1. 0 Presentation by: Austin Applegate Michael Cormier Paul Hodulik Carl Nordberg Nikki Zadikoff Global Asset Allocation February, 26 2004 Granite Investments

2. 1 Agenda Introduction Methodology Factors –1-Year EPS Growth –3-Year EPS Growth –Dividend Yield –% Change in FY1 Estimates over 3 Months –Up vs. Down EPS Est. Revisions –LTM EPS Yield –Estimated FY1 EPS Yield Scored Strategy Returns –Subjective Estimates –Optimized Estimates Summary Agenda

3. 2 Establishing Long-Short Trading Strategy Introduction Objective –Generate positive returns –Limit risk through hedging Quantitative stock screen –Seven 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

4. 3 Description of parameters used for screening process Methodology Sample –US equities listed on both NYSE and NASDAQ –Market capitalization above $100 million –Monthly data –In-sample time frame: 1988 – 1998 –Out-of-sample time frame:1999 – 2003 Selected variables believed to best predict future stock returns Allocated factors into quintiles based on selected criteria Resampled factors each month Analyzed output and performance over time

5. 4 Description of Factors Factors 1-Year EPS Growth: expected growth in EPS over 1 year 3-Year EPS Growth: expected average yearly growth in EPS over 3 years Dividend Yield: indicated dividends / current price % Change in FY1 Est. over 3 Months: % change in earnings estimates over a 3 month period (momentum play) Up vs. Down EPS Est. Revisions: [(# of Up - # of Down revisions)/Total Estimates] (momentum play) LTM EPS Yield: yield on EPS over the last twelve months (EPS yield is inverted P/E ratio) Estimated FY1 EPS Yield: FY1 EPS estimate / current price

6. 5 1-Year EPS Growth not a suitable factor for a long-short strategy Difference between quintile 1 and quintile 5 not large enough Quintile 1 not consistently enough best performing portfolio, and quintile 5 not consistently enough worst performing portfolio Factor: 1-Year EPS Growth

7. 6 3-Year EPS Growth not a suitable factor for a long-short strategy Magnitude of returns too small and difference between quintile 1 and quintile 5 not large enough Quintile 1 not consistently enough best performing portfolio, and quintile 5 not consistently enough worst performing portfolio Factor: 3-Year EPS Growth

8. 7 Dividend Yield displays some positive predictive ability Quintile 5 outperforms quintiles 3 and 4 on average, mitigating the short portion of the strategy Quintile 1 does outperform all other quintiles on a reasonably consistent basis, pointing to some predictive power This factor could be used in a multivariate scored long-short strategy Factor: Dividend Yield

9. 8 % Change in FY1 Est. over 3 Months has the potential to make a contribution in multivariate model, but not on its own Turnover rate is rather high which would lead to high transaction costs Quintile 1 is fairly consistent yielding the highest return, and quintile 5 is also fairly consistent in yielding the lowest return Factor: % Change in FY1 Est. over 3 Months

10. 9 Up vs. Down EPS Est. Revisions would not guarantee returns high enough on its own, but could be used in a multivariate model Difference in returns between quintile 1 and quintile 5 not high enough to make this strategy attractive for a long-short strategy Factor performs very well in three turbulent years, 2000 – 2002, suggesting that it could play a valuable role in a multivariate model Factor: Up vs. Down EPS Est. Revisions

11. 10 LTM EPS Yield does a remarkable job in adequately repeating the highest return yielding portfolio Wide spread between quintile 1 and quintile 5 which would make this strategy attractive from a return perspective Quintiles 1 and 5 perform as expected over time, except for 1999, which would have been disastrous and led to a return of (68)% Factor: LTM EPS Yield

12. 11 LTM EPS Yield does a fairly consistent job of outperforming the market On most observations, the factor outperforms the market, especially during years where the market went down However, in 1999, following a trading strategy based on this factor would have been disastrous Factor: LTM EPS Yield

13. 12 Estimated FY1 EPS Yield is most promising factor, with consistently high and low returns for quintiles 1 and 5 respectively Long-short strategy generates significant positive return in all years except 1999 with a loss of (54.71%) Including this loss, this strategy would still generate a 728% cumulative gain over the past 5 years Consider utilizing other variables in a scored strategy to mitigate 1999 returns Factor: Estimated FY1 EPS Yield

14. 13 Estimated FY1 EPS Yield shows significant upside In most years, a long-short strategy based on this factor would outperform the S&P 500 Index, with returns exaggerated in down markets As discussed before, 1999 would have produced catastrophic negative returns Factor: Estimated FY1 EPS Yield

15. 14 Considerations Scored Strategy Returns Rationale –Some factors were useful predictors of either upside or downside returns –Scoring system utilizes predictive power of numerous factors 2 Methodologies –Subjective Scoring Looking at historical results, determine most useful factors Assign weights using intuition and group discussion –“Optimized” Scoring Construct correlation matrix of several factors Conduct mean-variance analysis, using data derived from one-factor models Apply “optimal” weights to several factors

16. 15 Determining scored factors and weights Scored Strategy Returns: Subjective Estimates Subjective Estimates –Evaluated 7 factors, but selected only 3 factors FY1 EPS Yield –High correlation with LTM EPS Yield but better results –(+5 if 1, +1 if 2, -3 if 5) Dividend Yield –Positive Performance Predictive Ability –(+2 if 1) Up vs. Down EPS Est. Revisions –High correlation with % Change in FY1 Est. over 3 Months but lower turnover –(+3 if 1)

17. 16 Very powerful predictive ability of high and low returns Continues to generate positive returns in each year except 1999, but losses are reduced to (25.23%) Including this loss, this strategy would generate a 437% cumulative gain over the past 5 years Standard deviations and betas of quintiles 1 and 5 are almost identical Scored Strategy Returns: Subjective Estimates

18. 17 Subjective Scored Estimates display similar trend as previous best model (FY1 Yield), but less volatility Graph below depicts equal weighted annual returns of long-short strategy of Subjectively Scored Strategy and FY1 Yield Strategy While Subjective Scored Strategy sacrifices some upside, it performs much better during market anomaly of 1999 Scored Strategy Returns: Subjective Estimates

19. 18 Determining scored factors and weights Scored Strategy Returns: Optimized Scoring Optimized Estimates –Utilized a mean-variance optimizer Each selected quintile is essentially a portfolio with a mean and variance –Evaluated all 7 factors in optimization model, and selected 4 factors (6 total quintiles) Estimated FY1 EPS Yield –(+3.42 if 1, +0.64 if 2, -1.20 if 5) FY1 Revision Ratio –(0.04 if 1) Dividend Yield –(0.92 if 1) LTM EPS Yield –(-2.83 if 1)

20. 19 Value Weighted Portfolio shows intriguing results The equal weighted portfolio using optimized scoring produces very noisy results However, the value weighted portfolio possesses the favorable step distribution Over the past 5 years, a long-short strategy with the value weighted portfolio would have garnered a cumulative 174% gain. Scored Strategy Returns: Optimized Scoring

21. 20 Value weighted optimization appears to perform slightly worst than equal weighted subjective portfolio The value weighted optimized portfolio produces a negative return twice and performs worst than the subjective portfolio in 1999 The significant turnover of quintile 5 (37%) could also pose a problem with respect to trading costs Scored Strategy Returns: Optimized Scoring

22. 21 Initial findings have 5 MBA students pondering quitting school, rejecting their job offers, and starting a hedge fund… Summary Estimated FY1 EPS Yield –Empirically and logically a very strong factor In most markets and at most times, earnings continue to drive stock prices However, market anomalies such as 1999 make this strategy vulnerable –Combining this factor with others should reduce volatility Subjective Scoring –Adding reasonably uncorrelated factors drives down standard deviation –Utilizing intuitive weights for variables proves to be a valuable exercise –Best results of tested strategies We realize this is not an exhaustive list of long-short strategies, but are confident this model can produce significant returns A small (or large) hedge fund cannot incur losses of 50% or more in 1 year, so we are pleased with reduced volatility at expense of some upside that the scoring system brings