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The Allocators

Presented By:Ainsley FuhrMike GabrielNate RozofGraig SaloomGreg Williamson

February 27, 2006

Investigating “Innovation Factors” for Growth

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Agenda

• Introduction

– Objective

– Methodology

• Key Factors

• Screening/Alpha-tests

• Results

– Quintiles

– Heat Maps

– Scoring Strategy

• Closing Thoughts

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Introduction

Objective:

• Investigate recent claims of a shift to “New Economy” drivers of growth:

– The Innovation Boom, John Mouldin’s E-Letter, 2/20/06

– Why The Economy is Stronger than You Think, Businessweek, 2/13/06

• Determine whether “innovation” factors can identify excess returns

– R&D Expenditures

– Intangible Assets

– Investments in Human Capital

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Introduction

“Today, less capital is being invested in the expansion of physical capacity and more capital is being invested in the

expansion of intellectual capacity.”

“Today, less capital is being invested in the expansion of physical capacity and more capital is being invested in the

expansion of intellectual capacity.”

Source: “The Innovation Boom, John Mouldin’s E-Letter, 2/20/06

Trends in R&D expenses relative to capital expenditures:• They have grown much faster • They were unaffected by recessions, mid-cycle slowdown or financial

crises • The rate of increase, in some cases, is accelerating • The trends really diverged in the early 1990s (the beginning of the

explosion in the trade deficit) • They have led to strong productivity gains.

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Introduction

“Globalization, outsourcing, and the emphasis on innovation and creativity are forcing businesses to shift at a dramatic

rate from tangible to intangible investments.”

“Globalization, outsourcing, and the emphasis on innovation and creativity are forcing businesses to shift at a dramatic

rate from tangible to intangible investments.”

Source: “Why The Economy is Stronger than You Think”, Businessweek, 2/13/2006

Traditional Drivers:

• Focus: Capital Spending

• Metrics:

– ROA

– Capital Expenditures

– Property, Plant and Equipment

New Drivers:

• Focus: “Knowledge Spending”

• Metrics:

– ROIA (return on intangible assets)

– R&D expenditures

– Investments in Human Capital

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Introduction

According to BusinessWeek, investment in intangibles such as product development and training is critical for long-term profitability, but is not counted in GDP.

Unmeasured intangibles

$977*

Physical capital and software

$1,139

*Billions of dollars; Average for 2000-2003Data: Corado, Hulten, Siche

Our objective is to determine whether these factors have actually been driving significant asset returns

Investment by Asset Type (Billions of US Dollars)

46%54%

Unmeasured intangibles

Physical capital and software

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Introduction

Methodology

1. Identify “Innovation” Factors

2. Generate Stock Screens

3. Alpha-test Screens

4. Develop Scoring System

5. Apply Scoring System In Sample

6. Apply Scoring System Out of Sample

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Identified “Innovation” Factors

We identified metrics to measure innovation factors highlighted in both reports

Innovation Factor Metric AnalyzedInvestment in Information Assets R&D / (R&D + CapEx)

Return on Investment in Information Assets

Return on Intangible Assets (ROIA)

Productivity 5 Year Sales Growth / # of Employees

Effectiveness of Investment in Information Assets

Sales / Advertising Expense

Investments in Human Capital Metric Unidentifiable

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Screening/Alpha-tests

Screen Parameters

• Limit universe to S&P 500 securities

• Rebalance portfolios monthly

• In-sample period: 1996 – 2002

• Out-of-sample period: 2003 – 2005

Alpha-testing

• Quintile analysis for 25 factors (traditional + “innovative”)

• Monthly returns vs. Benchmark (S&P500)

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Results: Quintiles

Factor: ROIA (Innovation Factor)

Inconsistent linear relationship – Factor Rejected

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Results: Quintiles

Factor: Sales/Advertising (Innovation Factor)

Poor linear relationship – Factor Rejected

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Results: Quintiles

Factor: Sales Growth 5YR per Employee (Innovation Factor)

Promising linear relationship, significant spread – Factor Accepted

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Results: Quintiles

Factor: R&D to Capex Lag 1YR (Innovation Factor)

Mostly linear relationship, significant spread – Factor Accepted

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Results: Quintiles

Factor: ROA (Traditional Factor)

Promising linear relationship, significant spread – Factor Accepted

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Results: Heat Maps

Factor: ROA

Solid indicators in 4 out of 7 years for quintiles 1 and 5.

Annual Returns 1 2 3 4 5 Market1996 51.24% 29.15% 23.70% 32.31% 17.48% 26.27%1997 41.74% 30.47% 32.63% 40.00% 27.19% 26.90%1998 55.39% 22.78% 24.41% 18.55% 19.57% 32.49%1999 59.98% 8.27% 3.29% 6.76% 9.61% 10.35%2000 29.08% 30.97% 34.94% 40.43% 30.10% -0.90%2001 -0.30% 8.04% 3.02% 4.37% -2.82% -16.14%2002 -11.99% -6.91% -12.90% -13.15% -30.47% -23.01%

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Results: Heat Maps

Factor: Sales Growth 5YR per Employee

Solid indicators in 5 out of 7 years for quintile 1, moderate indicator for quintile 5.

Annual Returns 1 2 3 4 5 Market1996 43.56% 29.20% 22.00% 22.30% 22.47% 26.27%1997 40.26% 31.50% 28.69% 33.57% 27.32% 26.90%1998 33.14% 30.16% 17.38% 12.98% 18.02% 32.49%1999 50.89% 16.48% -0.36% 3.23% 1.01% 10.35%2000 58.47% 39.28% 31.05% 22.88% 15.66% -0.90%2001 -1.78% 2.17% 4.24% 3.33% 5.64% -16.14%2002 -16.48% -16.19% -12.55% -14.30% -18.27% -23.01%

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Results: Heat Maps

Factor: R&D to CapEx

Inconsistent indicator – Factor Rejected.

Annual Returns 1 2 3 4 5 Market1996 27.80% 24.97% 27.66% 31.93% 26.26% 26.27%1997 55.18% 30.09% 25.57% 34.56% 45.30% 26.90%1998 92.54% 34.32% 22.29% 13.55% 31.23% 32.49%1999 92.23% 60.58% 44.43% 18.82% 4.40% 10.35%2000 -2.08% 25.45% -4.07% 11.15% 19.18% -0.90%2001 4.45% -3.07% 7.76% 3.87% 20.36% -16.14%2002 -29.69% -21.90% -12.37% -8.85% -7.14% -23.01%

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Results: Scoring Strategy

Scoring System

• Factor 1: ROA(1) = +5

• Factor 2: ROA(5) = -4

• Factor 3: SalesGrwth/Emp(1) = +4

• Factor 4: SalesGrwth/Emp(5) = -2

Alpha-testing

• Quintile analysis for “Total Score”

• Monthly returns vs. Benchmark (S&P500)

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Results: Scoring Strategy

In-Sample Total Return: 1996-2002

Solid linear relationship, significant spread – Model Accepted

Significant quintile 1 alpha for moderate additional beta risk.

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Results: Scoring Strategy

Out-of-Sample Total Return: 2003-2005

Poor linear relationship indicates the model is not useful for long-short strategy.

Alpha/beta relationship appears less attractive.

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Results: Scoring Strategy

Out-of-Sample Total Return: 2003-2005

Quintile 1 outperforms market in each year, but fails to outperform all other quintiles.

Annual Returns 1 2 3 4 5 Market2003 49.60% 55.35% 41.47% 51.29% 71.41% 34.55%2004 13.71% 17.00% 12.80% 17.30% 7.98% 6.22%2005 22.90% 30.60% 13.06% 17.53% 12.19% 10.38%

All 5 quintiles beat market return each year. Therefore equal weight strategy likely skewing results.

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Closing Thoughts

• Equal weighted sorting strategy compared to value weighted benchmark (S&P 500) produces skewed results

• Additional analysis by sector was more promising and deserves further investigation

– Model more likely to explain information-based industries

– Inclusion of traditional, capital intensive industries and financials clouding results

• Long-only strategy in quintile 1 more promising than long-short strategy

• Additional data sources of innovation factors, especially in areas of human capital necessary

• We believe that new economic indicators such as “innovation” factors likely impact macro economic growth, but have less predictive power on an individual asset level

“Innovation” factors are intriguing, but don’t seem to be a compelling driver of above-average returns