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

1 Agenda Introduction Methodology Factors Analyzed Summary –Scoring Model –Selected Factors Agenda

2 Establishing Long-Short Trading Strategy Introduction 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

3 Stock Selection Process Methodology 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

4 Description of Factors Factors Analyzed Fundamental 1.Book to Price: book value per share / price per share 2.Dividend Yield: dividends per share / price per share 3.FCF Yield: (cash flow from operations – capex) / price per share 4.Return on Assets: annual net earnings / total assets 5.Return on Equity: annual net earnings / total shareholder equityExpectational 6.Percent Change in FY1 Estimates over 3 Months: percent of analysts changing their FY1 estimates over the last three months 7.Estimate FY1 EPS Yield: consensus estimate of FY1 EPS / price per share 8.SUE Score: standard unexpected earningsMomentum 9.Momentum 3 Months: one month – one year 3 month price return 10.1-Year EPS Growth: historical one year earnings per share growth rate 11.3-Year EPS Growth: historical three year earnings per share growth rate

5 Two Factors had rock-hard performance Factors Analyzed FactorAnalysis FCF YieldLong portfolio does well in both up and down markets Percent Change in FY1 Estimates over 3 Months Factor works well especially during market anomalies such as 1999 Return on Equity Does well for long and short out of sample, factor may be increasing in importance going forward Book to PricePoor predictive power Dividend YieldSome predictive ability Return on AssetsPoor predictive power Estimate FY1 EPS Yield Does well for long and short out of sample, but not in sample SUE Score Poor predictive power Momentum 3 MonthsPoor predictive power 1-Year EPS GrowthPoor predictive power 3-Year EPS GrowthPoor predictive power

6 Our Scoring System Scored Strategy Returns: Subjective Estimates 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)

7 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 Scored Strategy Returns: Subjective Scoring

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

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

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

11 Performance Details & Conclusions Summary 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 while Portfolio 5 has a Beta of –The Alpha of Portfolio 1 is versus Portfolio 5 being The T-stats are over 2 This appears to be a very attractive screening method by any measure

12 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) Selected Factor: FCF Yield

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

14 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 Selected Factor: FCF Yield

15 % 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 Selected Factor: % Change in FY1 Estimates over 3 Months

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

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

18 Back-up

19 Scored Strategy Returns: Subjective Scoring