The Surprising Alpha from Malkiels Monkey UpsideDown Strategies

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The Surprising “Alpha” from Malkiel’s Monkey & Upside-Down Strategies Jason Hsu, Ph. D. Chief

The Surprising “Alpha” from Malkiel’s Monkey & Upside-Down Strategies Jason Hsu, Ph. D. Chief Investment Officer Research Affiliates, LLC.

Research Affiliates 2

Research Affiliates 2

Research Affiliates, LLC Mission » Concentrate on Research and product development » Partner with

Research Affiliates, LLC Mission » Concentrate on Research and product development » Partner with world-class Affiliates to bring product to market Global leader in » Global tactical asset allocation (GTAA) » Innovative indexation Profile » Approximately $142 billion in assets managed using RA investment strategies as of March 20131 » Founded in 2002 by Rob Arnott » Majority employee-owned 1 As of 3/31/2013 based on estimates. Includes assets managed or sub-advised by Research Affiliates or licensees using RAFI®, Enhanced RAFI®, or GTAA strategies. Note: please refer to the important information slide at the end for all relevant disclaimers, disclosures, and information on our intellectual property. 3

Managed Assets Growth Since Inception *March 2013 data based on estimates. Includes GTAA, RAFI

Managed Assets Growth Since Inception *March 2013 data based on estimates. Includes GTAA, RAFI and Enhanced RAFI assets managed or sub-advised by Research Affiliates and RAFI licensees 4

The Surprising “Alpha” from Malkiel’s Monkey & Upside-Down Strategies 5

The Surprising “Alpha” from Malkiel’s Monkey & Upside-Down Strategies 5

Smart Beta Strategies Fundamental Index® Strategy Equal Weighting Diversity Weighting Minimum Variance Maximum Diversification

Smart Beta Strategies Fundamental Index® Strategy Equal Weighting Diversity Weighting Minimum Variance Maximum Diversification Risk Efficient Index Equal Weighting of Risk Clusters 6

1. High Risk—High Reward Claim » Investors are compensated for taking risk. The higher

1. High Risk—High Reward Claim » Investors are compensated for taking risk. The higher the risk of the strategy, the higher the return Implications 1. Risk-weighted strategies should have higher return. 2. The following strategies should outperform cap-weighted benchmark: » Volatility Weighted » Market Beta Weighted » Downside Semi-Deviation Weighted 7

1. High Risk—High Reward Performance vs. Cap (U. S. 1964– 2012) Strategy Return Standard

1. High Risk—High Reward Performance vs. Cap (U. S. 1964– 2012) Strategy Return Standard Deviation Sharpe Ratio Information Ratio Volatility Wt 1 12. 2% 19. 1% 0. 36 0. 34 Market Beta Wt 2 11. 9% 19. 8% 0. 34 0. 29 Downside Semi-Deviation Wt 3 12. 1% 18. 9% 0. 37 0. 36 9. 7% 15. 3% 0. 29 0. 00 U. S. Cap Wt 4 See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 8

1. High Risk—High Reward What about the inverse strategies? (U. S. 1964– 2012) Standard

1. High Risk—High Reward What about the inverse strategies? (U. S. 1964– 2012) Standard Information Deviation Sharpe Ratio 15. 6% 0. 47 0. 53 Strategy Inverse of Volatility Wt 1 Return 12. 5% Inverse of Market Beta Wt 2 13. 5% 15. 0% 0. 55 0. 53 Inverse of Downside Semi-Deviation Wt 3 12. 4% 15. 6% 0. 46 0. 53 Inverse of U. S. Cap Wt 4 9. 7% 15. 3% 0. 29 0. 00 Volatility Wt 1 12. 2% 19. 1% 0. 36 0. 34 Market Beta Wt 2 11. 9% 19. 8% 0. 34 0. 29 Downside Semi-Deviation Wt 3 12. 1% 18. 9% 0. 37 0. 36 9. 7% 15. 3% 0. 29 0. 00 U. S. Cap Wt 4 Upside-down strategies also outperform … by a bigger margin! See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 9

2. Strong Fundamentals—High Reward Claim » Strong fundamentals deliver high return Implications » Strategies

2. Strong Fundamentals—High Reward Claim » Strong fundamentals deliver high return Implications » Strategies weighted on accounting variables should outperform cap-weighted benchmark: » Strategies weighted on growth of fundamentals should outperform cap-weighted benchmark: 10

2. Strong Fundamentals—High Reward Fundamentals-based strategies outperform the market U. S. 1964– 2012 Strategy

2. Strong Fundamentals—High Reward Fundamentals-based strategies outperform the market U. S. 1964– 2012 Strategy Book Value Wt 5 Return 11. 2% Standard Deviation 15. 7% Sharpe Ratio 0. 38 Information Ratio 0. 35 5 -Yr Avg Earnings Wt 6 11. 2% 15. 1% 0. 40 0. 36 Fundamentals Wt 7 11. 6% 15. 4% 0. 41 0. 42 Earnings Growth Wt 8 12. 4% 19. 0% 0. 38 9. 7% 15. 3% 0. 29 0. 00 U. S. Cap Wt 4 See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 11

2. Strong Fundamentals—High Reward Upside-down strategies also outperform! U. S. 1964– 2012 Standard Sharpe

2. Strong Fundamentals—High Reward Upside-down strategies also outperform! U. S. 1964– 2012 Standard Sharpe Deviation Ratio 18. 5% 0. 47 Strategy Inverse of Book Value Wt 5 Return 13. 9% Inverse of 5 -Yr Avg Earnings Wt 6 14. 4% 18. 3% 0. 50 0. 55 Inverse of Fundamentals Wt 7 14. 1% 18. 8% 0. 47 0. 51 Inverse of Earnings Growth Wt 8 10. 3% 18. 0% 0. 28 0. 10 U. S. Cap Wt 4 9. 7% 15. 3% 0. 29 0. 00 Book Value Wt 5 11. 2% 15. 7% 0. 38 0. 35 5 -Yr Avg Earnings Wt 6 11. 2% 15. 1% 0. 40 0. 36 Fundamentals Wt 7 11. 6% 15. 4% 0. 41 0. 42 Earnings Growth Wt 8 12. 4% 19. 0% 0. 38 9. 7% 15. 3% 0. 29 0. 00 U. S. Cap Wt 4 Information Ratio 0. 51 See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 12

3. Popular Smart Beta Strategies Minimum Variance—low risk generates high return Maximum Diversification—return is

3. Popular Smart Beta Strategies Minimum Variance—low risk generates high return Maximum Diversification—return is proportional to volatility Risk-Efficient (λ=2) —return is proportional to downside semideviation Risk Cluster Equal Weight—equally weight country/industry clusters Diversity Weighting—a blend between cap weighting and equal weighting Fundamentals Weighting—strong fundamentals deliver high return 13

3. Popular Smart Beta Strategies Popular smart beta strategies outperform the market U. S.

3. Popular Smart Beta Strategies Popular smart beta strategies outperform the market U. S. 1964– 2012 Standard Deviation Sharpe Ratio Strategy Return Minimum Variance 9 11. 8% 11. 7% 0. 56 0. 26 Maximum Diversification 10 12. 0% 14. 0% 0. 48 0. 35 Risk-Efficient (λ=2)11 12. 5% 16. 8% 0. 43 0. 53 Risk Cluster Equal Weight 12 11. 2% 14. 6% 0. 41 0. 31 Diversity Weighting 13 10. 5% 15. 5% 0. 34 0. 47 Fundamentals Wt 7 11. 6% 15. 4% 0. 41 0. 42 9. 7% 15. 3% 0. 29 0. 00 U. S. Cap Wt 4 Information Ratio See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 14

3. Popular Smart Beta Strategies Upside-down strategies also outperform! U. S. 1964– 2012 Standard

3. Popular Smart Beta Strategies Upside-down strategies also outperform! U. S. 1964– 2012 Standard Deviation Sharpe Ratio 18. 1% 0. 41 Information Ratio 0. 48 Strategy Inverse of Minimum Variance 9 Return 12. 7% Inverse of Maximum Diversification 10 12. 5% 17. 6% 0. 41 0. 47 Inverse of Risk-Efficient (λ=2)11 12. 3% 17. 3% 0. 41 0. 46 Inverse of Risk Cluster Equal Weight 12 13. 2% 19. 0% 0. 42 0. 40 Inverse of Diversity Weighting 13 13. 4% 18. 3% 0. 45 0. 48 Inverse of Fundamentals Wt 7 14. 1% 18. 8% 0. 47 0. 51 U. S. Cap Wt 4 9. 7% 15. 3% 0. 29 0. 00 Minimum Variance 9 11. 8% 11. 7% 0. 56 0. 26 Maximum Diversification 10 12. 0% 14. 0% 0. 48 0. 35 Risk-Efficient (λ=2)11 12. 5% 16. 8% 0. 43 0. 53 Risk Cluster Equal Weight 12 11. 2% 14. 6% 0. 41 0. 31 Diversity Weighting 13 10. 5% 15. 5% 0. 34 0. 47 Fundamentals Wt 7 11. 6% 15. 4% 0. 41 0. 42 15. 3% 0. 29 0. 00 U. S. Cap Wt 4 9. 7% See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 15

Malkiel’s Monkey Throwing Darts 16

Malkiel’s Monkey Throwing Darts 16

4. Malkiel’s Monkey Throwing Darts In his bestselling book A Random Walk Down Wall

4. Malkiel’s Monkey Throwing Darts In his bestselling book A Random Walk Down Wall Street, Burton Malkiel claimed: “a blindfolded monkey throwing darts at a newspaper's financial pages could select a portfolio that would do just as well as one carefully selected by experts” 17

4. Malkiel’s Monkey Throwing Darts We randomly chose 30 of the 1, 000 largest-cap

4. Malkiel’s Monkey Throwing Darts We randomly chose 30 of the 1, 000 largest-cap stocks every year, from 1964 to 2012, and tracked the results… We repeated the exercise 100 times, replicating 100 monkeys Strategy Return Standard Deviation Sharpe Ratio Information Ratio Average of 100 Malkiel's Monkey Portfolios 14 11. 3% 18. 3% 0. 33 0. 21 9. 7% 15. 3% 0. 29 0. 00 U. S. Cap Wt 4 Only 2 out of 100 portfolios underperformed the cap-weighted benchmark… It takes an unlucky monkey to underperform the cap-weighted index! See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 18

Value and Size Factors 19

Value and Size Factors 19

Value and Size Factors Risk Strategies All non-cap-weighted strategies have value and small size

Value and Size Factors Risk Strategies All non-cap-weighted strategies have value and small size tilt Four-Factor Model Decomposition (U. S. 1964– 2012) Annual FFC Alpha 0. 23% Alpha t-stat 0. 46 Market Exposure 1. 10 Size Exposure 0. 55 Value Exposure 0. 16 Momentum Exposure -0. 04 Market Beta Wt 2 0. 56% 1. 01 1. 13 0. 54 0. 13 -0. 09 Downside Semi-Deviation Wt 3 0. 26% 0. 52 1. 10 0. 52 0. 17 -0. 04 Inverse of Volatility Wt 1 0. 58% 1. 13 0. 97 0. 28 0. 33 -0. 03 Inverse of Market Beta Wt 2 0. 86% 1. 07 0. 91 0. 25 0. 43 0. 03 Inverse of Downside Semi-Deviation Wt 3 0. 48% 0. 95 0. 97 0. 28 0. 33 -0. 02 U. S. Cap Wt 4 0. 00% 0. 00 1. 00 0. 00 Strategy Volatility Wt 1 See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 20

Value and Size Factors Fundamental Strategies All non-cap-weighted strategies have value and small size

Value and Size Factors Fundamental Strategies All non-cap-weighted strategies have value and small size tilt Four-Factor Model Decomposition (U. S. 1964– 2012) Strategy Book Value Wt 5 5 -Yr Avg Earnings Wt 6 Fundamentals Wt 7 Earnings Growth Wt 8 Inverse of Book Value 5 Inverse of 5 -Yr Avg Earnings Wt 6 Inverse of Fundamental Wt 7 Inverse of EPS Growth 8 U. S. Cap Wt 4 Annual FFC Alpha 0. 54% 0. 64% 0. 96% 1. 39% 1. 65% 1. 40% -0. 95% 0. 00% Alpha t-stat 1. 56 1. 92 1. 83 1. 34 2. 19 2. 06 -2. 17 0. 00 Market Size Exposure 1. 03 0. 03 1. 00 0. 00 1. 01 0. 05 1. 09 0. 47 1. 05 0. 56 1. 03 0. 57 1. 05 0. 60 1. 07 0. 42 1. 00 0. 00 Value Exposure 0. 34 0. 31 0. 37 0. 04 0. 39 0. 41 0. 10 0. 00 Momentum Exposure -0. 10 -0. 08 -0. 09 0. 00 -0. 11 -0. 09 -0. 11 -0. 02 0. 00 See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 21

Value and Size Factors Smart Beta Strategies All non-cap-weighted strategies have value and small

Value and Size Factors Smart Beta Strategies All non-cap-weighted strategies have value and small size tilt Four-Factor Model Decomposition (U. S. 1964– 2012) Annual FFC Alpha Market Size Value Momentum Strategy Alpha t-stat Exposure 1. 05% 1. 39 0. 70 0. 13 0. 34 0. 00 Minimum Variance 9 0. 40% 0. 54 0. 83 0. 26 0. 04 Maximum Diversification 10 11 0. 63% 1. 32 1. 03 0. 36 0. 26 -0. 03 Risk-Efficient (λ=2) 12 0. 31% 0. 49 0. 94 0. 03 0. 21 0. 03 Risk Cluster Equal Weight 0. 13% 0. 65 1. 01 0. 07 0. 11 -0. 01 Diversity Weighting 13 0. 64% 1. 83 1. 01 0. 05 0. 37 -0. 09 Fundamentals Wt 7 9 0. 54% 1. 07 1. 08 0. 45 0. 25 -0. 04 Inverse of Minimum Variance 0. 52% 0. 94 1. 07 0. 38 0. 28 -0. 05 Inverse of Maximum Diversification 10 0. 25% 0. 51 1. 04 0. 41 0. 27 -0. 03 Inverse of Risk-Efficient (λ=2)11 12 -0. 16% -0. 19 1. 06 0. 62 0. 41 -0. 02 Inverse of Risk Cluster Equal Weight 0. 54% 0. 91 1. 04 0. 59 0. 33 -0. 04 Inverse of Diversity Weighting 13 1. 40% 2. 06 1. 05 0. 60 0. 41 -0. 11 Inverse of Fundamental Wt 7 4 U. S. Cap Wt 0. 00% 0. 00 1. 00 0. 00 See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 22

Value and Size Factors Malkiel’s Monkey All non-cap-weighted strategies have value and small size

Value and Size Factors Malkiel’s Monkey All non-cap-weighted strategies have value and small size tilt Four-Factor Model Decomposition (U. S. 1964– 2012) Annual FFC Alpha Market Size Value Momentum Strategy Alpha t-stat Exposure 14 -0. 29% -0. 31 1. 05 0. 37 0. 13 -0. 02 Average of 100 Malkiel's Monkey Portfolios U. S. Cap Wt 4 0. 00% 0. 00 1. 00 0. 00 See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 23

Value and Size Factors All smart beta strategies are largely similar » Any portfolio

Value and Size Factors All smart beta strategies are largely similar » Any portfolio return can be decomposed: �� _�� =�� ∙�� [�� _�� ]=�� ∙�� [�� _�� ]+�� ∙������ [�� _�� , �� _�� ] =���� +�� ∙������ [�� _�� , �� _�� ] » ���� "—"Return of equally weighted portfolio—no skill! » �� ∙������ [�� _�� , �� _�� ]"—"skill from security selection. Jonathan Berk: Value and size factors generate returns because they sort stock based on prices! Smart Beta weights unrelated to price—no skill Smart Beta are all equal to each other! 24

Value and Size Factors Cap-weighted—negative skill benchmark » Weighting on price is negatively related

Value and Size Factors Cap-weighted—negative skill benchmark » Weighting on price is negatively related to future return » Cap-weighted is the only strategy in the study with negative skill! 25

Choosing a Smart Beta Strategy 26

Choosing a Smart Beta Strategy 26

Choosing a Smart Beta Strategy Implementation matters! » Capacity » Turnover » Trading costs

Choosing a Smart Beta Strategy Implementation matters! » Capacity » Turnover » Trading costs 27

Choosing a Smart Beta Strategy Research Results: Capacity/Average Size (Beginning of 2012) Weighted Average

Choosing a Smart Beta Strategy Research Results: Capacity/Average Size (Beginning of 2012) Weighted Average Market Cap (USD Billions) Weighted Average Bid-Ask Spreads Weighted Average Adjusted Daily Volume (USD Millions) Global U. S. Market Capitalization 4 66. 3 80. 8 0. 1% 0. 0% 464. 9 735. 4 Equal Wt 15 23. 9 11. 5 0. 2% 0. 1% 175. 0 132. 5 Risk Cluster Equal Weight 12 37. 5 37. 1 0. 2% 0. 0% 189. 1 312. 0 Diversity Wt 13 52. 4 50. 5 0. 1% 0. 0% 368. 2 477. 9 Fundamentals Wt 7 59. 1 66. 3 0. 1% 397. 8 617. 5 Minimum Variance 9 24. 0 19. 6 0. 4% 0. 1% 128. 4 136. 4 Maximum Diversification 10 20. 1 14. 8 0. 5% 0. 1% 122. 5 124. 1 Risk-Efficient 11 26. 9 12. 1 0. 2% 0. 1% 193. 5 140. 1 Strategy See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 28

Choosing a Smart Beta Strategy Research Results: Turnover Characteristics Developed Markets 1987– 2009 Average

Choosing a Smart Beta Strategy Research Results: Turnover Characteristics Developed Markets 1987– 2009 Average Annual Turnover United States 1964– 2009 Average Annual Turnover Fundamentals Wt 7 14. 9% 13. 6% Market Capitalization 4 8. 4% 6. 7% Equal Wt 15 21. 8% 22. 6% Risk Cluster Equal Weight 12 32. 3% 25. 4% Diversity Wt 13 10. 4% 8. 9% Minimum Variance 9 52. 0% 48. 5% Maximum Diversification 10 59. 7% 56. 0% Risk-Efficient 11 36. 4% 34. 2% Strategy See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 29

Global Findings 30

Global Findings 30

Global Findings 1. High Risk—High Reward Upside-down strategies also outperform! Global, 1991– 2012 Return

Global Findings 1. High Risk—High Reward Upside-down strategies also outperform! Global, 1991– 2012 Return Standard Deviation Sharpe Ratio Information Ratio 7. 9% 16. 9% 0. 28 0. 19 Market Beta Wt 2 6. 6% 18. 8% 0. 18 -0. 10 Downside Semi-Deviation Wt 3 Inverse of Volatility Wt 1 Inverse of Market Beta Wt 2 Inverse of Downside Semi-Deviation Wt 3 8. 3% 9. 4% 9. 1% 7. 1% 16. 8% 13. 9% 12. 3% 13. 9% 15. 1% 0. 31 0. 44 0. 51 0. 43 0. 29 0. 53 0. 33 0. 48 0. 26 0. 00 Strategy Volatility Wt 1 Global Cap Wt 4 See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 31

Global Findings 2. Strong Fundamentals—High Reward Upside-down strategies also outperform! Global, 1991– 2012 Strategy

Global Findings 2. Strong Fundamentals—High Reward Upside-down strategies also outperform! Global, 1991– 2012 Strategy Book Value Wt 5 Return Standard Deviation 9. 5% 16. 1% 0. 40 0. 49 5 -Yr Avg Earnings Wt 6 11. 2% 15. 3% 0. 51 0. 76 Fundamentals Wt 7 11. 0% 8. 8% 10. 6% 12. 5% 6. 6% 7. 1% 15. 3% 17. 1% 15. 5% 15. 4% 15. 7% 15. 9% 15. 1% 0. 49 0. 33 0. 48 0. 58 0. 22 0. 26 0. 72 0. 40 0. 61 0. 83 0. 80 -0. 12 0. 00 Earnings Growth Wt 8 Inverse of Book Value 5 Inverse of 5 -Yr Avg Earnings Wt 6 Inverse of Fundamental Wt 7 Inverse of EPS Growth 8 Global Cap Wt 4 Sharpe Ratio Information Ratio See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 32

Global Findings 3. Popular Smart Beta Strategies Upside-down strategies also outperform! Global, 1991– 2012

Global Findings 3. Popular Smart Beta Strategies Upside-down strategies also outperform! Global, 1991– 2012 Return Standard Deviation Sharpe Ratio Information Ratio 8. 4% 9. 9% 0. 53 0. 13 Maximum Diversification 10 7. 1% 11. 3% 0. 35 0. 00 Risk-Efficient (λ=2)11 9. 0% 14. 8% 0. 40 0. 53 Risk Cluster Equal Weight 12 9. 5% 15. 9% 0. 40 0. 36 Diversity Weighting 13 7. 4% 15. 3% 0. 28 0. 22 Inverse of Minimum Variance 9 8. 7% 16. 2% 0. 34 0. 45 Inverse of Maximum Diversification 10 8. 9% 15. 9% 0. 36 0. 48 Inverse of Risk-Efficient (λ=2)11 8. 5% 15. 5% 0. 35 0. 40 Inverse of Risk Cluster Equal Weight 12 9. 4% 16. 7% 0. 38 0. 35 Inverse of Diversity Weighting 13 8. 7% 15. 5% 0. 36 0. 45 Global Cap Wt 4 7. 1% 15. 1% 0. 26 0. 00 Strategy Minimum Variance 9 See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 33

Global Findings Malkiel’s Monkey Global, 1991– 2012 Strategy Average of 100 Malkiel's Monkey Portfolios

Global Findings Malkiel’s Monkey Global, 1991– 2012 Strategy Average of 100 Malkiel's Monkey Portfolios 14 Global Cap Wt 4 Return Standard Deviation Sharpe Ratio Information Ratio 8. 1% 16. 4% 0. 31 0. 16 7. 1% 15. 1% 0. 26 0. 00 See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 34

Global Findings Risk Strategies All non-cap-weighted strategies have value and small size tilt Four-Factor

Global Findings Risk Strategies All non-cap-weighted strategies have value and small size tilt Four-Factor Model Decomposition (Global 1991– 2012) Strategy Volatility Wt 1 Market Beta Wt 2 Downside Semi-Deviation Wt 3 Inverse of Volatility Wt 1 Inverse of Market Beta Wt 2 Inverse of Downside Semi-Deviation Wt 3 Global Cap Wt 4 Annual FFC Alpha 0. 12% -0. 13% 0. 55% 0. 77% 0. 66% 0. 54% 0. 00% Alpha t-stat 0. 20 -0. 13 0. 83 1. 28 0. 64 0. 90 0. 00 Market Size Value Momentum Exposure 1. 10 0. 31 0. 13 -0. 06 1. 19 0. 37 0. 03 -0. 15 1. 09 0. 29 0. 15 -0. 07 0. 92 0. 13 0. 34 -0. 04 0. 77 0. 01 0. 44 0. 01 0. 92 0. 14 0. 33 -0. 03 1. 00 0. 00 See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 35

Global Findings Fundamental Strategies All non-cap-weighted strategies have value and small size tilt Four-Factor

Global Findings Fundamental Strategies All non-cap-weighted strategies have value and small size tilt Four-Factor Model Decomposition (Global 1991– 2012) Strategy Book Value Wt 5 5 -Yr Avg Earnings Wt 6 Fundamentals Wt 7 Earnings Growth Wt 8 Inverse of Book Value 5 Inverse of 5 -Yr Avg Earnings Wt 6 Inverse of Fundamental Wt 7 Inverse of EPS Growth Wt 8 Global Cap Wt 4 Annual FFC Alpha 1. 31% 2. 36% 1. 93% 1. 55% 1. 94% 2. 70% 2. 81% -1. 20% 0. 00% Alpha t-stat 2. 22 3. 28 2. 98 1. 91 2. 60 3. 28 3. 44 -1. 57 0. 00 Market Exposure 1. 02 0. 97 0. 98 1. 11 0. 98 0. 99 1. 02 1. 00 Size Exposure 0. 09 -0. 01 0. 09 0. 27 0. 33 0. 29 0. 35 0. 43 0. 00 Value Momentum Exposure 0. 40 -0. 12 0. 39 -0. 09 0. 43 -0. 11 -0. 02 -0. 04 0. 46 -0. 13 0. 50 -0. 12 0. 51 -0. 15 0. 06 0. 02 0. 00 See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 36

Global Findings Smart Beta Strategies All non-cap-weighted strategies have value and small size tilt

Global Findings Smart Beta Strategies All non-cap-weighted strategies have value and small size tilt Four-Factor Model Decomposition (Global 1991– 2012) Strategy Minimum Variance 9 Maximum Diversification 10 Risk-Efficient (λ=2)11 Risk Cluster Equal Weight 12 Diversity Weighting 13 Inverse of Minimum Variance 9 Inverse of Maximum Diversification 10 Inverse of Risk-Efficient (λ=2)11 Inverse of Risk Cluster Equal Weight 12 Inverse of Diversity Weighting 13 Global Cap Wt 4 Annual FFC Alpha 1. 73% 0. 12% 0. 53% 0. 97% -0. 09% 0. 42% 0. 50% 0. 44% 0. 63% 0. 47% 0. 00% Alpha t-stat 1. 33 0. 08 0. 93 0. 66 -0. 33 0. 76 0. 88 0. 75 0. 42 0. 84 0. 00 Market Size Value Momentum Exposure 0. 55 0. 02 0. 30 -0. 06 0. 65 0. 11 0. 24 0. 01 0. 98 0. 19 0. 28 -0. 03 1. 00 0. 25 0. 21 0. 08 1. 01 0. 07 0. 04 0. 00 1. 07 0. 24 0. 23 -0. 05 1. 04 0. 21 0. 29 -0. 07 1. 01 0. 22 0. 25 -0. 06 1. 05 0. 14 0. 28 0. 02 1. 02 0. 34 0. 19 -0. 03 1. 00 0. 00 See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 37

Global Findings Malkiel’s Monkey All non-cap-weighted strategies have value and small size tilt Four-Factor

Global Findings Malkiel’s Monkey All non-cap-weighted strategies have value and small size tilt Four-Factor Model Decomposition (Global 1991– 2012) Annual Strategy FFC Alpha Average of 100 Malkiel's Monkey Portfolios 14 0. 15% Global Cap Wt 4 0. 00% Alpha t-stat 0. 10 0. 00 Market Size Value Momentum Exposure 1. 02 1. 00 0. 23 0. 00 0. 18 0. 00 -0. 03 0. 00 See slide 37 for disclosures regarding individual strategies. Source: Research Affiliates, LLC. 38

Notes: Strategy Simulation Descriptions 1 Volatility weighted: Weighted based on the standard deviation of

Notes: Strategy Simulation Descriptions 1 Volatility weighted: Weighted based on the standard deviation of monthly returns over the five year window prior to index construction. 2 Market Beta Weighted: Weighted based on CAPM betas using market factor kindly provided by Kenneth French on his website. The market beta loading is estimated using monthly returns data over five years window prior to index construction. 3 Downside Semi-Deviation Weighted: Weighted based on downside semi-deviation of the monthly returns over five year period prior to index construction. 4 Cap-Weighted: Weighted based on market capitalization. The market capitalization is computed using December close of the year prior to index construction. 5 Book Weighted: Weighted based on the book value of equity. We use the book value from the fiscal year two years prior to index construction. We introduce delay to avoid forward-looking bias. 6 Five-year Average Earnings Weighted: Weighted based on the average of the five-year earnings. The averaging period covers the five fiscal years ending with the fiscal year two years prior to index construction. We introduce delay to avoid forward-looking bias. 7 Fundamentals Weighted: Weighted based on the five year averages of cash flows, dividends, sales and the most recent book value of equity. We introduce two year delay to avoid forward-looking bias. Following the original method, we select top stocks with the largest fundamental weight. For details see Arnott, Hsu, and Moore (2005). 8 Earnings Growth Weighted based on five-year average dollar change in earnings divided by the average absolute dollar value of earnings over the five-year period. The last fiscal years of the measuring window is taken two years prior to index construction. We introduce delay to avoid forward-looking bias. 9 Minimum Variance: To construct the minimum variance strategy we use the method of Clarke, de Silva, and Thorley (2006). 10 Maximum Diversification Portfolio optimized to maximize expected diversification ratio, which is defined as the ratio of weighted average risk to the expected portfolio risk. For details see Choueifaty and Coignard (2008). 11 Risk-Efficient (λ=2) Mean-variance optimized portfolio assuming that expected excess returns are proportional to the stocks’ downside semi-deviation, and with stringent constraint to limit portfolio concentration. For details see Amenc et al (2010). 12 Risk Cluster Equal Weight Applying statistical methods to identify major market risk factors, assumed to be driven by industries and geographies, and then equally weight these uncorrelated risk clusters. 13 Diversity Weighting: Weighted based on the market capitalization weight raised to the power of a constant that is between zero and one to tilt the portfolio towards small cap stocks while limiting tracking error. We used the value of 0. 76 in our simulation. 14 Malkiel’s Monkey: Average of 100 portfolios, where each of the individual portfolios is rebalanced annually by randomly selecting 30 stocks out of the universe of the largest 1000 stocks by market capitalization. 15 Equal Weighting: Equally weighted portfolio of 1000 largest stocks by market capitalization . 39

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