Presentation by: Bryan Durand Josh Amoss Suri Thummala Steve Beuchaw Matthew Malouin

1. Global Asset Allocation Presentation by: Bryan Durand Josh Amoss Suri Thummala Steve Beuchaw Matthew Malouin February 28, 2005

2. Agenda Agenda • Introduction • Methodology • Factors Analyzed • Summary • Scoring Model • Selected Factors 1

3. Introduction Establishing Long-Short Trading Strategy • Objective • Limit universe of stocks to firms with middle capitalization ($500M to $2B) market values • We feel this is a less efficient universe • We feel these stocks will be liquid enough (low market impact due to trading) • Establish long / short portfolios based on quantitative stock screens • Rebalance portfolios monthly • Quantitative stock screen • Eleven factors • Find predictive powers on positive and negative returns • Select factors with strong predictive powers • Go long stocks in top quintile • Go short stocks in bottom quintile 2

4. Methodology Stock Selection Process • Screen Parameters • US equities listed on both NYSE and NASDAQ • Market capitalization above $500 million to $2,000 million • Monthly data • In-sample time frame: 1989 – 2001 • Out-of-sample time frame: 2001 – 2004 • Selected eleven fundamental, expectational, and momentum factors to predict future stock returns 3

5. Factors Analyzed Description of Factors Fundamental • Book to Price: book value per share / price per share • Dividend Yield: dividends per share / price per share • FCF Yield: (cash flow from operations – capex) / price per share • Return on Assets: annual net earnings / total assets • Return on Equity: annual net earnings / total shareholder equity Expectational • Percent Change in FY1 Estimates over 3 Months: percent of analysts changing their FY1 estimates over the last three months • Estimate FY1 EPS Yield: consensus estimate of FY1 EPS / price per share • SUE Score: standard unexpected earnings Momentum • Momentum 3 Months: one month – one year 3 month price return • 1-Year EPS Growth: historical one year earnings per share growth rate • 3-Year EPS Growth: historical three year earnings per share growth rate 4

6. Factors Analyzed Two Factors had rock-hard performance 5

7. Scored Strategy Returns: Subjective Estimates Our Scoring System Factor 1: FCF Yield • Portfolio does well in both up and down markets • Catastrophic loss in 1999 (-46%) • High turnover in portfolio – high cost to implement • We scored the long portfolio a 3 and the short portfolio -3 Factor 2: Percent Change in FY1 Estimates over 3 Months • Historical returns and consistency are good • Recent (in sample) returns not as strong • Factor works well especially during market anomalies such as 1999 • We scored the long portfolio a 2 and the short portfolio -2 Overall System • (Factor 1)*(3/5) + (Factor 2)*(2/5) 6

8. Scored Strategy Returns: Subjective Scoring Value Weighted Portfolio shows intriguing results • Scoring Strategy has good performance both In Sample and Out of Sample • There is a step down in returns between Quintiles 1 and 5 • Only 1 year with negative return (1999) • Moderate turnover compared to FCF Yield only – lower cost to implement 7

9. Scored Strategy Returns: Subjective Scoring Heat map demonstrates strong consistency -19% Return 8

10. Scored Strategy Returns: Subjective Scoring Distribution of returns for the scoring model are positively skewed 9

11. Scored Strategy Returns: Subjective Scoring Value Weighted Portfolio shows intriguing results • Quintile 1 and Quintile 2 have a solid Alphas spread over Quintile 4 and Quintile 5 10

12. Summary Performance Details & Conclusions • We have found two factors that give us very attractive returns both in sample and out of sample • Value Weighted Portfolio, Long Portfolio 1, Short Portfolio 5 • Average Return for our portfolio is 18.7% with 10.9% standard deviation, S&P 500 average return 16.6% with 13.7% standard deviation • The value weighted portfolio Sharpe ratio is 1.71 versus an S&P 500 sharp ratio of 1.21 • The average market caps are stable at approximately $1B across all portfolios (Portfolios 1 to 5) • Portfolio 1 beat the benchmark 65.5% of the time while portfolio 5 beat the benchmark 43.4% of the time (similar performance in up and down markets) • Potfolio 1 Outperform Benchmark: 67.4% in up markets, 62% in down • Portfolio 5 Underperforms Benchmark: 46.3% in up markets, 38% in down • Portfolio 1 has a Beta of 0.949 while Portfolio 5 has a Beta of 0.977 • The Alpha of Portfolio 1 is 13.421 versus Portfolio 5 being -7.671 • The T-stats are over 2 This appears to be a very attractive screening method by any measure 11

13. Selected Factor: FCF Yield FCF Yield is a suitable factor for a long-short strategy • FCF Yield has good performance both In Sample and Out of Sample • There is a step down in returns between Quintiles 1 and 5 • Quintile 5 does better than Quintile 4 • Quintile 5 has an average FCF yield of -9% and contains several growth companies • Further research might consider limiting to positive FCF yield companies (a possible knock out screen for growth companies) 12

14. Selected Factor: FCF Yield FCF Yield’s heat map demonstrates strong consistency -46% Return 13

15. Selected Factor: FCF Yield FCF Yield provides attractive Alphas • Quintile 1 and Quintile 2 have positive Alphas while Quintile 4 and Quintile 5 have negative Alphas for a good Alpha spread 14

16. Selected Factor: % Change in FY1 Estimates over 3 Months % Change in FY1 EPS Estimates was selected for its hedging ability • We have chosen to sacrifice some return in order to attempt to prevent catastrophic (and career ending) portfolio losses 15

17. Selected Factor: % Change in FY1 Estimates over 3 Months Heat map demonstrates some consistency and is able to limit catastrophic losses (example: positive 1999 return) 3% Return 16

18. Selected Factor: % Change in FY1 Estimates over 3 Months The in sample Alphas are suitable and we are willing to accept marginal Alphas out of sample due to the factor’s hedging ability 17

19. Back-up 18

20. Scored Strategy Returns: Subjective Scoring 19