1

Presentation by:Austin Applegate

Michael Cormier

Paul Hodulik

Carl Nordberg

Nikki Zadikoff

Global Asset Allocation

February, 26 2004

Granite Investments

2

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

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

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

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

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

Equal Weighted

0

5

10

15

20

25

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

Factor: 1-Year EPS Growth

Value Weighted

0

5

10

15

20

25

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

7

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

Equal Weighted

0

5

10

15

20

25

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

Factor: 3-Year EPS Growth

Value Weighted

0

5

10

15

20

25

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

8

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

Equal Weighted

0

5

10

15

20

25

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

Value Weighted

0

5

10

15

20

25

30

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

9

% 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

Equal Weight

0

5

10

15

20

25

30

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

Factor: % Change in FY1 Est. over 3 Months

Value Weight

0

5

10

15

20

25

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

10

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

Equal Weight

0

5

10

15

20

25

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

Factor: Up vs. Down EPS Est. Revisions

Value Weight

0

5

10

15

20

25

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

11

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)%

Equal Weighted

0

5

10

15

20

25

30

35

40

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

Factor: LTM EPS Yield

Value Weighted

0

5

10

15

20

25

30

35

40

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

12

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

Long/Short vs. Market

-80

-60

-40

-20

0

20

40

60

80

100

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

An

nu

al R

etu

rn %

EW_Long/Short VW_Long/Short Market

13

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

Equal Weighted

0

5

10

15

20

25

30

35

40

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

Value Weighted

0

5

10

15

20

25

30

35

40

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

14

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

Long/Short vs. Market

-80

-60

-40

-20

0

20

40

60

80

100

120

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

An

nu

al R

etu

rn %

EW_Long/Short VW_Long/Short Market

15

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

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

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

Equal Weight

0

5

10

15

20

25

30

35

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

Value Weight

0

5

10

15

20

25

30

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

18

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

Long/Short vs. Market

-80

-60

-40

-20

0

20

40

60

80

100

120

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

An

nu

al R

etu

rn %

EW L/S Subj Scrd EW L/S FY1 EPS Yld Market

19

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

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

Equal Weight

0

5

10

15

20

25

30

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

Value Weight

0

5

10

15

20

25

30

1 2 3 4 5

Quintile

An

nu

aliz

ed

Av

g. R

etu

rn %

21

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

Long/Short vs. Market

-60

-40

-20

0

20

40

60

80

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

An

nu

al R

etu

rn %

EW Subjectve VW Optimized Market

22

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