%1.55% ,519,4931,580, Broker #130.18%0.02%0.05%0.06% 0.51%372541,283,1351,535, Broker #140.21%0.03%0.04%0.08%0.09%0.53% ,089,8871,997, Broker #150.20%0.04%0.07% 0.06%0.51%15129,603,803357, Broker #160.21%0.06% 0.08%0.41%152313,589,094494, Broker #170.21%0.07%0.06%0.07%0.08% 6853,080,906125, Broker #180.32%0.11%0.06%0.07%0.19%1.02% ,750,7801,856, TOTAL0.17%-0.04%0.04%0.07%0.06%1.10%12, ,531,655,36156,804, Top performing agency broker, last 120 days Average agency trade cost = 0.17% Total costs 0.04% below expectations Shown for illustrative purposes, and not intended to be a recommendation or as a complete listing. Source of Data: QMA

39 39 SP\QC 9-04 Analyze Every Trade F Evaluate broker performance based upon residual cost, given difficulty of trade Agency Trades By Broker Last 90 Days 4/9/03 BrokerDate Total Cost (%) Residual Cost (%) Half - Spread (%) Commissio n (%) Impact & Other (%) % of Avg Daily Volume Number of Trades Value ($) Shares ($) Transaction Price Sells ($) Buys ($) Broker #61/10/030.14%-0.01%0.07%0.08%-0.01%0.15% ,171 28, , ,587 Broker #61/23/030.23%0.03%0.05%0.09% 0.44% ,906 32, , ,919 Broker #61/24/030.13%0.00%0.04%0.06%0.03%0.20% 64 10,092, , ,416 9,886,235 Broker #62/7/030.22%0.04%0.03%0.10%0.09%0.02% ,406 19, ,561 54,845 Broker #62/14/030.18%0.04%0.06%0.07%0.06%0.19% 143 1,831,103 70, , ,574 Broker #62/27/030.16%0.01%0.04%0.07%0.05%0.34% 164 8,215, , ,306,782 3,908,811 Broker #62/28/030.16%-0.04%0.03%0.06%0.07%1.13% ,789,292 1,929, ,528,48929,260,803 Broker #63/3/030.10%-0.02%0.06%0.05%-0.01%0.25% ,634 23, , ,630 Broker #63/4/030.20%0.06%0.04%0.07%0.08%0.01% 5 19, ,613 Broker #63/5/030.09%-0.05%0.04%0.07%-0.02%0.15% 114 1,855,612 68, , ,791 Broker #63/6/030.07%-0.08%0.04%0.06%-0.03%0.40% ,458, , ,061,791 2,396,530 Broker #63/7/030.14%-0.05%0.04%0.10%0.00%0.19% 15 1,121,695 61, ,121,695 Broker #63/14/030.16%0.05%0.03%0.05%0.08% ,274 19, ,349 97,925 Broker #63/17/030.43%0.28%0.04%0.08%0.31%0.09% ,348 41, , ,793 Broker #63/18/030.21%0.08%0.02%0.05%0.14%0.36% ,243 13, , ,571 Broker #63/19/030.13%0.01%0.02%0.06%0.05% ,142 10, , ,015 Broker #63/20/030.05%-0.05%0.03%0.05%-0.03%0.05% 8 158,960 4, ,506 55,454 Broker #63/27/030.12%-0.11%0.08%0.12%-0.08%0.15% ,754 26, ,402 62,352 Broker #63/28/030.12%-0.03%0.03%0.06%0.02%0.36% 64 5,140, , ,227,101 2,913,367 Broker #64/1/030.08%-0.05%0.03%0.04%0.00%0.50% 4 195,002 5, ,974 69,028 Broker #64/3/030.12%-0.04%0.09%0.06%-0.03%0.35% ,847 13, , ,769 Total0.14%-0.03%0.04%0.06%0.04%0.74% 1,220105,285,035 3,764, ,104,72753,180,307 Cost below expectations. Good trade. Large, slightly unbalanced, program Shown for illustrative purposes only. This does not depict actual trades. Source of Data: QMA

40 40 SP\QC 9-04 Biographies James H. Scott, PhD is the President and co-head of Quantitative Management Associates (QMA). Jim is portfolio manager for enhanced equity index portfolios for institutional investors and mutual fund clients. Prior to joining the firm, Jim was a professor and head of the Finance Department at Columbia University Graduate School of Business. His academic career included positions at Stanford University, University of Wisconsin-Milwaukee, and Carnegie Mellon University. During this period, Jim also served as a consultant, corporate director, mutual fund trustee, and research fellow at the Federal Reserve Bank of Cleveland. He has written numerous articles that have appeared in The Journal of Portfolio Management, The Journal of Finance, and The Financial Analysts Journal, among other publications. Jim is a cum laude graduate from Rice University where he holds a BA in Economics. He holds a Masters and PhD in Economics from Carnegie Mellon University. He serves on the Business Board of Advisors for the Graduate School of Industrial Administration at Carnegie Mellon University, and is a Director of the Institute for Quantitative Research in Finance, and Chair of its Research Committee. He is also a member of the Board of Editors of The Financial Analyst Journal and of The Journal of Investment Management. Margaret S. Stumpp, PhD is the Chief Investment Officer and co-head of Quantitative Management Associates (QMA). She is portfolio manager for enhanced equity index portfolios for institutional investors and mutual fund clients. Maggie is extensively involved in quantitative research in asset allocation, security selection and portfolio construction for Quantitative Management Associates. Prior to joining the firm, Maggie was employed by the AT&T Treasury department and by Price Waterhouse as a senior consultant. In both positions, she was responsible for providing expert testimony on economic and financial matters. She has published articles on finance and economics in numerous publications, including, The Financial Analysts Journal, The Journal of Portfolio Management, The Journal of Investment Management and Award Papers in Public Utility Economics. Maggie earned a BA cum laude with distinction in Economics from Boston University, and holds an AM and PhD in Economics from Brown University. Ted Lockwood is Managing Director for Quantitative Management Associates (QMA). Ted oversees the equity area, which includes quantitative equity, derivative, and index funds. He is also responsible for managing portfolios, investment research, and new product development. Previously, Ted was with AT&T and a member of the technical staff at AT&T Bell Laboratories. Ted graduated summa cum laude with a BE in Engineering from the State University of New York at Stony Brook, as well as an MS in Engineering and an MBA in Finance from Columbia University. Peter Xu, PhD is Principal for Quantitative Management Associates (QMA). He conducts equity market research, the results of which are used in the stock selection process for all quantitative core equity portfolios. He has published articles in various journals, including The Financial Analysts Journal, The Journal of Portfolio Management, Review of Quantitative Finance and Accounting, and Review of Pacific Basin Financial Markets and Policies. Previously, Peter taught in the business school at the University of Houston. He earned a BS in Nuclear Physics from Fudan University in Shanghai, an MA in Economics from Rice University, and a PhD in Finance from the University of Houston.

41 41 SP\QC 9-04 John Van Belle, PhD is Managing Director for Quantitative Management Associates (QMA). John manages global balanced portfolios, domestic balanced funds, and equity portfolios for foreign-based full service clients. Previously, John was a vice president in Currency Management Consulting Groups at both Bankers Trust and Citibank. He began his career in the research department at the Federal Reserve Bank of New York. Before that he taught Economics and Finance at the University of Virginia and Rutgers Graduate School of Management. He has published numerous articles in the fields of Economics and Finance. John earned a BS in Economics from St. Joseph's College and holds a PhD from the University of Virginia. Mitchell B. Stern, PhD is Vice President for Quantitative Management Associates (QMA). Mitch is responsible for research, development, and management of structured products. He also is a portfolio manager for the PIIMA (Prudential Investments Individually Managed Accounts) individual tax-managed portfolios and the Long-Short Market Neutral fund. Previously, Mitch was an Assistant Professor of Finance at Fairfield University and the University of Tennessee. He also has twelve years of experience as a consultant to portfolio managers and hedge funds on quantitative investment strategies. Mitch holds a BA cum laude in Economics from Brandeis University, and an MA and PhD in Financial Economics from the University of Virginia. Maxwell Smith, PhD is Senior Associate for Quantitative Management Associates (QMA). He is responsible for optimizing quantitative core equity portfolios and engages in research to improve the quantitative investment process. Previously, he was a municipal bond portfolio manager with Prudential Fixed Income. He joined Prudential Financial in Max earned a BS in Physics from CalTech, an MS in Physics from the University of Illinois, and holds a PhD in Finance from the University of British Columbia. Betty Sit Tong is Investment Associate for Quantitative Management Associates (QMA). She co-manages the global index portfolios benchmarked against MSCI developed index series. She is also responsible for trading foreign and domestic equities, foreign exchange, and derivative instruments. In addition to the developed index series, she has experience with funds benchmarked against the MSCI small cap and emerging market index series. Previously, Betty was employed by Prudential Equity Management Associates. She joined Prudential Financial in Betty earned a BA in Psychology from Princeton University. Daniel Carlucci, CFA, is Senior Associate and Portfolio Advisor for Quantitative Management Associates (QMA). He assists with the management of several quantitative portfolios, specifically the large-cap and and small-cap core portfolios as well as tax-managed portfolios for high net worth investors. Prior to his current assignment, Dan was an Investment Analyst with Quantitative Management Associates Value Equity team, where he assisted with the management of quantitative large-cap institutional portfolios. He joined Prudential Financial in Dan holds a BS in Finance and an MBA in Finance from Rutgers University. Richard L. Crist, ChFC, CLU is Vice President for Quantitative Management Associates (QMA). Rich is responsible for trading US and foreign equities for the group's quantitative core, quantitative value, and global balanced strategies. He manages US equity index funds and also trades inflation indexed government bonds, treasuries, foreign currencies, and futures contracts. Previously, he was an Accounting Supervisor with the Prudential Asset Management Company, which he joined in Rich earned a BS in Accounting from Montclair State College. He holds the Chartered Financial Consultant designation, and is a Certified Life Underwriter from the American College. Biographies

42 42 SP\QC 9-04 Quantitative Core Equity Fee Schedules 35 basis points on first…………………....$25 million 30 basis points on next………………….$75 million 25 basis points ……………………………..Thereafter Minimum account ………………….……..$2 million Commingled Fund (includes custody) 35 basis points on first…………………....$25 million 30 basis points on next………………….…$75 million 25 basis points ……………………………..Thereafter Minimum account ………………….……..$30 million Single Client Separate Account (excludes custody)

43 43 SP\QC 9-04 Quantitative Core Equity Composite

44 44 SP\QC 9-04 Quantitative Core Equity Composite


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