tion 2014 : ahead - cfaboston.orgisi’s quantitative research team. françois was formerly with...

The Boston Security Analysts Society, Inc.

ASSET ALLOCATION 2014:

WARNING! STRUCTURAL SHIFTS AHEAD

JANUARY 14, 2014 Westin Copley, Copley Place, Boston

THANK YOU TO OUR SPONSORSPLATINUM

GOLD

Welcome to BSAS’ Asset Allocation 2014: Warning! Structural Shifts Ahead.

On behalf of the Asset Allocation Conference planning committee, I’d like to welcome all our

participants, speakers and our sponsors to our third annual asset allocation full day seminar.

We’ve designed today’s seminar to address you some of the most innovative thinking around broad

portfolio construction design that we have come across in the past decade. And, we’ve tapped into

a deep pool of experts from well-known research and money management firms along with key

asset owners to give you a well-balanced perspective on the challenges and opportunities for

investors seeking to position their portfolios for success in 2014. We hope you find today’s

program to be timely, insightful and thought provoking and we encourage your active participation

throughout the day’s agenda.

The title this year, "Asset Allocation 2014: Warning: Structural Changes Ahead!” may at first blush

conjure up a cautionary outlook for the year ahead, laced with more potential turmoil and

danger. On the contrary, this theme was chosen for 2014 because 2014 marks a year that

innovation and material structural change will finally take hold in the area of asset allocation and

portfolio construction, and we want you to be prepared for the major shift in thinking by

investors. Investors have been contemplating major changes to their asset allocation policies and

processes and considering non-traditional portfolio construction concepts since the financial crisis

of 2008, when academics and practitioners alike were challenging the assumptions of Modern

Portfolio Theory. And from those early discussions, a new breed of alternative portfolio

construction approaches was born. To date, but for corporate pension plans who have embraced

an LDI approach and a few trailblazers and research firms, few others have made major structural

changes to the way they build their portfolios and make asset allocation decision. With the growing

popularity of new portfolio design techniques like smart beta and risk premia /factor-based asset

allocation, 2014 may mark not only the "great rotation" out of fixed income in equities, but may

become the year that these new innovative asset allocation approaches are embraced by the

mainstream.

I’d like to take a moment to thank all the Programs Chairs, education volunteers and BSAS staff for

their tireless efforts in bringing the Asset Allocation 2014 conference to life. On behalf of the BSAS,

I’d also like to offer our appreciation to the our esteemed line up of speakers for coming to Boston

in the dead of winter to share their experiences, expertize, and unique perspectives on portfolio

construction trends and best practices for 2013 with you. Finally, I’d like to thank our sponsors for

helping us to bring such a high caliber of speakers and programming content at to this year’s

participants a reasonable cost, a feature of BSAS events that we hope will continue to allow us to

offer affordable programs without sacrificing quality of the content.

Best,

Stacey Marino, CFA, CAIA

Chair, Asset Allocation Conference Planning Committee

BSAS Board of Directors

Asset Allocation Conference planning committee:

James Anderson, CFA, ClearMomentum

Brent Bell, CFA, FRM, State Street Global Advisors

Christopher Foti, CFA, BNY Mellon, BSAS Board of Directors

Peter Gerlings, CFA, Segal Rogerscasey

Michael Greis, Riverbend Advisors

George Kimball

Erinn King, CFA, Payden & Rygel

Bruce Picard, CFA, MassMutual Financial Group

Lawrence Pohlman, BSAS Board of Directors

Shana Sissel, CAIA, Fidelity Investments

Guillermo Tello, CFA, CFP, U.S. Trust, Bank of America

Vitaly Veksler, CFA, Beyond Borders Investment Strategies




8:00am - 8:30am Registration and Continental Breakfast

8:30am - 8:45am Welcome and Introductions

8:45am - 9:30amInvesting for the 10 Great Rotations Ahead Francois Trahan, PartnerCornerstone Marco

9:30am - 10:15amInnovations in Smart BetaRic Thomas, CFA, Senior Managing Director State Street Global Advisors

10:15am - 10:45am Break

10:45am - 11:30amRisk ParityLaurnz Swartz, Former Chief Investment Officer Fairfax County Retirement Systems

11:30am - 12:15pmAlternative Investment Opportunities in 2014 and Beyond John Christmas, Managing DirectorJ.P. Morgan Private Bank

12:15pm - 1:15pmNetworking Lunch

1:15pm-2:00pmDiversifying Beyond the Equity PremiumAntti Ilmanen, Managing DirectorAQRExpected Returns: An Investor’s Guide to Harvesting Market Rewards

2:00pm - 2:45pm Alternatives on the Efficient Frontier Peter Shepard, Executive Director & Head ofMulti-Asset class and Alternatives ResearchMSCI

2:45pm - 3:15pmBreak

3:15pm - 4:00pmEmerging Markets: Opportunities in Currencies, Debt and Equities Peter Marber, Head of Emerging MarketsLoomis Sayles

4:00pm - 4:45pmA Fireside Chat on the Future of Asset Allocation for Endowments Jane Mendillo, President and CEOHarvard Management Company

4:45pm - 5:00pm Closing Remarks

5:00pm - 6:00pmNetworking Reception

AGENDA




John Christmas, Managing Director, J.P. Morgan Private BankJohn Christmas is a Managing Director of J.P. Morgan Securities LLC and member of J.P. Morgan Private Bank’s Alternative Investments Group in New York. Mr. Christmas sits on the Private Bank’s Investment Team, which is responsible for making strategic investment decisions for Private Banking clients and also helps coordinate all direct investment deals. Prior to joining the Private Bank, Mr. Christmas worked in institutional sales for 15 years, selling and trading a wide range of products including equities, derivatives and high yield bonds. He began his career at Friedman Billings and Ramsey in Arlington, VA where he worked as an arbitrage trader before moving into institutional sales with a focus on covering hedge funds. In 2000, he moved to New York to join J.P. Morgan’s Institutional Equity sales force with continued focus on covering hedge funds. Mr. Christmas left J.P. Morgan in 2006 to join CIBC and returned to J.P. Morgan in 2010. He received a B.A. from Brown University in 1996.

Antti Ilmanen, Managing Director, AQR Author of Expected Returns: An Investor’s Guide to Harvesting Market Rewards Antti Ilmanen, Ph.D., Managing Director (London) Antti, a Managing Director at AQR, manages the Portfolio Solutions Group, which advises institutional investors and sovereign wealth funds, and develops AQR’s broad investment ideas. Before AQR, Antti spent seven years as a senior portfolio manager at Brevan Howard, a macro hedge fund, and a decade in a variety of roles at Salomon Brothers/Citigroup. He began his career as a central bank portfolio manager in Finland. Antti earned M.Sc. degrees in economics and law from the University of Helsinki and a Ph.D. in finance from the University of Chicago. Over the years, he has advised many institutional investors, including Norway’s Government Pension Fund Global and the Government of Singapore Investment Corporation. Antti has published extensively in finance and investment journals and has received the Graham and Dodd award and the Bernstein Fabozzi/Jacobs Levy award for his articles. His book Expected Returns (Wiley, 2011) is a broad synthesis of the central issue in investing. Antti recently scored a rare double in winning the best-paper and runner-up award for best articles published in 2012 in The Journal of Portfolio Management (co-authored articles “The Death of Diversification Has Been Greatly Exaggerated” and “The Norway Model”).

Peter Marber, Head of Emerging Markets, Loomis SaylesPeter Marber is currently Head of Emerging Markets Investments at Loomis Sayles & Company. He was formerly Chief Business Strategist and head of global emerging markets debt at HSBC Global Asset Management. Before that, he was a founding partner, senior portfolio manager and chief investment strategist for The Atlantic Funds, LLC which was acquired by HSBC in 2005. Peter has been a faculty member at Columbia University since 1993 and will begin teaching at Harvard University in 2014. He is the author of From Third World to World Class: The Future of Emerging Markets in the Global Economy, Money Changes Everything: How Global Prosperity is Reshaping Our Needs, Values, and Lifestyles and Seeing the Elephant: Understanding Globalization from Trunk to Tail.

Jane Mendillo, President and CEO, Harvard Management CompanyJane Mendillo became President and Chief Executive Officer of Harvard Management Company (HMC) on July 1, 2008. Since rejoining HMC, Jane has reoriented and grown HMC’s investment platform and organization to position the portfolio for continued long-term success. Ms. Mendillo returned to HMC after serving as Chief Investment Officer of Wellesley College from 2002-2008, where she built the college’s first investment office and restructured its investment portfolio.

Prior to Wellesley, Ms. Mendillo spent 15 years at HMC where her responsibilities included oversight of all of the portfolio’s outside-managed assets as Vice President of External Management, after serving as a key member of the Internal Equity and Private Equity management teams. Ms. Mendillo earned her BA and MBA degrees from Yale University. She began her business career as a management consultant with Bain & Company in Boston. She is a Chartered Financial Analyst and a member of the Boston Security Analysts Society, Inc., the Boston Committee on Foreign Relations and the Boston Economic Club and serves as a member of the Board of Directors for the Boston Foundation. She also serves on the Investment Committees at Partners Healthcare and the Rockefeller Foundation.

SPEAKER BIOS

Peter Shepard, Executive Director & Head of Multi-Asset class and Alternatives Research, MSCIPeter Shepard is Executive Director and Head of Multi-Asset Class and Alternatives Research at MSCI. He led development of the Barra Integrated Model, spanning global stocks, bonds, commodities, currencies, hedge funds, volatility futures, and most recently global private real estate and private equity. He was also an architect of the Barra Global Equity Model, and has done research in portfolio construction. Dr. Shepard holds a Ph.D. in theoretical physics from the University of California at Berkeley and has publications in physics and finance. Dr. Shepard also holds a Bachelors degree in physics and mathematics from Brown University.

Laurnz Swartz, Former Chief Investment OfficerFairfax County Retirement SystemsMr. Swartz recently retired after 15 years with Fairfax County where he led the investment team as both Executive Director (1997-2008) and Chief Investment Officer (2009-2013) of the Retirement Administration Agency. In those roles, he supported the Boards of three defined benefit plans with total assets of $6 billion. Mr. Swartz was selected by Institutional Investor Magazine as Small Public Fund Manger of 2013.

Before joining Fairfax County in 1997, Mr. Swartz held a variety of positions with Prudential Insurance and the Prudential Asset Management Company including Vice President, Retirement Administration and Vice President, Financial Services. Larry received a B.A. in Economics from Yale University and an M.B.A. from Rutgers University.

Ric Thomas, CFA, Senior Managing Director State Street Global AdvisorsRic is a Senior Managing Director of State Street Global Advisors and is Global Head of Strategy and Research for SSgA’s Investment Solutions Group (ISG). Previously at SSgA, Ric was head of Alternative Investments and also served as the Head of Global Enhanced Equity. Prior to joining SSgA in 1998 Ric was a Quantitative Analyst in Fixed Income for Putnam Investments and an Assistant Economist at the Federal Reserve Bank of Kansas City.

Francois Trahan, Partner, Cornerstone MarcoFrançois Trahan leads Cornerstone Macro’s portfolio strategy efforts. An economist by training, he is widely praised for his differentiated insights into the dynamics of the markets and his unique understanding of the business cycle. Prior to founding Cornerstone, François was the Vice Chairman and Chief Investment Strategist of Wolfe Trahan & Co. Previously, he was Executive Managing Director and Chief Investment Strategist at ISI Group, as well as head of ISI’s Quantitative Research Team. François was formerly with Bear Stearns & Co. where he served as Chief Investment Strategist for four years. Earlier, he worked for Ned Davis Research and the Bank Credit Analyst Research Group.

In 2013, François was voted to Institutional Investor magazine’s All-American Research Team as the #1 Portfolio Strategist, and has been selected as #1 for seven of the past nine years. Since 2010, he has also been ranked among the top analysts for Quantitative Analysis as well. François received his undergraduate and graduate degrees in economics and econometrics from the University of Montreal.

1

Innovations in Smart Beta

January 14, 2014

Ric Thomas, CFA

Global Head of Strategy and Research, Investment Solutions Group

SSgA

BSAS — Asset Allocation 2014

MACS-0818

2

The Rise of ―Smart‖ Beta

AUM = $142 Billion

— Economist Magazine, July 2013

53% of Institutions to increase their use of ―Smart‖ Beta ETFs over next

3 years

— Cogent Research, December 2013

Two forthcoming surveys confirm rising institutional demand.

— Cogent Research, Q1 2014

— Longitude Partners, Q1 2014

But… Is “Smart” Beta a smart idea?

MACS-0818

3

Advanced Beta

1. Alternatives to Cap Weighting – Valuation based

– Low volatility

– Smaller capitalization

– Quality focused

– Equal weighted

– GDP weighting

– etc.

3. Alternative Asset Class Payoffs – Leveraged

– Inverse

– Protected

– Option over-writing

– Collars

– etc.

2. Non-Traditional Asset Classes – Break-even inflation

– Commodities

– Gold

– Volatility

– Currency carry

– etc.

4. Specialized Rules-based Strategies – Merger arbitrage

– Trend-following

– Convertible arbitrage

– Active manager emulation

– etc.

The Advanced Beta Opportunity Set

MACS-0818

4

• Low Beta (Black, Jensen and Scholes, 1972)

• Size (Banz, 1981 and Reinganum, 1981)

• Price to Earnings (Basu, 1977)

• Price to Book (Fama/French, 1993)

• Quality (Haugen, 1979)

• Momentum (Jagadeesh and Titman, 1993)

• Long-Term Reversal (DeBondt and Thaler, 1985)

Evidence of Return Premiums

Academics have identified these equity factors as earning return premiums:

MACS-0818

5

Advanced Beta Strategies: Multiple Factors

SSgA Attribute Definitions

MACS-0818

Attribute Description

Valuation Price/Fundamental

Fundamentals: Earnings, Cashflow, Sales, Dividend, and Book Value

Volatility Volatility of Total Return

60-month variance

Size Market Capitalization

Free float market capitalization

Momentum Total Return

Trailing 12m

Quality (1) Profitability, (2) Earnings Consistency, and (3) Low Leverage

ROA, EPS variability, LT Debt/Equity

6 MACS-0818


But do these factors outperform over time?

Value Momentum Volatility Size Quality

Quintile 1 14.33% 12.94% 11.57% 10.36% 10.85%

Quintile 2 11.19 11.96 11.13 10.38 10.55

Quintile 3 10.18 9.34 10.03 9.75 10.22

Quintile 4 6.09 7.39 9.05 9.37 9.30

Quintile 5 5.89 5.40 5.45 8.15 7.21

Quintile 1–Quintile 5 8.44 7.54 6.12 2.22 3.64

Std Dev Q1–Q5 12.37 21.47 19.33 13.69 9.03

Excess/Std Dev 0.68 0.35 0.32 0.16 0.40

Source: SSgA, MSCI

Hypothetical returns are based upon estimates and reflect subjective judgments and assumptions. These results were achieved by means of a mathematical

formula and do not reflect the effect of unforeseen economic and market factors on decision-making. The hypothetical returns are not necessarily indicative

of future performance, which could differ substantially.

January 1987 – March 2013

7 MACS-0818


Diversification Benefits of Risk Premiums:

Can Factors be grouped together based on correlation?

Factors to consider:

• Value and Quality have a meaningful negative correlation

• Volatility and/or Momentum could provide downside protection

• Size has low/negative correlations to other factors, except value

Correlation of Excess Returns

Value Momentum Volatility Size Quality

Value 1.00 -0.41 0.12 0.37 -0.38

Mom -0.41 1.00 0.59 -0.46 0.53

Volatility 0.12 0.59 1.00 -0.41 0.53

Size 0.37 -0.46 -0.41 1.00 -0.37

Quality -0.38 0.53 0.53 -0.37 1.00

January 1987 – March 2013

Source: SSgA, MSCI Hypothetical returns are based upon estimates and reflect subjective judgments and assumptions. These results were achieved by means of a mathematical formula and do not reflect the effect of unforeseen economic and market factors on decision-making. The hypothetical returns are not necessarily indicative of future performance, which could differ substantially. The correlation coefficient measures the strength and direction of a linear relationship between two variables. It measures the degree to which the deviations of one variable from its mean are related to those of a different variable from its respective mean.

8

Redesigning Equities

Traditional Model Factor Based Model

Low Beta

Value

Quality

Size

Momentum

Source: State Street Global Advisors The information contained above is for illustrative purposes only.

Core-Cap Weighted

Active #1

Active #2

Active #3

Active #4

MACS-0818

9

Expanding the Alternative Risk Premia Universe

Market Neutral Equity Risk Premiums

Source: SSgA, MSCI.

• Long Value — Short Growth (Positive Beta)

• Long Low Beta — Short High Beta (Negative Beta)

• Long Equal Weighted — Short Cap Weighted

Currency

MACS-0818

• Long/Short Carry (Positive Beta)

• Long/Short GDP

• Long/Short Purchasing Power Parity (Value with downside protection)

Commodities

• Commodity Roll Premium (Positive Beta)

• Momentum (Negative Beta)

Credit & Other

• CDX

• Variance Swaps, VIX Futures (Short positions are Long Beta)

10

Portable Beta

Is this the future?

Source: State Street Global Advisors The information contained above is for illustrative purposes only.

Equities

Fixed Income

Real Estate

Private Equity

Hedge Funds

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Alternative Risk Premia

100%

Overlay

> 100%

11

Emulation Strategies — Merger Arb

Merger Arbitrage Payoff

Source: SSgA. For illustrative purposes only.

• Maximum potential loss is greater than maximum potential gain

• Likelihood of gain is greater than the likelihood of loss

• What type of option strategy does this look like?

• Key systematic risk: VOLATILITY

MACS-0818

Pre-Announcement

Price

Arbitrageur's

Purchase Price

Buyout

Price

Po

ten

tia

l

Ga

in

Po

ten

tia

l

Lo

ss

12

Emulation Strategies — Trend Following Managed Futures

• Profit if upward trend continues

• Profit if downward trend continues

• What type of option strategy does this look like?

• Is the investor long or short volatility?

Source: SSgA. For illustrative purposes only.

Trend follower

buys S&P 500 as

price rises.

Trend follower

shorts S&P 500

as price falls.

Trend follower

profits if S&P

500 keeps falling.

Trend follower

profits if S&P 500

keeps rising.

1A

2A

1B

2B

Managed Futures Payoff

Trend Following Payout Profile

MACS-0818

13

• Managing Beta exposures is a ―smart‖ way to control risk, not just enhance return

• Most asset owners are heavily exposed to growth (equity beta)

• Most fixed income strategies are heavily exposed to term structure factors

• Reweighting the beta/or factor exposure can help with diversification

Advanced Beta and Risk

MACS-0818

14

• PCA can reduce the dimensions and complexity of a correlation matrix

• PCA helps simplify our understanding of the main sources of return variations

• PCA can show how many true risk factors (components) explain asset class returns

• PCA requires fundamental judgment to interpret the results

• Often (but not always) the results are intuitive

How Many True Independent Factors can Explain Returns?

Principal Component Analysis (PCA)

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15

Factor Exposures for Major Asset Classes

Source: SSgA,.

As of September 30, 2013 MACS-0818

0.00

0.10

0.20

0.30

0.40

0.50

0.60

PC1 — Global Growth

-0.40

-0.20

0.00

0.20

0.40

0.60

0.80

PC2 — Global Term Structure

-0.40

-0.20

0.00

0.20

0.40

0.60

0.80

1.00

PC3 — Global Inflation

-0.80

-0.60

-0.40

-0.20

0.00

0.20

0.40

0.60

0.80

PC4 — Global Inflation Disconnect

16

Cumulative Proportion of Variance Explained by Factors

Source: SSgA,. Source: SSgA,.

As of September 30, 2013

Proportions are as of the date indicated, are subject to change, and should not be relied upon as current thereafter. MACS-0818

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

PC1 PC2 PC3 PC4

17

Key Findings

There are 3 factors that explain bulk of asset class returns

Source: SSgA, MSCI.

• Growth

• Term Structure

• Inflation

What is the effective exposure of a Pension fund to the first 3 factors?

MACS-0818

18

How Diversified are Pension Funds on the Risk Factors?

Risk Exposures to:

• Growth

• Term Structure

• Inflation

MACS-0818

The information contained above is for illustrative purposes only.

PC: “Term"

0%

PC: "Inflation“

6%

PC: "Other"

11%

PC: "Growth“

83%

19

Risk Parity

Objective is to Equalize Risk Exposures

σmv ≤ σRP ≤ σEW

Inflation

33%

Term

33%

Growth

34%

Risk Parity reconciles minimum variance with nominal diversification

MACS-0818

The information contained above is for illustrative purposes only.

Source: SSgA

Objective of Risk Parity — Risk Allocation

20

Factor Allocations in Fixed Income



Allocations are as of the date indicated, are subject to change, and should not be relied upon as current thereafter. MACS-0818

100% Barclays Global Aggregate PCA Decomposition

Global Term Structure

61.3%

Global Growth

16.0%

Global Inflation

1.7%

P-4

0.2%

P-6

6.3%

P-7

7.1%

P-8

2%

PC-Other

6.0%

21

Factor Allocations in Fixed Income

MACS-0818

74% Barclays Global Aggregate, 8%Global HY, 8% EM Debt

PCA Decomposition

Global Term Structure

42.3%

Global Growth

41.0%

P-4

0.3%

P-6

5.5%

P-7

4.8%

P-8

1.1%

PC-Other

4.3%

Global Inflation

0.2%

P-5

0.5%



Allocations are as of the date indicated, are subject to change, and should not be relied upon as current thereafter.

22

Comments on Alternatives to Cap-Weighting

• What factor or attribute is being emphasized?

• Is the historical evidence a product of data-mining or over-fitting?

• Why should one expect a superior investment outcome?

• Who owns the investment decision?

• Can the investor weather interim volatility?

• Are costs acceptable?

Questions for investors considering alternatives to cap-weighting

MACS-0818

23 MACS-0818

Summary

• Advanced Beta allocations likely to grow

• Money will come from both active and traditional passive

• Large public and corporate DB plans will be key buyers

• Portable structures of interest in northern Europe. Trend may spread.

• Active managers need to differentiate. Unique factors + the ability to time.

• Managing risk in a ―smart‖ fashion will be just as important

Source: SSgA,

24

Appendix A: Important Disclosures

25 MACS-0818

Important Risk Disclosure

Investing involves risk including the risk of loss of principal.

The whole or any part of this work may not be reproduced, copied or transmitted or any of its contents disclosed to third

parties without SSgA's express written consent.

The information provided does not constitute investment advice and it should not be relied on as such. It should not be

considered a solicitation to buy or an offer to sell a security. It does not take into account any investor's particular

investment objectives, strategies, tax status or investment horizon. You should consult your tax and financial advisor.

All material has been obtained from sources believed to be reliable. There is no representation or warranty as to the

accuracy of the information and State Street shall have no liability for decisions based on such information.

Diversification does not ensure a profit or guarantee against loss.

The views expressed in this material are the views of Ric Thomas, Investment Solutions Group through the period ended

December 24, 2013 and are subject to change based on market and other conditions. This document contains certain

statements that may be deemed forward-looking statements. Please note that any such statements are not guarantees of

any future performance and actual results or developments may differ materially from those projected.

Risk associated with equity investing include stock values which may fluctuate in response to the activities of individual

companies and general market and economic conditions.

Although bonds generally present less short-term risk and volatility risk than stocks, bonds contain interest rate risks; the

risk of issuer default; issuer credit risk; liquidity risk; and inflation risk. This effect is usually pronounced for longer-term

securities. Any fixed income security sold or redeemed prior to maturity may be subject to a substantial gain or loss.

Investing in commodities entail significant risk and is not appropriate for all investors. Commodities investing entail

significant risk as commodity prices can be extremely volatile due to wide range of factors. A few such factors include

overall market movements, real or perceived inflationary trends, commodity index volatility, international, economic and

political changes, change in interest and currency exchange rates.

Source: SSgA,

26 MACS-0818


Investing in REITs involves certain distinct risks in addition to those risks associated with investing in the real estate

industry in general. Equity REITs may be affected by changes in the value of the underlying property owned by the REITs,

while mortgage REITs may be affected by the quality of credit extended. REITs are subject to heavy cash flow dependency,

default by borrowers and self-liquidation. REITs, especially mortgage REITs, are also subject to interest rate risk

(i.e., as interest rates rise, the value of the REIT may decline).

Investing in foreign domiciled securities may involve risk of capital loss from unfavorable fluctuation in currency values,

withholding taxes, from differences in generally accepted accounting principles or from economic or political instability in

other nations.

Investments in emerging or developing markets may be more volatile and less liquid than investing in developed markets

and may involve exposure to economic structures that are generally less diverse and mature and to political systems which

have less stability than those of more developed countries.

Investing in high yield fixed income securities, otherwise known as junk bonds, is considered speculative and involves

greater risk of loss of principal and interest than investing in investment grade fixed income securities. These Lower-quality

debt securities involve greater risk of default or price changes due to potential changes in the credit quality of the issuer.

Investing in futures is highly risky. Futures positions are considered highly leveraged because the initial margins are

significantly smaller than the cash value of the contracts. The smaller the value of the margin in comparison to the cash

value of the futures contract, the higher the leverage. There are a number of risks associated with futures investing

including but not limited to counterparty credit risk, currency risk, derivatives risk, foreign issuer exposure risk, sector

concentration risk, leveraging and liquidity risks.

Source: SSgA,

27 MACS-0818


―The MSCI is a trademark of MSCI Inc.‖

S&P GSCI® is a trademark of Standard & Poor's Financial Services LLC. and has been licensed for use by Goldman,

Sachs & Co.

Web: www.ssga.com

© 2013 State Street Corporation — All Rights Reserved

State Street Global Advisors, One Lincoln Street, Boston, MA 02111-2900

Tracking number: MACS-0818

Expiration Date — 12/31/2014.

Source: SSgA,

28

Appendix B: Biography

29

Biography

Ric Thomas, CFA

Ric is a Senior Managing Director of State Street Global Advisors and is Global Head of Strategy and Research for SSgA’s Investment Solutions

Group (ISG). Ric and his team offer extensive research services to clients, helping them address their most challenging problems. Actionable

solutions include customized liability driven strategies, tactical multi-asset allocation, tail risk solutions, and exposure management. Previously at

SSgA, Ric was Head of Alternative Investments and also served as the Head of Global Enhanced Equity.

Prior to joining SSgA in 1998 Ric was a Quantitative Analyst in fixed income for Putnam Investments and an Assistant Economist at the Federal

Reserve Bank of Kansas City.

Ric holds an MBA from the University of Chicago, an MA in Economics from the University of Colorado, a BA in Economics from Colorado State

University, and he has earned the Chartered Financial Analyst designation. Ric also serves on the Investment Committee for the Colorado State

University Foundation.

A Q RC A P I T A L

M A N A G E M E N TA Q RC A P I T A L

M A N A G E M E N T AQR Capital Management, LLC | Two Greenwich Plaza, Third Floor | Greenwich, CT 06830 | T: 203.742.3600 | F: 203.742.3100 | www.aqr.com

AQR C A P I T A L

M A N A G E M E N T

AQR Capital Management, LLC | Two Greenwich Plaza, Fourth Floor | Greenwich, CT 06830 | T: 203.742.3600 | F: 203.742.3100 | www.aqr.com

AQR C A P I T A L

M A N A G E M E N T

Diversifying Beyond the Equity Premium

Antti Ilmanen

AQR Capital Management

BSAS Asset Allocation Conference

Boston, January 2014

For Investment Professional Use Only.

A Q RC A P I T A L


M A N A G E M E N T

Disclosures

2

The information set forth herein has been obtained or derived from sources believed by AQR Capital Management, LLC (“AQR”) to be reliable. However, AQR does not make any representation or warranty,

express or implied, as to the information’s accuracy or completeness, nor does AQR recommend that the attached information serve as the basis of any investment decision. This document has been provided

to you solely for information purposes and does not constitute an offer or solicitation of an offer, or any advice or recommendation, to purchase any securities or other financial instruments, and may not be

construed as such. This document is intended exclusively for the use of the person to whom it has been delivered by AQR and it is not to be reproduced or redistributed to any other person. This document is

subject to further review and revision. Please refer to the Appendix for more information on risks and fees. For one-on-one presentation use only. Past performance is not an indication of future performance.

This presentation is not research and should not be treated as research. This presentation does not represent valuation judgments with respect to any financial instrument, issuer, security or sector that may be

described or referenced herein and does not represent a formal or official view of AQR.

The views expressed reflect the current views as of the date hereof and neither the speaker nor AQR undertakes to advise you of any changes in the views expressed herein. It should not be assumed that the

speaker will make investment recommendations in the future that are consistent with the views expressed herein, or use any or all of the techniques or methods of analysis described herein in managing client

accounts. AQR and its affiliates may have positions (long or short) or engage in securities transactions that are not consistent with the information and views expressed in this presentation.

The information contained herein is only as current as of the date indicated, and may be superseded by subsequent market events or for other reasons. Charts and graphs provided herein are for illustrative

purposes only. The information in this presentation has been developed internally and/or obtained from sources believed to be reliable; however, neither AQR nor the speaker guarantees the accuracy,

adequacy or completeness of such information. Nothing contained herein constitutes investment, legal, tax or other advice nor is it to be relied on in making an investment or other decision.

There can be no assurance that an investment strategy will be successful. Historic market trends are not reliable indicators of actual future market behavior or future performance of any particular investment

which may differ materially, and should not be relied upon as such. Target allocations contained herein are subject to change. There is no assurance that the target allocations will be achieved, and actual

allocations may be significantly different than that shown here. This presentation should not be viewed as a current or past recommendation or a solicitation of an offer to buy or sell any securities or to adopt

any investment strategy.

The information in this presentation may contain projections or other forward‐looking statements regarding future events, targets, forecasts or expectations regarding the strategies described herein, and is only

current as of the date indicated. There is no assurance that such events or targets will be achieved, and may be significantly different from that shown here. The information in this presentation, including

statements concerning financial market trends, is based on current market conditions, which will fluctuate and may be superseded by subsequent market events or for other reasons. Performance of all cited

indices is calculated on a total return basis with dividends reinvested.

The investment strategy and themes discussed herein may be unsuitable for investors depending on their specific investment objectives and financial situation. Please note that changes in the rate of exchange

of a currency may affect the value, price or income of an investment adversely.

Neither AQR nor the speaker assumes any duty to, nor undertakes to update forward looking statements. No representation or warranty, express or implied, is made or given by or on behalf of AQR, the

speaker or any other person as to the accuracy and completeness or fairness of the information contained in this presentation, and no responsibility or liability is accepted for any such information. By

accepting this presentation in its entirety, the recipient acknowledges its understanding and acceptance of the foregoing statement.

A Q RC A P I T A L


M A N A G E M E N T

Outline

I. Equity Premium

Historical evidence and prospective analysis

II. Additional Ways to Pursue the Equity Premium

Defensive equity, including value and momentum tilts through stock selection or timing

III.Why Do Many Institutions Choose to Depend on the Equity Premium?

Many mainstream investment models imply very high equity market correlations.

Reasons? Not justified by mean-variance efficiency but by “4Cs”: conviction,

constraints, conventionality, capacity

IV. Beyond the Equity Premium

Aggressive diversification through risk parity investing and alternative beta premia

3 For Investment Professional Use Only.

A Q RC A P I T A L


M A N A G E M E N T

I. Equity Premium

I. Equity Premium











A Q RC A P I T A L


M A N A G E M E N T

I. Equity Premium: Historical Evidence

Long-run world equity premium over cash is 4.4% (geometric mean in Dimson-Marsh-

Staunton (2012) for 1900-2011), with positive long-run premia in all countries studied

The equity premium over bonds is 3.5% and the real return is 5.4% (Morningstar data

for 1926-2011). Comparable U.S. figures are 0.6-0.8% higher. Comparable arithmetic

premia are 1.0-1.5% higher. T-costs and taxes would reduce these estimates

5

Sources: AQR, Ibbotson Associates (Morningstar). Stocks are represented by the S&P 500 Index since 1957 and comparable equity indices prior to 1957,. Bonds are represented by long-dated Treasuries. Past

performance is not a guarantee of future results.

Ex-post Rolling 20-Year Compound Average Equity Premium in the U.S.

-4%

0%

4%

8%

12%

16%

19

45

19

50

19

55

19

60

19

65

19

70

19

75

19

80

19

85

19

90

19

95

20

00

20

05

20

10

Equity Premium Over Cash Equity Premium Over Bonds


A Q RC A P I T A L


M A N A G E M E N T

-4%

0%

4%

8%

12%

16%

1909 1919 1929 1939 1949 1959 1969 1979 1989 1999 2009

Ex-ante Real Return on Equity Market Ex-ante Real Tsy Bond Yield

Ex-ante Real Tsy Bill Rate (1953 - ) Ex-ante Equity-Bond Premium

I. Equity Premium: Prospective Analysis

Forward-looking real returns are below historical average but equity premia over FI are

above average. Simple measures (‘Shiller’ E10/P and DDM) point to ca. 4% expected

real return on U.S. equities, compared to 0.5% real yields for bonds and -2% for cash

6

Ex-ante Real Return Estimates on Major U.S. Asset Classes, 1900 – 2013*

*Data through 10/31/2013.

Sources: Bloomberg, Robert Shiller’s website, Ibbotson Associates (Morningstar), Kozicki-Tinsley (2006), Federal Reserve Bank of Philadelphia, Blue Chip Economic Indicators, Consensus Economics. The ex-

ante real return on equity market is a 50/50 mix of Shiller E/P and Dividend/Price. Ex-ante real tsy bill rate treasury is 3m treasury bill yields over 1yr inflation forecast. Ex-ante real tsy bond yield is 10 year

treasury yield over 10 year inflation forecast. Ex-ante equity-bond premium is the difference between ex-ante real return on equity market and ex-ante real tsy bond yield. There is no guarantee, express or

implied, that long-term return targets will be achieved. Realized returns may come in higher or lower than expected. Past performance is no guarantee of future results.


1900

A Q RC A P I T A L


M A N A G E M E N T


I. Equity Premium


II.Additional Ways to Pursue the Equity Premium

Defensive equity, including value and momentum tilts through

stock selection or timing








A Q RC A P I T A L


M A N A G E M E N T

II. Defensive Equity Tilt: Seeks Similar Returns With Less Risk

Source: S&P 500 Index and AQR. Please see “Betting Against Beta” paper, Frazzini, Pedersen (2013) for more on the Low-Beta 30% portfolio. These are not the excess returns of an actual portfolio and are for

illustrative purposes only. Please see important disclosures in the Appendix. Broad-based securities indices are unmanaged and are not subject to fees and expenses typically associated with managed accounts or

investment funds. Investments cannot be made directly in an index. Here, beta risk refers to the risk associated with market volatility. Past performance is not a guarantee of future results.

Cumulative Total Returns on U.S. Equities, 1927 – 2011

8

Beta risk has not been rewarded within equity markets. In most asset classes, defensive

assets tend to have better risk-adjusted returns than their speculative brethren

Leverage aversion and lottery preferences appear to be the main explanations

Low-Beta 30% (lowest three deciles) vs Market 1927-2011: Compound Average Return

of 9.57% vs 9.45%, Vol 13.9% vs 18.9%, SR 0.48 vs 0.39

1

5

50

500

1927 1937 1947 1957 1967 1977 1987 1997 2007

Cu

mu

lati

ve

Re

turn

s

Low-Beta 30%

U.S. Equity Market


A Q RC A P I T A L


M A N A G E M E N T

II. Value and Momentum Tilts May Help in Stock Selection

Earning the equity premium together with helpful stock selection tilts can improve on

a market-cap portfolio’s performance (but only modest diversifier if long-only)

• Example: Combine one third each in “Market” (U.S. market-cap portfolio), “Value” (top three

deciles of value-weighted B/M-sorted stocks), and “Momentum” (top three deciles of value-

weighted 2-to-12-month Momentum-sorted stocks) portfolios. The combo’s compound

average return for 1927-2011 was 12.2%, exceeding the Market’s 9.5%. (The IR is 0.68 and

SR 0.49.)

9

Source: Ken French’s website, S&P 500 Index and AQR. Market with Value & Momentum Stock Selection Tilts from Ken French’s website using full market universe, no size sorting (unlike HML and UMD

factors). These are not the returns of an actual portfolio and are for illustrative purposes only. Please see important disclosures in the Appendix. Hypothetical performance results have certain inherent limitations,

some of which are disclosed in the Appendix hereto. Past performance is not a guarantee of future results.

Cumulative Total Returns on U.S. Equities With Hypothetical Stock Selection Tilts, 1927 – 2011

0.4

4

40

400

4000

1927 1937 1947 1957 1967 1977 1987 1997 2007

Cu

mu

lati

ve

Re

turn

s

Market with Value & Momentum Stock Selection Tilts

U.S. Equity Market

Outperformance


A Q RC A P I T A L


M A N A G E M E N T

II. Value and Momentum Tilts May Help in Timing (But Less)

Earning the equity premium together with helpful market timing tilts can improve the

“buy&hold” portfolio’s performance (but the risk is concentrated)

• Example: Scaling the S&P equity index position size based on the inverted Shiller P/E ratio

and past-year real stock market momentum boosts the timed portfolio’s compound average

return for 1926-2011 to 11.3%, exceeding the S&P’s 9.8%. (The timed portfolio’s IR is 0.32

and SR 0.47; cf. S&P’s 0.40.)

10

Source: S&P 500 Index, Robert Shiller’s website and AQR. Market with Value & Momentum Timing Tilts scales S&P 500 returns based on the inverted Shiller P/E ratio and past-year changes in price. These are

not the returns of an actual portfolio and are for illustrative purposes only. Please see important disclosures in the Appendix. Hypothetical performance results have certain inherent limitations, some of which are

disclosed in the Appendix hereto. Past performance is not a guarantee of future results.

Cumulative Total Returns on U.S. Equities with Hypothetical Market Timing Tilts, 1926 – 2011

0.4

4

40

400

4000

1926 1936 1946 1956 1966 1976 1986 1996 2006

Cu

mu

lati

ve

Re

turn

s

Market with Value& Momentum Timing Tilts

U.S. Equity Market

Outperformance


A Q RC A P I T A L


M A N A G E M E N T

III. Why Do Many Institutions Choose to Depend On The Equity Premium?

I. Equity Premium




III.Why Do Many Institutions Choose to Depend on the Equity

Premium?

Many mainstream investment models imply very high equity market

correlations. Reasons? Not justified by mean-variance efficiency but by

“4Cs”: conviction, constraints, conventionality, capacity




A Q RC A P I T A L


M A N A G E M E N T

12

III. Why Do Many Institutions Choose to Depend On The Equity Premium?

* For illustration purposes only. Please see important risk disclosures in the Appendix.

The Global 60/40 portfolio consists of the MSCI World Index (60%) and the Barclays Global Aggregate Index (40%) (Hedged to USD). The Endowment Proxy consists of S&P 500 Index (8%), MSCI ACWI

ex-US (7%), MSCI EMG (5%), Barclays Capital Global Aggregate Index hedged to USD (11%) , Barclays Capital Global HY Index hedged to USD (4%), HFRI Fund Weighted Composite Index (26%) as

absolute return proxy, Russell 2500 Value as PE proxy (17%) and FTSE EPRA/NAREIT and S&P GSCI (11% each) as two real asset proxies. Chart above shows 36-month rolling correlations. Broad-based

securities indices are unmanaged and are not subject to fees and expenses typically associated with managed accounts or investment funds. Investments cannot be made directly in an index. Past performance is

not a guarantee of future results.

36-Month Correlation to MSCI World

High market directionality: Correlations with global equities often exceed 0.9

Co

rre

latio

ns

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

Global 60/40

Endowment Proxy

Hedge Fund Index


A Q RC A P I T A L


M A N A G E M E N T

III. Major Investment Models…and an Alternative

13

Wide-Harvesting

Approach

Source: AQR. For illustrative purposes only.

All these mainstream models have high equity market correlations


A Q RC A P I T A L


M A N A G E M E N T

III. Diversify Portfolio Risk Well In Several Perspectives

The Cube: Asset Class, Strategy Style and

Risk Factor Perspectives to Investing Many Institutional Portfolios

Imply a Lopsided Cube

14

These are complementary perspectives

on a portfolio’s risk exposures

Blue and orange sides show investable factors

(static asset classes and dynamic strategies),

green side shows uninvestable underlying factors


For illustrative purposes only.

A Q RC A P I T A L


M A N A G E M E N T

15

A6. Why Are Style Premia Underutilized?

Mean-variance analysis with even heavily discounted historical return inputs would

point to large portfolio weights for diversifying return sources such as alternative beta

premia (compared to long-only asset classes and especially equities)

Yet, many diversifying return sources with historically appealing return potential are

only modestly utilized in many institutional portfolios. Why? “The 4Cs”:

• Conviction: investor uncertainty about the sustainability of non-equity premia

• Constraints: aversion to leverage, shorting and derivatives

• Conventionality: “better to fail conventionally” – Keynes

• Capacity: limitations may apply especially for very large investors

Moreover, the market portfolio of all assets tends to be dominated by equity risk, so

this should also be true for the average investor’s portfolio. More effective risk

diversification cannot be for everyone

III. Why Don’t More Investors Escape Concentrated Equity Risk?


Please read important disclosures in the Appendix.

A Q RC A P I T A L


M A N A G E M E N T

III. Only Equities Can Be Forgiven a Few Bad Years…Or A Decade

To sum up, investors may have several reasons to over-rely on stocks – best conviction

(based on theory and pervasive empirical evidence), embedded leverage,

conventionality, and high capacity

Together these features can enhance investors’ patience and time consistency

CAPM

Everyone’s

Doing It...

Capacity 2:1

Debt : Equity


For illustrative purposes only.

A Q RC A P I T A L


M A N A G E M E N T


I. Equity Premium








IV.Beyond the Equity Premium

Aggressive diversification through risk parity investing and

alternative beta premia


A Q RC A P I T A L


M A N A G E M E N T

Alpha

Alternative Beta Premia

(e.g., style premia)

Market Risk Premia

(e.g., equity premium, term premium)

18

IV. Wide Harvesting From Diverse Return Sources

• Highest Cost (“2 and 20”)

• Lowest Capacity

• Zero-sum game

• Moderate Cost

• Medium Capacity

• Long/short strategies

• Lowest Cost (Index Funds)

• Highest Capacity

• Long-only asset classes

• We believe cost-effectively harvesting many systematic premia is the most reliable way to achieve consistent long-

run returns

• Illiquid investments, thematic betas, tactical timing and ‘star’ managers may help around the margins of this core

A Pyramid of Long-Run Return Sources


A Q RC A P I T A L


M A N A G E M E N T

Equities

Bonds

Cash

Real Estate

Alternatives

IV. Market Risk Premia: Equity Risk Dominates Traditional Portfolios

Equity market directional risk usually dominates traditionally diversified portfolios

Concentration is more apparent when portfolio allocations are measured by risk and not

by dollars

19

By Capital By Risk

Traditional Allocation

Traditional Risk Allocation

Equity Risk

Nominal Interest Rate Risk

Inflation Risk

Credit/Default Risk

Hedge Funds


Inflation Risk

Credit/Default Risk

Public and Private Equity

“By Capital” and “By Risk” allocation charts are for illustrative purposes only. and are intended to illustrate an asset class allocation and corresponding risk allocation/exposure of the typical multi-asset class, or

“traditional” portfolio. The illustrative allocation above does not represent the actual or target allocation of any AQR client account, fund or strategy, or that of any other adviser. “By Risk” allocations are

calculated based on AQR volatility and correlation estimates. No representation or warranty is made as to the reasonableness of the assumptions made or that all assumptions used in calculating risk allocations

have been stated or fully considered. Please see risk disclosures in the Appendix.


A Q RC A P I T A L


M A N A G E M E N T

20

IV. Risk Parity Seeks to Give Better Risk Diversification

Risk Parity Risk Allocation… Traditional Risk Allocation

Equity Risk


Inflation Risk

Equity Risk


Inflation Risk

Risk-balanced combination of several long-only market risk premia can avoid equity

risk concentration

Strategic risk balance is supported by empirical evidence of similar risk-adjusted returns

0.0

0.1

0.2

0.3

0.4

0.5

Stocks Bonds Commodities Equal RiskWeight

Sh

arp

e R

ati

os

…Is Supported By Long-Run Evidence (1971-2013)


* Data from January 1971 – September 2013. Inflation risk historical Sharpe ratio is calculated using commodities return data as Inflation-Protected Securities were not available for the majority of the

observation period. The Equal Risk Weight Strategy is a simulated portfolio, constructed by AQR by allocating risk equally across three asset classes: stocks, bonds and commodities, using the following indices

in strategy construction: MSCI World Index (stocks), Barclays Capital US Government Index and Ibbotson Government Index (before 1976) (bonds), and S&P 500 GSCI Index (commodities). The simulated

portfolio targets an equal amount of volatility from each asset class every month. Realized Sharpe Ratios are based on each asset class/index gross monthly returns in excess of the 3 month T-bill. Broad-based

securities indices are unmanaged and are not subject to fees and expenses typically associated with managed accounts or investment funds. Investments cannot be made directly in an index. Charts are for

illustrative purposes only and are based on AQR volatility and correlation estimates. Exposures are subject to change without notice. Please see important risk disclosures in the Appendix.

A Q RC A P I T A L


M A N A G E M E N T

IV. Style Perspective To Alternative Beta Premia

Style tilts are deviations from market-weighted benchmarks based on certain characteristics or

risk exposures. Long-only style-tilted portfolios are often called smart beta

Style premia are comparable dynamic long/short strategies in liquid asset classes. They are

more generally called alternative beta premia (or exotic betas, etc.)

Alternative beta premia can potentially improve both returns and diversification and thus may

justify a meaningful positive strategic exposure in investor portfolios

We have identified “The Big Four” styles that have historically generated positive long-run

returns in multiple asset class contexts classes:

21

Momentum

Value

Carry

The tendency for an asset’s recent relative performance to continue in the near future

The tendency for relatively cheap assets to outperform relatively expensive ones

The tendency for higher-yielding assets to provide higher returns than lower-yielding assets

Defensive The tendency for lower risk and higher-quality assets to generate higher risk-adjusted returns

Source: AQR. Past performance is not a guarantee of future performance. Please read important disclosures in the Appendix.


A Q RC A P I T A L


M A N A G E M E N T

IV. Style Premia Intuition: Why They Work?

22

Momentum

Value

Carry

• Value securities are “beaten up”, distressed, “unglamorous” or less-favored by investors

• Investors may over-extrapolate growth prospects, resulting in overpricing of growth/glamour

stocks

• Value strategies tend to perform poorly when liquidity dries up and are short a structural break,

and value assets may have greater default risk and tend to co-move

Defensive

• Leverage aversion may explain why low-risk assets offer higher risk-adjusted returns

• Unlevered investors seek high-beta assets for more “bang-for-the-buck”

• Investors overpay for “lottery” characteristics

• High (or low) yields may indicate excess demand for (or supply of) capital

• In currencies, for example, expected capital offsets (appreciation/depreciation) have not

materialized, possibly due to inefficiencies caused by non-profit-seeking participants such as

central banks

• May be compensation for negative skewness and losses in “bad times”, especially in currencies

Behavioral and Risk Based Explanations for Style Persistence

• Securities or investments that have performed relatively well (or poorly) over the past year tend

to continue to perform well (or poorly) over the short term

• May be explained by investor initial under-reaction to news and subsequent herding/continued

over-reaction, and other behavioral biases like the disposition effect

• Momentum securities tend to move together, which may denote a common risk


Source: AQR. Past performance is not a guarantee of future performance. Please read important risk disclosures in the Appendix.

A Q RC A P I T A L


M A N A G E M E N T

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Stocks WithinIndustries

Stocks AcrossIndustries

Equity Indices Bonds Interest Rates Currencies Commodities Composite

Sh

arp

e R

ati

o

Value Momentum Carry Defensive

23

IV. Evidence Across Many Assets

Hypothetical Gross Sharpe Ratios of Long/Short Style Components Across Assets, Jan 1990 – May 2013

The Big-Four style premia “travel well” and have delivered positive long-run returns in stock

selection, in country allocation in several asset classes, etc.

Positive Sharpe ratios for long/short strategies in several liquid asset classes (below)

Diversified composites of style premia in seven asset class contexts had even higher Sharpe ratios

Source: AQR. Above analysis reflects a backtest of theoretical long/short style components based on AQR definitions across identified asset groups, and is for illustrative purposes only and not based on an

actual portfolio AQR manages. The results shown do not include advisory fees or transaction costs; if such fees and expenses were deducted the Sharpe ratios would be lower. Please read performance

disclosures in the Appendix for a description of the investment universe and the allocation methodology used to construct the backtest. Hypothetical data has inherent limitations, some of which are disclosed in

the Appendix hereto. The data presented herein is supplemental to the GIPS® compliant presentation for the Style Premia Composite included in the Appendix.


A Q RC A P I T A L


M A N A G E M E N T

IV. A Directional Style Premium: Trend Following

The examples above emphasized market-neutrality. If directional market exposures are allowed,

trend-following – a directional strategy that invests in a diversified set of liquid futures and

forwards – can be an effective timing approach, essentially a fifth style

Since 1980s, a hypothetical trend-following strategy has delivered positive long-run returns in all

50+ assets studied (below). Hurst-Ooi-Pedersen (2012) extend evidence back to 1903 and show

that a trend-following composite earned positive returns every decade, with a long-run Sharpe

ratio of 1.0 (after estimated trading costs and 2+20% fees)

Works for chasing 1-12 –month returns, not for the common chasing of multi-year returns

24

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Alum

inumBrent O

ilCattleCocoaCoffeeCopperCornCottonCrude O

ilG

as Oil

Gold

Heating O

ilH

ogsN

atural Gas

Nickel

PlatinumSilverSoybeansSoy M

ealSoy O

ilSugarG

asolineW

heatZincA

UD

-NZD

AU

D-U

SDEU

R-JPYEU

R-NO

KEU

R-SEKEU

R-CHF

EUR-G

BPA

UD

-JPYG

BP-USD

EUR-U

SDU

SD-CA

DU

SD-JPY

ASX

SPI 200D

AX

IBEX 35

CAC 40

FTSE/MIB

TOPIX

AEX

FTSE 100S&

P 5003 Y

r Australian Bond

10 Yr A

ustralian Bond2 Y

r Euro -Schatz5 Y

r Euro -Bobl10 Y

r Euro -Bund30 Y

r Euro -Buxl10 Y

r CGB

10 Yr JG

B10 Y

r Long Gilt

2 Yr U

S Treasury Note

5 Yr U

S Treasury Note

10 Yr U

S Treasury Note

30 Yr U

S Treasury Bond

Gro

ss S

harp

e Rat

io

Sharpe Ratio of 12 Month Trend Strategy

Commodities Currencies Equities Fixed Income

Source: Moskowitz, Ooi, and Pedersen (2012) “Time Series Momentum”. Hypothetical data has inherent limitations, some of which are disclosed in the Appendix hereto. Past performance is not a guarantee of

future performance.


Hypothetical Sharpe Ratio of 12 Month Trend Strategy

A Q RC A P I T A L


M A N A G E M E N T

IV. Trend Following As An Empirical Safe Haven?

25

Source: AQR. The Hypothetical Time Series Performance (Trend Following) is a backtest for the time period January 1903–December 2012, net of 2/20 fees and estimated transaction costs; not the

performance of an actual portfolio. The 60/40 portfolio has 60% of the portfolio invested in the S&P 500 Index and 40% invested in U.S, 10-year bonds. The portfolio is rebalanced to the 60/40 weights at the

end of each month, and no fees or transaction costs are subtracted from the portfolio returns. For illustrative purposes only. Please read important disclosures relating to the Time Series Momentum Strategy

(Trend Following) in the Appendix. Hypothetical performance results have certain inherent limitations, some of which are disclosed in the Appendix hereto. Past performance is no guarantee of future results

The main puzzle is not the strong paper returns of trend-following strategies but reconciling them

with the surprisingly consistent risk-reducing characteristics

Ilmanen (2011) showed that a trend-following composite was profitable in 13 of the 15 worst months

for global equities over 25 years. Hurst-Ooi-Pedersen (2012) show below that a trend-following

composite made money in 9 of the 10 worst drawdowns for the U.S. 60/40 portfolio over 110 years

Panic of 1907 World War I Post WWIRecession

GreatDepression

Recession of1937-1938

Stagflation OilCrisis

1987 StockMarket Crash

Dot-comBubble Bursting

GlobalFinancial

Crisis

-100%

-50%

0%

50%

100%

150%

09/1906 -11/1907

11/1916 -12/1917

10/1919 -06/1921

08/1929 -05/1932

02/1937 -03/1938

11/1968 -06/1970

12/1972 -09/1974

08/1987 -11/1987

08/2000 -09/2002

10/2007 -02/2009

Historical Hedging Performance During Portfolio Drawdown

60/40 Portfolio Returns US 10Y Bond Returns Gold Returns Time Series Momentum Returns

Hypothetical Trend Following Performance During Portfolio Drawdowns

Simulated Data, 1903 - 2012


Trend Following

A Q RC A P I T A L


M A N A G E M E N T

26

IV. Low Correlations Can Boost Risk Adjusted Returns

Source: AQR. Above analysis reflects a backtest of the AQR Style Premia Strategy and underlying theoretical long/short style components based on AQR definitions across identified asset groups. Chart is

provided for illustrative purposes only and is not based on an actual portfolio AQR manages. Please see the Appendix for further details on the investment universe and the allocation methodology used to

construct the backtests. Hypothetical data has certain inherent limitations, some of which are disclosed in the Appendix hereto. Broad-based securities indices are unmanaged and are not subject to fees and

expenses typically associated with managed accounts or investment funds. Investments cannot be made directly in an index. All correlations based on monthly data, excess of cash. The data presented herein is

supplemental to the GIPS® compliant presentation for the Style Premia Composite included in the Appendix.

Long/Short Strategies Can Have Lowly Correlated Sources Of Return

Market Risk Premia Alternative Risk Premia

Interest

Rate Inflation Equity Value Momentum Carry Defensive

Trend

Following

Interest Rate

Inflation 0.0

Equity 0.0 0.1

Value 0.0 -0.1 0.1

Momentum 0.1 0.1 0.0 -0.6

Carry 0.0 0.2 0.2 -0.1 0.2

Defensive 0.2 0.0 -0.2 0.0 0.1 0.0

Trend Following 0.2 0.1 0.0 -0.2 0.5 0.1 0.1

0.0 0.1 0.0 -0.1 0.1 0.1 0.0 0.1

Mark

et

Ris

k

Pre

mia

Alt

ern

ati

ve R

isk

Pre

mia

Median


A Q RC A P I T A L


M A N A G E M E N T

27

IV. Hypothetical Performance Across Macro Environments

Long/Short Styles Have Performed More Consistently Than Long-Only Asset Classes

Source: Bloomberg, AQR. These results are based on our models, which may be susceptible

to design decisions or specific to the sample period. Global Equities is the MSCI World

index. Global Bonds is a GDP weighted composite of Australian, German, Canadian,

Japanese, UK and US 10yr government bonds. Commodities is an equal dollar-weighted

index of 24 commodities. Long/Short Style Premia are backtests of style premia as described

herein. Global 60/40 takes 60% Global Equities and 40% Global Bonds. Naïve Global Risk

Parity uses trailing 12-month volatility and long-term correlation assumptions to target equal

risk-contributions from a portfolio of Global Equities, Global Bonds and Commodities.

Simple Style-5 is an equal dollar-weighted composite of the five long/short style premia.

Please see Appendix for more details on the construction of the return series and

macroeconomic environmental indicators. The analysis is based on hypothetical returns gross

of trading costs and fees. Hypothetical performance results have certain inherent limitations,

some of which are disclosed in the Appendix hereto. Past performance is no guarantee of

future results.

Market Risk Premia 1972-2013

Hypothetical Long/Short Style Premia 1972-2013

Simple Portfolios 1972-2013


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IV. Style Premia: How To Harvest?

Strategic Long/Short Multi-Strategy Allocations May Offer Efficient Exposure

1. Strategic or tactical?

We believe the Big Four style premia deserve meaningful strategic (long-run) allocations in many

portfolios. We find limited additional benefits in tactical style timing (unless complex, likely

overfitted rules are used) and fear instability may well induce harmful multi-year return chasing.

2. Long-only tilts or long/short strategies?

A long/short approach seeks to maximize the efficiency and diversifying impact of style

investing. However, investor constraints and capacity concerns may favor long-only approach (or

a combo).

3. Single styles or multi-strategy?

A multi-strategy approach can provide better diversification, reduce transaction costs and fees via

netting, and promote patience (induces less return-chasing than single-strategy approaches).


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Appendices

29

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30

A1. Style Premia Universe Selection

* Exposures and investment universe are subject to change at any time without notice.

Diversified Across Many Asset Groups*

Stock Selection (Within

and Across Industries) Approximately 1500 names across: Europe, Japan, UK, and US

Country Equities Developed: Australia, Canada, European Union, Hong Kong, Japan, Sweden, Switzerland, UK, US

Within Europe: Italy, France, Germany, Netherlands, Spain

Emerging: Brazil, China, India, Russia, South Africa, South Korea, Taiwan

Bonds Australia, Canada, Germany, Japan, UK, US

Interest Rate Futures Australia, Canada, Europe (Euribor), UK, US

Currencies Developed: Australia, Canada, Euro, Japan, New Zealand, Norway, Sweden, Switzerland, UK, US

Emerging: Brazil, India, Mexico, Poland, Russia, Singapore, South Korea, Taiwan, Turkey

Commodities Silver, Copper, Gold, Crude, Brent Oil, Natural Gas, Corn, Soybeans

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A1. Are Illiquidity Premia Overrated?

Illiquidity could be a natural style to add to our list of style premia. Indeed, many investors

skeptical on the “Big-4” take it for granted that they get rewarded if they hold illiquid

investments. Conventional industry studies seem to support them in this faith

Academic surveys by Phalippou (2011), de Jong-Driessen (2013) and Ang (2013) are more

skeptical re empirical evidence for illiquidity premia in many illiquid alternative asset classes.

After adjusting for costs/fees, risks and biases, it is not clear that private asset markets such as

direct real estate or private equity offer higher long-run returns than comparable public markets

This would be puzzling because the normative case seems clear: Investors should get

compensated for holding illiquid investments. Moreover, there is some evidence within liquid

asset classes of positive illiquidity premia

If true, any lack of long-run illiquidity premia may reflect offsetting investor demand for other

characteristics of illiquid investments: smoothed returns and embedded leverage

Data histories on alternatives are too short and biased/problematic to give conclusive answers

(voluntary reporting boosts average returns, overly smooth returns understate portfolio risks)


Please read important disclosures in the Appendix.

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High Costs

32

A1. And It Is Not Just About Smart Return Sources

What Investors

Seek

What They Miss

Source: Penrose, Colorado Chamber of Commerce. http://www.penrosechamber.com/LocalInformation/History.aspx

Portfolio Concentration

Expected Return

Poor Risk Management

Pay Attention To Every Step Of The Investment Process


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A2. Constructing Macro Indicators

Macro Indicators

Our first choice was to decide which macro dimensions are most relevant. We chose economic growth, inflation, real yields, volatility, and illiquidity. Monetary policy was another

candidate; it is closely related to real yields.

We choose to construct macro indicators, or risk factors, mainly based on fundamental economic data, and not based on asset market returns (which are ‘too close’ to the patterns

we try to explain). For example, potential market-based proxies of economic growth include equity market returns, the relative performance of cyclical industries, dividend swaps,

and estimates from cross-sectional regressions of asset returns on growth surprises. This choice brings its own problems, notably timing challenges as macroeconomic data are

backward-looking, published with lags and later revised, while asset prices are clearly forward-looking. The impact of publication lags and the mismatch between backward- and

forward-looking perspectives can be mitigated by using longer windows. Thus, we use contemporaneous annual economic data and asset returns through our analysis (past-year data

with quarterly overlapping observations). Arguably composite growth surprise indices are the best proxies of economic growth news, but such composites are available at best going

back to 1990s. Forecast changes in economist surveys as well as business and consumer confidence surveys may be the next best choices because they are reasonably forward-

looking and timely. In a globalized world, it is not clear whether we should focus only on domestic macro developments, but data constraints make us focus on U.S. data. Finally, it

is not clear how real economic growth ties to expected corporate cash flow growth (e.g., earnings per share) that influence stock prices or to real yields that influence all asset prices

but especially those of bonds.

Each of our macro indicators combines two series, which are first normalized to Z-scores: that is, we subtract a historical mean from each observation and divide by a historical

volatility. We use rolling 10-year windows for means and volatilities when normalizing the last three macro indicators. However, for growth and inflation indicators we use in-

sample 1972-2013 means and volatilities because we do not have long histories of economist forecasts needed to construct the surprise series below. This choice does not seem to

change any major results. When we classify our quarterly 12-month periods into, say, ‘growth up’ and ‘growth down’ periods, we compare actual observations to the median so as

to have an equal number of up and down observations (because we are not trying to create an investable strategy where data should be available for investors in real time, we use the

full sample median).

The underlying series for our growth indicator are the Chicago Fed National Activity Index (CFNAI) and the ‘surprise’ in industrial production growth over the past year. Since

there is no uniquely correct proxy way to capture “growth”; averaging may make the results more robust and signals appropriate humility. CFNAI takes this averaging idea to

extremes as it combines 85 monthly indicators of U.S. economic activity. The other series – the difference between actual annual growth in industrial production and the consensus

economist forecast a year earlier – is narrower but more directly captures the surprise effect in economic developments. We use median forecasts from the Survey of Professional

Forecasters data as published by the Philadelphia Fed. While data surprises a priori have a zero mean, this series has exhibited a downward trend in recent decades, reflecting the

(partly unexpected) relative decline of the U.S. manufacturing sector.

Our inflation indicator is also an average of two normalized series. One series measures the de-trended level of inflation (CPIYOY minus its mean, divided by volatility), while the

other measures the surprise element in realized inflation (CPIYOY minus consensus economist forecast a year earlier).


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A2. Constructing Investment Return Series

Investment Return Series

The investment return series we study include both asset class premia and style premia. The former are long-only returns but expressed in excess returns over the Treasury bill rate.

The latter are long/short returns and scaled to target or realize 10% annual volatility. We subtract no trading costs or fees, which makes a bigger difference for the long/short

strategies.

The main asset class premia we focus on are US equities (proxied by the S&P500 index), US Treasuries (proxied by the constant-maturity 10-year return), and commodities

(proxied by the S&P GSCI index). For robustness, we also studied global equities (MSCI World), global bonds (GDP-weighted average of 10-year government bonds in six

countries), and an equal-weighted composite of 24 commodity futures. In addition, we studied the credit excess returns of investment-grade corporates over duration-matched

Treasuries (Barclays index data since 1973) and TIPS returns (using an in-house proxy for inflation-linked bond performance; the series begins already in 1980, well before the first

TIPS were issued in 1997).

Style premia series are more difficult to compile, especially because we apply these premia in numerous asset classes. To start histories back in 1972, we splice together different

series. Since 1990, we use value, momentum, carry and defensive style premia as described in “Investing With Style” (AQR white paper, 2012). The intuition in the four styles is to

buy assets that are cheap, or recently outperforming, or high-yielding, or boring (low risk) – while selling assets with opposite characteristics. We apply these styles in stock

selection, industry allocation, country allocation in equity, fixed income and currency markets, as well as in commodities.

Briefly, we construct market-neutral long/short portfolios in several asset classes (stocks, bonds, currencies, commodities) based on a few indicators in each style. Besides the

broadest style composites, we also construct separate style premia for global stock selection (GSS) and global asset allocation (GAA). When we create the composite GAA style

premia, we use the same relative risk weights for asset classes as “Investing With Style” (33% equity country allocation, 25% fixed income, 25% currencies, 17% commodities).

However, for GSS we use 50/50 risk weights between stock selection within industries and across industries (to be in line with the common but arguably inefficient practice of

letting across-industry positions matter as much as within-industry positions), and we also use 50/50 risk weights when we combine GSS and GAA style composites. For 1972-

1989, we source value and momentum style returns from “Value and Momentum Everywhere” (Journal of Finance, 2013), defensive style returns from “Betting Against Beta”

(forthcoming in Journal of Financial Economics, 2013), and GSS carry style premium from dividend yield strategy returns in Ken French’s data library. We construct the GAA

carry style premia before 1990 as well as some early histories of GAA value, momentum and defensive styles with AQR in-house backtests.

In addition to the market-neutral “big four” style premia, we use market-directional premia. Trend style applies 12-month trend-following strategy in liquid investments in four

major asset classes (GAA). While the style is nearly uncorrelated with equity markets in the long run, at any point in time it can be directionally long or short. We source trend style

premia from “Time Series Momentum” (Journal of Financial Economics, 2012) and in-house data extension before 1985.

While the GSS style premia proxies we use since 1990 are market (beta) neutral, the value and momentum premia before 1990, and the carry premium throughout, are ‘only’ dollar-

neutral and may contain moderate empirical beta exposures. The defensive style premia are beta-neutral through the whole sample (we buy larger amounts of low-risk investments

than we sell high-risk investments), which means that they are actually not as defensive as the dollar-neutral quality style. (The general lesson is that we need to be precise in

understanding strategy designs. Just as corporate bond positions will have very different market exposures depending on whether they are duration-hedged with Treasuries, market

exposures of style premia will depend on the degree of hedging).


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A3. Disclosures

This document has been provided to you solely for information purposes and does not constitute an offer or solicitation of an offer or any advice or recommendation to purchase any securities or other

financial instruments and may not be construed as such. The factual information set forth herein has been obtained or derived from sources believed to be reliable but it is not necessarily all-inclusive

and is not guaranteed as to its accuracy and is not to be regarded as a representation or warranty, express or implied, as to the information’s accuracy or completeness, nor should the attached

information serve as the basis of any investment decision. This document is intended exclusively for the use of the person to whom it has been delivered and it is not to be reproduced or redistributed

to any other person. This document is subject to further review and revision.

PAST PERFORMANCE IS NOT AN INDICATION OF FUTURE PERFORMANCE.

There is no guarantee, express or implied, that long-term return and/or volatility targets will be achieved. Realized returns and/or volatility may come in higher or lower than expected.

Diversification does not eliminate the risk of experiencing investment losses.

Hypothetical performance results (e.g., quantitative backtests) have many inherent limitations, some of which, but not all, are described herein. No representation is being made that any fund or account will or is

likely to achieve profits or losses similar to those shown herein. In fact, there are frequently sharp differences between hypothetical performance results and the actual results subsequently realized by any

particular trading program. One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial

risk, and no hypothetical trading record can completely account for the impact of financial risk in actual trading. For example, the ability to withstand losses or adhere to a particular trading program in spite of

trading losses are material points which can adversely affect actual trading results. The hypothetical performance results contained herein represent the application of the quantitative models as currently in effect

on the date first written above and there can be no assurance that the models will remain the same in the future or that an application of the current models in the future will produce similar results because the

relevant market and economic conditions that prevailed during the hypothetical performance period will not necessarily recur. There are numerous other factors related to the markets in general or to the

implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results, all of which can adversely affect actual trading results. Discounting

factors may be applied to reduce suspected anomalies. This backtest’s return, for this period, will vary depending on the date it is run. Hypothetical performance results are presented for illustrative purposes only.

The Time Series Momentum Strategy (Trend Following) was constructed with an equal-weighted combination of 1-month, 3-month, and 12-month time series momentum strategies for 59 markets across 4 major

asset classes — 24 commodities, 11 equity indices, 15 bond markets and 9 currency pairs — from January 1903 to June 2012. Since not all markets have return data going back to 1903, we construct the strategies

using the largest number of assets for which return data exist at each point in time. We use futures returns when they are available. Prior to the availability of futures data, we rely on cash index returns financed at

local short rates for each country. Please refer to the A Century Evidence on Trend Following Investing white paper for additional information. Please inquire at AQR for a copy of this paper.

AQR backtests of Value, Momentum, Carry and Defensive theoretical long/short style components are based on monthly returns, undiscounted, gross of fees and transaction costs, excess of a cash rate proxied by

the Merrill Lynch 3-Month T-Bill Index, and scaled to 12% annualized volatility. Each strategy is designed to take long positions in the assets with the strongest style attributes and short positions in the assets

with the weakest style attributes, while seeking to ensure the portfolio is market-neutral. The representative Composite and Style Premia Strategy portfolio is based on the target asset group allocations included

herein, roughly equally risk weighting styles within the asset group, resulting in a style allocation of approximately 32% to Value, 32% to Momentum, 22% to Defensive and 14% to Carry. The AQR backtest of

the Style Premia Strategy is based on monthly returns, net of a 1.5% advisory fee and estimated transaction costs, excess of a cash rate proxied by the Merrill Lynch 3-Month T-Bill Index and heavily discounted

to reflect uncertainty in historical costs and opportunities; targeting 12% annualized volatility. Please see below for a description of the Universe selection.

Stock and Industry Selection: approximately 1,500 stocks across Europe, Japan, U.K. and U.S. Country Equity Indices: Developed Markets: Australia, Canada, Eurozone, Hong Kong, Japan, Sweden,

Switzerland, U.K., U.S. Within Europe: Italy, France, Germany, Netherlands, Spain. Emerging Markets: Brazil, China, India, Russia, South Africa, South Korea, Taiwan. Bond Futures: Australia, Canada,

Germany, Japan, U.K., U.S. Interest Rate Futures: Australia, Canada, Europe (Euribor), U.K. and U.S. Currencies: Developed Markets: Australia, Canada, Euro, Japan, New Zealand, Norway, Sweden,

Switzerland, U.K., U.S. Emerging Markets: Brazil, India, Mexico, Poland, Russia, Singapore, South Korea, Taiwan, Turkey. Commodity Selection: Silver, Copper, Gold, Crude, Brent Oil, Natural Gas, Corn,

Soybeans.

There is a risk of substantial loss associated with trading commodities, futures, options, derivatives and other financial instruments. Before trading, investors should carefully consider their financial position and

risk tolerance to determine if the proposed trading style is appropriate. Investors should realize that when trading futures, commodities, options, derivatives and other financial instruments one could lose the full

balance of their account. It is also possible to lose more than the initial deposit when trading derivatives or using leverage. All funds committed to such a trading strategy should be purely risk capital.

AQR White Papers discussed here are available upon request.


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A3. Disclosures

The MSCI World Index is a free float-adjusted market capitalization weighted index that is designed to measure the equity market performance of developed markets..

The MSCI ACWI Index is a free float-adjusted market capitalization weighted index that is designed to measure the equity market performance of developed and emerging markets. The MSCI ACWI

consists of 45 country indices comprising 24 developed and 21 emerging market country indices.

The MSCI Emerging Markets Index (MSCI EMG) is a free float-adjusted market capitalization index that is designed to measure equity market performance in the global emerging markets.

The Barclays Capital Global Aggregate Bond Index is a broad-based measure of the global investment-grade fixed income markets.

The Barclays Capital Global High Yield Index is a broad-based measure of global high yield fixed-income markets.

The HFRI Fund Weighted Composite Index is a global, equal-weighted index of over 2,000 single-manager funds that report to HFR Database.

The Russell 2500 Value Index measures the performance of those Russell 2500 companies with lower price-to-book ratios and lower forecasted growth values.

The FTSE EPRA/NAREIT Developed Index (formerly named FTSE EPRA/NAREIT Global Real Estate Index) is a global market capitalization weighted index composed of listed real estate.

The S&P GSCI™ is a world production-weighted index composed of the principal physical commodities that are the subject of active, liquid futures markets.

The Standard and Poor’s 500 Index (S&P 500) is market value weighted index consisting of 500 stocks chosen for market size, liquidity, and industry grouping, and is meant to reflect the risk/return

characteristics of the large cap universe.

The NCREIF transaction-based index is based on properties that were in the NCREIF Property Index (NPI) and were sold that quarter.

The Credit Suisse Hedge Fund Index is an asset-weighted hedge fund index.

The Cambridge Associates LLC U.S. Private Equity Index® is based on returns data compiled for U.S. private equity funds (including buyout, growth equity and mezzanine funds) that represent the

majority of institutional capital raised by private equity partnerships formed since 1986.


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AQR Capital Management, LLC

Style Premia Composite*

8/31/12 – 12/31/12

Year Gross Return % Net Return % Benchmark * Number of

Portfolios

Composite Assets

($M)

Total Firm Assets

($M) % of Firm Assets

2012 -1.20 -1.69 0.11 1 6.76 71,122.42 0.00

This presentation cannot be used in a general solicitation or general advertising to offer or sell interest in its Funds. As such, this information cannot be included in any advertisement, article, notice or

other communication published in any newspaper, magazine, or similar media or broadcast over television or radio; and cannot be used in any seminar or meeting whose attendees have been invited by

any general solicitation or general advertising.

Notes:

Firm Information:

AQR is a Connecticut-based investment advisor registered with the Securities and Exchange Commission under the Investment Advisers Act of 1940. AQR conducts trading and investment activities,

specializing in global asset allocation and global stock selection involving a broad range of instruments, including, but not limited to, individual equity and debt securities, currencies, futures,

commodities, fixed income products and other derivative securities.

For purposes of Firm wide compliance and Firm wide total assets, AQR defines the “Firm” as entities controlled by or under common control with AQR (including voting power). The Firm is comprised

of AQR, CNH Partners, LLC (“CNH”) and AQR Re Ltd. (AQR Re).

Upon request AQR will make available a complete list and description of all of Firm composites, as well as additional information regarding policies for valuing portfolios, calculating performance, and

preparing compliant presentations.

Past performance is not an indication of future performance.

Fees: AQR’s asset based fees for portfolios within the composite may range up to 1.50% of assets under management, and are generally billed monthly or quarterly at the commencement of the calendar

month or quarter during which AQR will perform the services to which the fees relate. In addition, AQR funds incur administrative fees and may have a redemption charge of 2% based on gross

redemption proceeds may be charged upon early withdrawals.

Please refer to the Funds’ applicable Prospectus, or the Private Offering Memoranda and AQR’s ADV Part 2A for more information on fees.

A4. Performance Disclosures

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A4. Performance Disclosures

Composite Characteristics: The Style Premia Composite (the “Composite”) was created in September, 2012. Accounts included are designed to produce high risk-adjusted returns while maintaining low-

to-zero correlation to traditional markets. AQR pursues these goals by investing in a combination of different investment strategies that apply quantitative return forecasting models and systematic risk

control methods. The composite benchmark is the Merrill Lynch 3 Month Treasury Bill Index. The index measures the rate of return an investor would realize when purchasing a single US 3 month

treasury bill, holding it for one month, selling it, and rolling it into a newly selected issue at the beginning of the next month. Investments in the composite vary substantially from those in the benchmark.

Accounts included may engage in leverage, derivative, and short transactions. In general, a derivative contract typically involves leverage, i.e., it provides exposure to potential gain or loss from a change

in the level of the market price of a security, currency or commodity (or a basket or index) in a notional amount that exceeds the amount of cash or assets required to establish or maintain the derivative

contract

Consequently, an adverse change in the relevant price level can result in a loss of capital that is more exaggerated than would have resulted from an investment that did not involve the use of leverage

inherent in the derivative contract. Many of the derivative contracts are privately negotiated in the over-the-counter market. These contracts also involve exposure to credit risk since contract performance

depends in part on the financial condition of the counter-party. These transactions are also expected to involve significant transaction costs. The risks inherent to the strategies employed by the Master

Account and the UCITS Fund are set forth in the applicable offering documents and other information provided to potential subscribers.

Additionally, there may be subjective unobservable inputs used in the valuation of certain financial instruments contained in the accounts included.

Calculation Methodology: Valuations and returns are computed and stated in U.S. dollars, and individual portfolios may be revalued monthly or daily depending on the portfolio. Portfolios that are

revalued monthly are also are revalued intra-month when cash flows occur. The firm links returns geometrically to produce an accurate time-weighted rate of return. Composite returns are asset-weighted.

Gross of fees returns are calculated gross of management, administrative, and custodial fees and net of transaction costs. Returns are calculated net of all withholding taxes on foreign dividends. Accruals

for fixed income and equity securities are included in calculations. Net of fees returns are net of model management fees of 1.50%. The dispersion measure is the equal-weighted standard deviation of

accounts in the composite for the entire year. Dispersion is not considered meaningful for periods shorter than one year or for periods during which the composite contains five or fewer accounts for the

full period. **The three-year annualized ex-post standard deviation measure is inapplicable when 36 monthly returns are not available.

Other Disclosures: AQR claims compliance with the Global Investment Performance Standards (GIPS®) and has prepared and presented this report in compliance with the GIPS standards. AQR has been

independently verified for the periods August 1998 through December, 2012. The verification report(s) is/are available upon request. Verification assesses whether (1) the firm has complied with all the

composite construction requirements of the GIPS standards on a firm-wide basis and (2) the firm’s policies and procedures are designed to calculate and present performance in compliance with the GIPS

standards. Verification does not ensure the accuracy of any specific composite presentation.

www.loomissayles.com

BOSTON CHICAGO DETROIT SAN FRANCISCO WASHINGTON DC

One Financial Center Boston, Massachusetts 02111 617 482-2450

EMERGING MARKETS 2014:

A YEAR FOR SELECTIVITY

This presentation is provided for informational purposes only and should not be construed as investment advice. Any

opinions or forecasts contained herein reflect the subjective judgments and assumptions of the authors only and do not

necessarily reflect the views of Loomis, Sayles & Company, L.P. Investment recommendations may be inconsistent with

these opinions. There can be no assurance that developments will transpire as forecasted and actual results will be

different. Data and analysis does not represent the actual or expected future performance of any investment product. We

believe the information, including that obtained from outside sources, to be correct, but we cannot guarantee its accuracy.

The information is subject to change at any time without notice.

14 January 2014

presented by

Peter Marber

Head of Emerging Markets Investments,

Loomis Sayles & Company, L.P.

FOR BSAS CONFERENCE USE ONLY. NOT FOR FURTHER DISTRIBUTION.

1For BSAS use only. Not for further distribution.

three developments to watch in 20141. Elections

• South Africa and India (parliamentary), Brazil and Turkey (presidential), Indonesia (both),

several others

2. Tapering and Interest rates

• How fast, how much?

3. Normalization of growth?

• Which countries have reformed and will adapt better to the

new global environment?

Go beyond EM indices

• Index orientation limits EM investing

• Look at 2013

This information is provided for informational purposes only and should not be construed as investment advice. Any opinions or forecasts contained herein

reflect the subjective judgments and assumptions of the authors only and do not necessarily reflect the views of Loomis, Sayles & Company, L.P.

Investment recommendations may be inconsistent with these opinions.


external debt

OUR VIEWS

External debt under some pressure due to slow rise in interest rates

• 50 bps. of interest rates rise?

• Investors should consider target duration level

Headline sovereign spread averages obscure opportunities

• IG portion is near pre-crisis tights

• HY situations dicey (Ukr, Ven, Arg)

Investors should consider corporate credit

• IG paying 70-110bps over comps

• BB and B 100-250 bps over





hard currency indices mask returns

MORE THAN 1800 BPS POINTS DIFFERENCE IN SUBINDICES IN 2013

2013 returns varied wildly depending on corporate vs. sovereign, grade or high yield (and

rating segments), EM or frontier markets

Source: Bloomberg, data from 1/2/2013 through 12/20/2013.Information obtained from outside sources is believed to be correct, but we cannot guarantee its accuracy. It cannot be copied, reproduced or redistributed without authorization.


local currency and bondsDollar strength continuing?

• 50 bps. of interest rates rise?

• Declining US trade deficit?

We are seeing investors start to play select EM currencies against all major currencies

• Mexican peso vs. US dollar

• Hungarian forint vs. euro

• South Korean won vs. Japanese yen

Frontier markets?

• Less correlated to major markets

• Uganda, Uruguay?





local debt indices also had large

variations in 2013COUNTRY VARIATIONS WITHIN INDICES EVEN LARGER

Source: Bloomberg, data from 12/20/2012 through 12/20/2013. We cannot guarantee the accuracy of third-party data.

Information obtained from outside sources is believed to be correct, but we cannot guarantee its accuracy. It cannot be copied, reproduced or redistributed without authorization.


MSCI EM equity index, 1989-2012As of April 30 2013, Commonly followed index is constantly evolving: China, Korea and Taiwan

comprise 43+%

Source: BNP Paribas, MSCI, Factset, as of April 30, 2013.

Indexes are unmanaged and do not incur fees. It is not possible to invest directly in an index.


equities

OUR VIEWS

Can EM rebound?

• P/Es very cheap 10x vs 15x in developed markets

• Divergence for the last 16 months

Selectively target large markets – not indices

• Russia, China

• Poland

• Mexico

Frontier markets?

• Less correlated to majors

• Top 10 stock markets in 2013 were frontier markets




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