globalmarketperspective expected, securities with high liquidity (easy to sell when de-risking) and...

SEPTEMBER 2015

Global Market Perspective

Current Positioning

Position Trend Overweight Underweight/Short

Equities – Flat Japan, Select EM Canada, US

Comments and Recent Activity: Absence of traditional excesses that mark end of cycle; profit margins to sustain. Modest improvements in credit flows improve Europe, Japan outlook. High volatility, valuation drove underweight

Sovereign Bonds 0 Flat US, Australia, Canada Japan, Europe

Comments: Low real rates, no exposure to Japanese bonds, overweight CAN, US, AUS sovereigns for higher yields

IG Credit 0/+ Flat Japan

HY Credit 0 Up

Comments: EM more attractive, but selectivity is key; added on improved valuation

Petroleum + Down Long-dated futures, oil services

Comments: Supply growth decelerates as capex cuts offset gains from technology. Bought put spreads

Industrial Metals 0 Flat

Comments: Attractive value; slow recovery

Precious Metals 0 Flat

Comments: Increased attractiveness due to decline in real yields. Gold-miner equities increasingly attractive

Equity Style Flat GARP Style, Value Momentum, High Risk

Comments: Quality growth stocks, with attractive free-cash-flow yield

Currencies Flat USD, High-Yield EM EUR, GBP, AUD �Highest-conviction ideas/active positions – / 0 / + Refer to underweight, neutral and

overweight positions vs. strategic allocation

As of August 31, 2015Source: AB

How We Are Positioned and Where the Opportunities AreDuring August, the sell-off in risk assets moved decidedly beyond commodities andemerging markets. There was also a notable lack of differentiation among countries,sectors and even asset classes. For example, equity returns in virtually all regions andsectors fell between 5% and 8%, while credit markets declined by 1% to 2%(Performance, page 8).

Highlights

n During August, the sell-off in riskassets moved beyond commoditiesand emerging markets; incomestrategies and safety assets postedpositive returns.

n We reduced exposure to equities andcredit in risk-aware strategies, largelydue to higher volatility. In otherportfolios, we added exposures tovalue assets.

n There’s still some skepticism about theeffectiveness of adding value throughtactical factor allocation; historicalevidence suggests otherwise.

n Factor positioning is increasinglydefensive in the US; we’re takingadvantage of value in Japan andEurope. Momentum is broadlyattractive, but fairly crowded and risky.

Vadim ZlotnikovChief Market Strategist &Co-Head—Multi-Asset Solutions

This publication offers investors a systematic,

comprehensive assessment of the global

economy and the world’s capital markets. Using

a short horizon, we analyze current and

emerging trends, risks and opportunities across

countries, regions and asset classes, providing

perspective on the global investing landscape

investors face today. These materials present

the viewpoint of the Multi-Asset team and do

not necessarily represent the views of other AB

portfolio-management teams.

(continued)

Making the Case for Factor RotationAugust saw a sell-off consistent with a broad-based de-risking, with value strategies particularly hurt; we reduced risk

exposure in risk-aware strategies during the month. In this edition, we address skepticism about the effectiveness of strate-

gies that seek to add value by tactically rotating factors.

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At the same time, income strategies and safety assets (includingsovereign bonds, low-volatility equities and high-dividend-yieldequities) posted positive returns. Energy rebounded slightly fromits sharp decline in July, but remains toward the low end of itsfive-year trading range.

The nature of the sell-off is consistent with the broad-basedde-risking we discussed in the June 2015 Global MarketPerspective. There’s substantial, though anecdotal, evidence thatmany risk-aware strategies (risk parity, volatility-capped variableannuities) and hedged equities took down their risk as volatilityspiked. As expected, securities with high liquidity (easy to sellwhen de-risking) and with a large presence in cap-weightedbenchmarks exhibited some of the largest declines. Forexample, Apple, Pfizer, Wal-Mart Stores and IBM had marketbetas well under 1.0, but they declined by 3% to 5% morethan the market during the past few weeks.

The euro and yen strengthened versus the US dollar, while mostother currencies fell. It’s tempting to attribute the currencymoves to the relatively stronger economic data from thoseregions, but we believe some of the gain stems from thede-risking of the fairly crowded “long US dollar” trade. As wediscussed last month, we remain overweight both Japaneseequities and the yen, while we’re materially underweightJapanese bonds. These positions had a fairly neutral impact onthe different portfolios. Japanese equities underperformed by1% to 1.5%, and a slight increase in Japanese governmentbonds was offset by currency gains.

During August, we reduced exposure to equities and credit inrisk-aware strategies to an underweight position from a largelyneutral stance in July (Current Positioning, page 1). The bulk ofthe decision reflects a significant pickup in volatility (or uncer-tainty) associated with the potential for China contagion, higherUS interest rates and a collapse in commodities. In portfoliosthat place less emphasis on reducing drawdowns, we addedenergy beta and selectively increased exposure to attractivelyvalued cyclical stocks. We also reduced duration in fixed incomegiven its run-up, shifting the funds into cash.

More generally, our quantitative models, designed to captureexpected return rather than risk characteristics, are identifyingfew large mispricing opportunities. Equities are modestly

Display 1

Information Ratio of Individual Equity Factor Strategies

Capital Use

Current Value

Deep Value Momentum Profitability Quality

US

2003–2007 0.1 1.0 1.1 0.4 0.5 0.3

2008–2015 0.3 0.3 0.1 0.4 0.4 –0.1

Difference 0.2 –0.7 –0.9 –0.1 –0.1 –0.4

Global

2003–2007 0.7 2.1 0.8 1.8 0.1 1.3

2008–2015 0.7 1.1 –0.1 0.7 1.2 0.9

Difference 0.0 –1.0 –0.8 –1.1 1.2 –0.4

As of August 31, 2015Source: Bloomberg, S&P Compustat, Worldscope and AB

Display 2

Potential Benefit from Factor Timing Assuming PerfectHindsight: Information Ratios

Increase in Efficacy Due to

Timing

All 6Factors

Removing Bottom 1 Factor

Top 3 Factors

Avoid Worst Factor

Choose Best 3 Factors

1990–2002 1.1 1.6 2.1 42% 86%

2003–2007 1.2 1.7 2.4 38% 96%

2008–2015 1.0 1.5 2.2 56% 124%


attractive, with a preference for Japan, and bonds are alsosomewhat favored. The positive view of both asset classes isdriven by a decline in oil prices and break-even inflation rates .On the margin, a long US bonds/short Japanese governmentbonds position seems attractive.

Emerging-market equities and currencies suffered dramaticdeclines, which significantly improved their attractiveness interms of valuations. However, history argues against trying to“catch a falling knife,” and the negative momentum of these

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assets detracts from their attractiveness score. In other words,our models suggest delaying an increase in emerging-marketassets until the sell-off has run its course and prices stabilize.

Testing the Effectiveness of Factor RotationThe primary purpose of the Global Market Perspective report isto highlight the cross-asset opportunities we see in the marketand provide an update on the actions we’re taking in theportfolios we manage. Our method of assessing these opportu-nities is through a lens of risk premiums and the capitalallocation according to those premiums—this is reflected in theway we conduct research, develop new solutions and managestrategies. For example, in the July 2015 issue, we describedhow we design portfolios to extract different multi-asset riskpremiums, as well as our approach to refining strategic andtactical allocation.

Our discussions with clients suggest that many of them remainskeptical that money managers can add value through tacticalallocation to different risk premiums throughout the businesscycle. Many institutional investors are growing more acceptingof the idea that some systematic deviations from a capitaliza-tion-weighted benchmark can generate excess returns, but theystill view the notion that returns can be further enhanced bytilting a portfolio toward different systematic exposuresthroughout the business cycle as a somewhat speculative one.

It’s interesting that even those clients who use more advancedtechniques are willing to use tactical “market timing” when theobjective is to reduce losses or protect against drawdowns, butthey doubt that tactical allocation can increase the returns of asystematic strategy.

In the end, the best proof is how a “live” strategy actuallyperforms. In this report, we detail our capital allocationapproach among different equity risk premiums, which we’vedeployed in various mandates over the past four years. Ourhope is to provide a foundation for thinking about desirablestyle tilts. Large institutional clients can use this information toimplement tilts among existing style-intense managers, or aspart of a risk-management framework, by ensuring they haveexposure to the most “desirable” styles at different points intime.

The effectiveness of many “traditional” equity factor strategieshas declined, but the opportunity to add value through factortiming remains the same.

As we’ve discussed in prior reports, the risk-adjusted returns formost traditional equity factors have deteriorated since 2007. Forboth global and US factors, the deterioration was mostpronounced in value strategies, while the capital-use andprofitability factors fared somewhat better (Display 1, page 2).It’s easy to hypothesize about the reasons for the deterioration:

Display 3

Annualized Excess Return of Equal-Weighted Strategies

All6 Factors

Removing Bottom 1 Factor

Top3 Factors

1990–2002 3.9% 6.0% 10.9%

2003–2007 3.5 5.3 8.2

2008–2015 2.4 4.4 7.5


Display 4

Framework to Drive Capital Allocation Among EquityFactors

Horizon

Short� Momentum� Quality

US CanadaGreatBritain

Europeex UK

Japan AU/NZ

Expected Risk and Return

Target Excess Return: 1.5%–3.0% p.a. alphaTarget Risk: 2.0%–5.0% tracking error

Regional Consideration

Medium� Capital use� Current value

Long� Profitability� Deep value

SizeBetaRisk

Persistent Return Episodic Return

What Type of Factors Should Work?� Business cycle

Have They Started to Work?

Is the Opportunity Large?

Have the Others Figured This Out?

� Momentum� Valuation� Dispersion� Crowding


4

uncertain growth (bad for value, good for profitability), highliquidity and low interest rates (good for capital use). However,there’s no guarantee that investors could have foreseen thechanges in effectiveness and taken advantage of them. Leavingaside practicality, the question is: has trying to time theallocation to different factors become more or less important?In other words, is it more important to try?

To keep the back-test simple, we examined how perfecthindsight and the ability to rebalance a factor allocationquarterly improved effectiveness, and we limited the analysis tothe US. We compared three scenarios. First, we looked at thereturns from an equal-weighted allocation among factors,rebalanced monthly (we refer to this as “equal weighted”).Second, we assumed perfect hindsight and removed the onefactor that had the worst performance over the quarter, equallyweighting the rest. This “risk managed” approach is a proxy forwhat may be possible if the objective is to manage portfolio riskby removing the riskiest, least attractive factor. And third, weassumed the ability to identify and invest in the top three of thesix factors. This is a proxy for the “ultimate” return-seekingstrategy.

Our analysis shows that the risk-managed factor strategy wouldhave improved the information ratio by 0.5, and the ultimatefactor strategy would have improved it by 1.0 to 1.2 across thethree time periods (Display 2, page 2). Obviously, this would beimpossible to achieve in an actual product, but it does highlightthat the potential to add value through factor timing haspersisted despite the erosion in individual factor efficacy. Thismeans that the potential to enhance performance throughfactor timing has actually increased as a percentage of totalperformance. It’s important to note that using a smaller numberof factors actually increased portfolio volatility, but this was fullyoffset by much stronger returns (Display 3, page 3). In otherwords, there was full compensation for giving up somediversification benefit.

A Comprehensive Factor-Rotation ProcessHere’s an overview of our approach to factor timing, which hasfour key components (Display 4, page 3):

1) What type of factors should work? Using OECD leadingindicators, we assess where we are in the business cycle in each

Display 6

Information Ratios for Deep-Value Long-Only StrategiesVis-à-Vis Business Cycle Phases

OECD Leading Indicator

Level Trend US Canada UKEU exUK

Asiaex

Japan Japan AU/NZ

Expansion Accelerating 0.7 –0.1 0.6 0.7 0.8 1.4 0.3

Expansion Decelerating 0.2 0.1 0.7 –0.9 — — 0.5

Contraction Accelerating 0.6 –0.6 1.2 –0.1 1.2 3.3 1.5

Contraction Decelerating 0.3 0.7 2.5 0.8 0.3 0.1 1.8

As of August 31, 2015Source: Bloomberg, OECD, S&P Compustat, Worldscope and AB

Display 5

Average Sector Exposures for the MSCI World, andDifferent “Value” Index Constructs

SectorMSCI World

Top Quintile*

MSCI Value

“Pure” Value*

Financials 22% 32% 33% 18%

Energy/Commodities 16 20 18 18

Healthcare/Tech/Staples 33 16 22 33

Consumer Discretionary 11 14 7 12

Capital Equipment/Defense 11 10 9 11

Telecom/Utilities 8 9 11 8

From January 2003 to July 2015*Top quintile is constructed by aggregating 20% of the stocks within each region that aremost attractive on the basis of price/book and price/earnings. “Pure” value is based onan optimized construction of a value factor that seeks to minimize known value riskexposures, and relies on a sector-relative calculation of price/book and price/earningsvalue exposures.Source: Bloomberg, MSCI, S&P Compustat, Worldscope and AB

region. We divide the cycle into four traditional phases:contraction, expansion, accelerating growth, and deceleratinggrowth. We then identify the styles that should generateoutperformance in the current setting based on history.

5

2) Has the factor started to work? This assessment simply usestrailing nine-month momentum. The intent is to avoid incurringlosses when the business cycle provides an incomplete orerroneous signal.

3) Is the opportunity large? We evaluate this through a simplerelative valuation of the most attractive stocks for a particularstyle or factor. If the attractive cohort is very expensive versushistory, it tends to signal low opportunity and higher risk.

4) Have others figured this out? We use a proprietary frame-work for assessing crowding at the security level. We apply it inboth factor construction and factor selection. In factor construc-tion, we seek to avoid excessive risk exposure to crowded stocksrelative to the benchmark. In factor selection, crowdingcontributes to our sizing of the exposure, since crowded factorstend to be more risky.

Factor timing, or factor rotation, strategies must explicitly takeinto account the way individual factors are constructed. Youcan’t simply develop generic strategies for timing styles orfactors and apply them to active management, passive indexesor “pure” factors. Why is that the case? Different factorimplementations carry dramatically different unintended (ornonfactor) risk exposures.

For example, we compare the sector weights that would resultfrom using each of three implementations of the value factor:1) selecting the most attractive quintile of stocks based onprice/book value and price/earnings ratios; 2) using the MSCIValue factor index; and 3) a “pure” implementation using a riskmodel to neutralize nonfactor systematic risks.

As shown in Display 5, page 4, these implementations wouldresult in dramatically different sector weights today. Failing totake these differences into account in a factor-timing modelcould have dire implications for outcomes. In the rest of thereport, we’ll focus on the results obtained using the exposuresfrom the “pure” factor implementation.

Applying Our Framework1) Business cycle. As shown in Display 4, page 3, the startingpoint for allocating capital among the different factors is thebusiness cycle, as defined by OECD leading economic indicators

Display 8

Equity Factor Strategy Performance: Impact of Momentumfor Timing

Equal Weighting

All 6 FactorsTop 3 Factorsby Momentum

Return 11.75% 12.94%

Volatility 14.5% 14.8%

Information Ratio 1.15 1.26

From January 2003 to August 31, 2015Source: Bloomberg, S&P Compustat, Worldscope and AB

(LEI). Since we’re also allocating regionally, we need to incorpo-rate regional LEIs, because business cycles aren’t synchronized.Display 6, page 4, highlights the effectiveness of the deep-valuetheme, as captured by the information ratio, for different regionsand phases of the business cycle. There are some commonalitiesacross regions, such as a broad weakness in performance duringthe early stages of economic deceleration (expansion at adecelerating rate) and a strong rebound in the early stages of therecovery. This has direct implications for the region(s) we selectto capture the deep-value premium at any given point in time.

Display 7

Information Ratios for Capital Value Long-Only StrategiesVis-à-Vis Business Cycle Phases

OECD Leading Indicator

Level Trend US Canada UKEU exUK

Asia ex

Japan Japan AU/NZ

Expansion Accelerating 0.5 0.2 0.4 0.5 0.9 0.9 0.3

Expansion Decelerating 0.2 0.3 1.0 –0.1 –0.4 0.9 0.3

Contraction Accelerating 0.4 1.0 0.8 1.6 1.2 2.3 0.8

Contraction Decelerating 0.6 0.0 3.0 2.1 1.6 1.1 –0.3

As of August 31, 2015Source: Bloomberg, OECD, S&P Compustat, Worldscope and AB

6

In Display 7, page 5, we show the effectiveness of the capital-use factor, which generally seeks to overweight companies withhigh dividend yields and high share-repurchase yields. In mostregions, capital use is a valuable diversification counterpart todeep value in the early stages of economic contraction, asinvestors begin to discount monetary stimulus. Empiricalevidence argues against sourcing capital-use exposure inAustralia/New Zealand, where it rarely delivers favorable returns.This framework is a useful starting point for assessing howtactical allocation among factors should deviate from thestrategic position.

2) Factor momentum. We look at recent factor performance ineach region to assess whether the factor has started to workand whether that performance pattern is likely to persist. On astand-alone basis, we find that momentum is only of limitedeffectiveness, because the return improvement is somewhatoffset by higher volatility (Display 8, page 5). In general, factormomentum has the greatest predictive power when used inconjunction with the business cycle and/or valuation metrics, asin our framework.

3) Factor valuation and dispersion. Our factor construction isdesigned to make sure that the overall portfolio’s valuation isessentially in line with that of the overall benchmark (except forvalue factors, where deviation from the benchmark is theultimate goal). In other words, if we look at the aggregatevaluation multiples of our momentum and profitability factorsover time, they should be very similar to those of the overallmarket.

That’s why we define valuation somewhat differently. Wecalculate the valuation of the top quintile of stocks based on aspecific factor versus the valuation of the overall market. Then,we compare that spread to historical trends. Selecting factorsbased on valuation alone has only limited effectiveness. Wefound that avoiding the most expensive (least attractive) factorsreduces portfolio drawdown, but limiting the universe to themost attractively valued exposures didn’t help or hurt perfor-mance. The factors that are the most overvalued relative tohistory are shown in Display 9. At this point, we use valuation asan input to make a qualitative judgment and in products wheredrawdown protection is an explicit consideration.

4) Crowding. As we’ve discussed previously, we’ve developed aproprietary definition of crowding at the stock level. It capturesbroad-based investor optimism (or pessimism in the case of theleast crowded) as reflected in ownership, risk-taking, long-termperformance, and expectations data.

Display 10 shows the performance of the most crowded versusthe least crowded stocks on a global basis. On average, the

Display 9

Sector-Neutral Factor Spreads (Top Quintile* MinusBenchmark)

US Canada UKEU

ex UKAsia ex Japan Japan AU/NZ

Capital Use

Current Value

Deep Value

Momentum

Profitability

Quality

Beta

Risk

Size

As of August 31, 2015*Beta = high beta; Risk = high risk; Size = small-capGreen = expensive vs. history; teal = cheap vs. historySource: S&P Compustat, Worldscope and AB

Display 10

Crowded vs. Uncrowded Stocks: One-Year Rolling Returns(Region Neutral)

–30%

–20%

–10%

0%

10%

20%

30%

99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14

Percent

Crowded Uncrowded

Ann. Return –0.7% 0.0%Sharpe –0.13 0.00

Crowded

Uncrowded

Through August 31, 2015Source: Bloomberg and AB

7

Display 11

Sector-Neutral Most Attractive* Quintile Crowding

US Canada UKEU

ex UKAsia ex Japan Japan AU/NZ

Capital Use

Current Value

Deep Value

Momentum

Profitability

Quality

Beta

Risk

Size

As of August 31, 2015*Beta = high beta; Risk = high risk; Size = small-capGreen = most crowded relative to history; teal = least crowded relative to historySource: S&P Compustat, Worldscope and AB

Display 12

Trailing 12-Month Returns and Most Attractive FactorExposures by Region

CapitalUse

Current Value

DeepValue Momentum Profitability Quality

US –4.8% –0.2% –8.8% 9.3% –0.5% 1.4%

EU ex UK –0.9 –0.8 –1.5 7.1 1.3 1.3

Canada –1.4 1.0 1.0 –1.7 1.8 9.8

UK 7.3 –1.2 0.4 4.8 –1.2 1.8

Japan 14.4 2.3 2.3 –0.3 9.2 –6.9

Asia ex Japan –1.6 –3.4 5.5 5.9 –2.6 –2.7

AU/NZ –2.6 –6.3 0.2 3.4 –1.7 3.3

As of August 31, 2015Teal = most attractive todaySource: Bloomberg, S&P Compustat, Worldscope and AB

another alpha factor. We’ve highlighted some of the most andleast crowded exposures today (Display 11).

What Does Factor Analysis Tell Us Today?Putting it all together, we can determine which factors arecurrently preferred; we show them in Display 12 along withtheir trailing 12-month returns. Positioning in the US andAustralia/New Zealand reflects the anticipation of a slowingexpansion, while exposures in Europe ex UK and Japan arebased on stable to improving economic growth. Canada andAsia ex Japan exposures reflect defensive positioning. Theseexposures haven’t changed significantly over the past quarter.

relative performance of the most and least crowded stocks isvery close to zero. The most and least crowded stocks also havevery negative correlation and offer opportunity for diversifica-tion. And crowded stocks experience significantly higherdrawdowns around market downturns, while the least crowdedoutperform. So, we see crowding as an important considerationin managing risk and achieving diversification, rather than

8

Past performance is no guarantee of future results.Please refer to Glossary on page 16 for a description of return calculations and sources.As of August 31, 2015Source: AB

Equity Returns by Region

1 Mo. 3 Mo. 1 Yr. 3 Yr.3-Yr.

Percentile

Canada -4.3% -6.8% -8.4% 8.2% 47%

US -6.1 -6.2 -0.1 13.7 77

Japan -7.9 -9.2 21.5 30.0 91

UK -6.1 -9.9 -5.9 6.5 27

Australia -8.2 -9.0 -3.7 11.2 62

Global -6.6 -7.7 0.6 12.9 73

DM -6.7 -7.1 1.9 14.0 68

Asia-Pac ex Japan -9.5 -11.6 -5.9 9.1 61

EU ex UK -7.8 -7.1 8.2 14.7 76

EM -6.5 -12.6 -9.5 4.1 26

LatAm -5.5 -7.3 -16.6 -0.5 5

EU & MidEast -3.5 -3.8 -4.1 1.0 36

Asia -7.5 -15.8 -9.3 5.1 26

Far East -7.8 -17.3 -10.6 3.9 18

Bond Returns by Region

1 Mo. 3 Mo. 1 Yr. 3 Yr.3-Yr.

Percentile

Canada -0.1% 2.1% 9.7% 7.7% 4%

US 0.0 0.0 2.3 0.9 4

Japan 0.3 0.8 4.4 4.9 1

UK 0.6 2.1 16.2 10.2 16

Australia 0.7 2.2 10.6 7.1 3

DM 0.0 0.0 2.6 1.9 0

Asia-Pac ex Japan 0.3 0.3 3.1 1.4 3

Eurozone -0.8 -1.1 2.2 4.7 18

EU ex UK -0.6 -0.9 3.0 4.4 12

EM 0.1 0.0 2.6 2.1 2

Global Treasury -0.2 -0.2 2.9 3.2 6

Equity Global Sector Returns

1 Mo. 3 Mo. 1 Yr. 3 Yr.3-Yr.

Percentile

Energy -5.9% -14.8% -30.5% -5.1% 13%

Materials -7.1 -15.4 -14.7 -0.5 38

Industrials -6.3 -9.1 -1.1 12.2 73

Consumer Discretionary -7.2 -6.2 8.4 17.9 88

Consumer Staples -6.2 -4.0 5.3 9.2 58

Healthcare -7.3 -4.7 13.0 21.2 93

Financials -7.9 -8.4 -0.8 12.6 77

Technology -6.2 -9.3 0.4 12.3 80

Telecom -5.1 -5.3 1.0 6.9 70

Utilities -5.6 -7.5 -4.3 5.0 69

Bond Strategy Returns

1 Mo. 3 Mo. 1 Yr. 3 Yr.3-Yr.

Percentile

Global Inv. Grade -0.5% -1.3% -5.0% 1.3% 5%

Global High Yield -1.2 -2.7 -4.7 4.8 17

EM Inv. Grade -1.3 -2.6 -1.3 1.6 3

EM High Yield -1.1 -2.3 -3.8 3.3 3

Global Asset Backed -0.3 0.1 -1.7 2.0 6

Duration -0.2 -0.3 2.3 3.2 70

FI Carry -0.3 -1.2 0.8 0.3 0

Commodities Spot Returns

1 Mo. 3 Mo. 1 Yr. 3 Yr.3-Yr.

Percentile

Dow Jones–UBS -0.9% -9.9% -28.1% -14.6% 0%

Natural Gas -2.7 -1.5 -43.1 -15.2 50

Industrial Metals -2.8 -14.3 -29.3 -11.5 12

Agriculture -3.9 -3.6 -19.4 -17.5 7

WTI Crude 2.1 -21.3 -54.2 -22.4 4

Brent Crude 2.7 -18.8 -53.8 -22.4 0

Gold Spot 3.6 -4.7 -11.8 -12.5 2

Spot Currency Returns

1 Mo. 3 Mo. 1 Yr. 3 Yr.3-Yr.

Percentile

JPY 2.2% 2.4% -14.1% -13.5% 1%

EUR 2.1 2.0 -14.6 -3.8 29

GBP -1.8 0.4 -7.5 -1.1 45

CAD -0.4 -5.2 -17.2 -9.1 0

AUD -2.7 -7.0 -23.8 -11.7 1

CHF -0.1 -2.8 -5.1 -0.4 29

NOK -1.2 -6.1 -25.2 -11.2 5

CNY -2.6 -2.8 -3.6 -0.1 40

USD -0.4 -0.1 9.9 3.8 85

Performance

Broad Sell-Off in Equities, Credits; Bonds, Energy Up

Equity Risk Premium Returns

1 Mo. 3 Mo. 1 Yr. 3 Yr.3-Yr.

Percentile

Value -0.4% -1.2% -2.8% 2.1% 0%

Growth -1.4 0.0 1.8 1.6 16

Income 0.8 0.8 2.0 1.2 46

High Risk -0.1 -3.1 -2.8 2.9 73

High Beta -1.2 -3.0 -5.3 -0.4 18

MN Quant -0.3 -0.9 -0.6 1.6 1

9

Attractiveness

Highest Conviction: Overweight Japan Equities, Underweight JGBs

Equities, Credit Modestly Attractive; Favor Japan Equities and US Bonds as DiversifierAsset-Class Attractiveness

Global Assets(3)

DM & EMEquity Regions

(1)IG & HY CreditRegions (3)

DM BondRegions (1, 4)

DM & EMCurrencies (2)

–3–2–1012

DM Equity

DM Bonds

IG Credit

HY Credit

AxJ

CAN

ExU

JPN UKUS

EMLATAM

EMEA

EMAsia

US IG

ExU IG

US HY

ExU HY

AxJ

CAN

ExU

JPN UKUS

AUD

CAD

CHF

EUR

GBP

JPY

NOK

NZD SEK

USD EM

LATAM

EMEA

EMAsia

Petroleum

Ind Metals

Prec Metals

Z Score

Commodity Sectors


Tight Spreads, but Yield High in EM, GermanyEquities (Region)

0

20

40

60

80

100

0

2

4

6

8

10Current Level (Left Scale)Percentile

Earnings Yield (Percent) Percentile vs. H

istory

Through August 31, 2015. Forward earnings yields for all MSCI region andcountry local indices (since 1970 or earliest available after that).Source: MSCI and AB

Favor Carry: US/UK Long vs. Germany/New Zealand ShortBonds (Slope)

0

25

50

75

100

0

1

2

3

4

Current Level (Left Scale)

Bon

d-Yield Slope

(Per

cent

)

Percentile Percentile vs. History

Through August 31, 2015. Slope is the difference in the yields of the 10-year andthree-month bonds, using AB proprietary data (since 1950 or earliest available afterthat).Source: AB

High Currency Carry in CNY, AUDCurrency

0

20

40

60

80

100

–1

0

1

2

3

4

EUR-Germany

JPY GBP CAD AUD CHF NOK CNY

Current Level (Left Scale)

Percentile

Percentile vs. History

Interest-Rate Differential (Percent)

Through August 31, 2015. Interest-rate differential vs. the USD for each currencyusing AB proprietary data (since 1950 or earliest available after that).Source: AB

Past performance is no guarantee of future results. See Glossary for notes and commentary.

1

2 3

5Diversified Factor Exposure PreferredGlobal Theme Allocations

0%

20%

40%

60%

80%

100%

US EU Japan Asia exJapan

Australia

Growth

Percent

Value

Small-Cap/High Risk

Income/Stability


4

10

Solid Employment Gains, but Weak ProductionRecent Growth and Trends

AU/NZ

Canada

–3.0

–2.5

–2.0

–1.5

–1.0

–0.5

0.0

0.5

1.0

–0.4–0.3–0.2–0.10.0

Weak, Deteriorating

Growth

Strong, Improving Growth

Impr

oving

Fund

amen

tals

Det

eriora

ting

Fund

amen

tals

Asia exJapan

Change in Unemployment (Percent)

US

Japan

EU ex UK

EM

Germany DM

UK

As of August 31, 2015Source: Haver Analytics and AB

Growth

Outside of Japan, Revisions Remain Negative, Even as Output SurprisesRobust


Consumer Spending and PMI Remain LacklusterConsumer Spending Trends and PMI

AU/NZ

Canada

UK

EU ex UK

Global

Asia ex Japan

–0.2

0.0

0.2

0.4

0.6

0.8

–1.5 –1.0 –0.5 0.0 0.5

Change in PMI: Z Score

EPS Revisions of Consumer Cyclicals: Z Score

US

Japan


Strong Dollar Hurts US Sales; Rest OKTTM YoY Sales Growth

–8–6–4–202468

MSC

I ACW

I

Japa

n

EM EU

Asia ex

Jap

an US

Hea

lthca

re

Con

. Cyc

licals

Tech

nology

Teleco

m

Con

. Staples

Indu

strials

Utilities

Materials

Energy

Percen

t

Regions Sectors

As of August 31, 2015Source: MSCI and AB

Revisions Weak Outside Japan, Especially IndustrialsI/B/E/S Cap-Weighted Earnings Revision

Cyclicals Defensives Industrials Technology

US –1.0% 0.8% –5.5% –2.3%

EU & UK –9.0 –7.7 –14.5 –0.5

Japan 3.7 1.1 –0.5 5.6

Asia ex Japan –5.0 –5.3 –6.3 –2.1

AU & NZ –4.2 –6.6 –31.5 0.0

LatAm –1.2 –4.4 –7.5 0.0

As of August 31, 2015Arrow: improving or deteriorating earnings revision of past six months; cell color: redmeans bottom 30%, while teal means top 30% for the past 10 years.Source: Thomson Reuters I/B/E/S and AB

Employment Neutral in Most RegionsEmployment Surprise

–1.5

–1.0

–0.5

0.0

0.5

1.0

1.5

Feb14

Apr14

Jun14

Aug14

Oct14

Dec14

Feb15

Apr15

Jun15

Aug15

Japan

Eurozone

UK

USPositive

Negative

Surprise

Through August 31, 2015Source: AB

Positive Output Surprises in Japan, USOutput Surprise

–1.0

–0.5

0.0

0.5

1.0

1.5

Feb14

Apr14

Jun14

Aug14

Oct14

Dec14

Feb15

Apr15

Jun15

Aug15

Eurozone

UK

Japan

US

Positive

Negative

Surprise


1 2

3 4

5 6

11

Subdued Inflation Expectations ex EMFive-Year Implied Inflation Level vs. CPI

–1

0

1

2

3

4

–1 0 1 2 3 4

Break

even

s(Perce

nt)

US (Down)

Consumer Price Index (YoY % Change)

Japan (Down)APAC ex Japan (Up)

Canada (Down)

EM (Up)

DM (Down)

EU ex UK (Down)

UK (Down)

Germany (Down)

Australia (Down)


Cost of “Inflation Insurance” Is HighReal Yield on 10-Year Inflation-Indexed Bonds*

–0.2

–0.1

0.0

0.1

0.2

0.3

0.4

–1.8 –1.4 –1.0 –0.6 –0.2

Rising

Falling

High Low

“Inflation Insurance” CostChange in “Inflation Insurance” Cost

UK

EU ex UK

DM

Asia ex Japan

US

Canada

Japan

EM

Australia

Global

Germany

As of August 31, 2015*Level vs. history and recent change (percent)Source: AB

Broad Acceleration in Consumer Loans…Housing Prices vs. Consumer-Loan Growth (Percent)

–2

–1

0

1

2

3

4

5

–2 –1 0 1 2 3 4 5

4-Month Change in

Consumer-Loan Growth

4-Month Change in Housing Prices

EM

Germany

DM

Australia

US

Japan

Canada

EU ex UK

China

UK


…but Commodities Continue to WeakenCommodities Inflation (Percent)

–6.0–4.5–3.0–1.5 0.0 1.5 3.0

–24–18–12–60612

Natural Gas

Petroleum

Grains

Livestock

Soft

Com

modities

Ind. Metals

Gold

Spot Returns

Contango

and Cost Y

ield

Spot Returns Contango Daily Cost Yield

Inflationary

Deflationary

Soft

Com

modities



Inflation

Labor Cost Acceleration Has Not Hit Inflation Expectations

Some Currency-Driven Reflation in EuropeChange in Import Prices/Imports as Percent of Economy

–4

–3

–2

–1

0

1

2

3

4

10 15 20 25 30 35 40 45

Imports as Percent of Economy

Japan

Canada

US

Germany

Brazil

China

UK

4-M

onth

Cha

nge

in Im

port

Pri

ces

(%)

Australia


Unit Labor Cost AcceleratingUnit Labor Cost vs. Two Quarters Ago (YoY % Change)

–3.0

–2.0

–1.0

0.0

1.0

–0.5 0.0 0.5 1.0 1.5 2.0

YoY % Change in Unit Labor Cost

Japan

Canada

US

GermanyOECD Total

UK

Change in Inflation (%

)

Australia Euro Area

Inflationary/Accelerating

Deflationary/Decelerating

Accelerating

Decelerating

As of August 31, 2015Source: Haver Analytics, OECD and AB

1 2

3 4

5 6

12

Credit/Sentiment

Dichotomy: Equities Risk-Seeking, While Credit Spreads Widen


Spreads Mostly WidenRegional Credit Spreads and Recent Momentum

0.0

0.5

1.0

1.5

–1.0 –0.5 0.0 0.5 1.0

Spre

ad M

omen

tum

Regional Credit Spread*

Australia

Wid

enin

g N

arro

win

g

EM

Asia ex Japan

EU ex UK

Japan

USDM

UK

Canada

Germany

Narrow Wide

Global

As of August 31, 2015*Expressed as z score vs. historySource: AB

Largely Risk-Seeking Behavior Persists in EquitiesEquity VRP*

–1.2–1.0–0.8–0.6–0.4–0.20.00.20.40.60.8

–1.8–1.6–1.4–1.2–1.0–0.8–0.6–0.4–0.2 0.0 0.2 0.4 0.6 0.8

4-Month Average

1-Month Average

Japan

USDM

Asia exJapan

UK

EU ex UK

EM

Canada

GermanyAustralia

IncreasinglyRisk-Seeking

PersistingRisk Aversion

IncreasinglyRisk-Averse

PersistingRisk-Seeking

As of August 31, 2015*Volatility risk premium (VRP) is the difference between implied and observedvolatility.Source: AB

Styles Differ by RegionRisk Aversion: Regional Level and Trend*

–0.4

–0.2

0.0

0.2

0.4

0.6

0.8

1.0

–3.0 –2.5 –2.0 –1.5 –1.0 –0.5 0.0 0.5 1.0 1.5 2.0 2.5Current Level of Risk Aversion

Exploit ValueOpportunities

Risk-Averse Risk-Seeking

Japan†

Canada UK

Asia-Pacificex Japan

EM

EU ex UK DM

Global

Defensive

Trend Following Wins

Favor High Quality

Risk-Seeking

Risk-Averse

US

Cha

nge in Risk Aversion

Australia

Germany

As of August 31, 2015*The difference in z scores of (10-year minus two-year) bond slopes minus z scores ofoption-adjusted spreads†Driven by an unusually flat bond slope as a result of monetary policySource: AB

Broad Acceleration in Loan GrowthCredit Growth vs. Trend

US

UK

Canada

Japan

–0.4

–0.2

0.0

0.2

0.4

0.6

–1.0 –0.5 0.0 0.5 1.0 1.5 2.0

Slower Faster

Accelerating

Decelerating

NZ

Germany

Upward Pressure on Rates

Downward Pressure on Rates

Cha

nge in Loa

n Growth

YoY % Bank-Loan Growth

Australia


Consumer Surprises NeutralConsumer Sentiment Surprise Index

–2

–1

0

1

2

3

4

Jan14

Mar14

May14

Jul14

Sep14

Nov14

Jan15

Mar15

May15

Jul15

US

Eurozone

UK

Japan

Positive

Negative

Surprise


Business Surprises Broadly WidenBusiness Sentiment Surprise Index

–2

–1

0

1

2

Jan14

Mar14

May14

Jul14

Sep14

Nov14

Jan15

Mar15

May15

Jul15

Eurozone

UK

US

Japan

Positive

Negative

Surprise


1 2

3 4

5 6

13


Valuation (Equities/Bonds)

Few Deep-Value Opportunities

US vs. Japan High Valuation GapRegional Equity Valuations: Shiller & Forward P/E

0

25

50

75

100

0 25 50 75 100

Relative Shiller P/E (Percentile Rank)Attractive Unattractive

Unattractive

Global

Canada

Germany

Asia-Pacificex Japan

UK

Japan

EU ex UK DM

EM

Relative Forward P/E

(Percentile Rank)

Attractive

AustraliaUS


Some Opportunities in EMCurrent Relative Valuations vs. History by Geography*

0

25

50

75

100

0 25 50 75 100

Price to Forward Ea

rnings

Price to Book

IND

CHN

CHL

GRC

CHE

ISRHKG

FRAFIN

DNK

BRA

BEL

AUS

Attractive Unattractive

Una

ttractive

Attractive

JPN

ITAAUT IDN

UK

NOR

PHL

ESP

NZL

THA

SWE

SGP

RUS

POL

KOR

NLD

MYS

TUR

TWN

MEX

PRT

US

ZAF

CAN

DEU

Through August 31, 2015*Percentile vs. history. MSCI All-Country World universe, medians, January 1,1988–August 31, 2015Source: FactSet, MSCI, Thomson Reuters I/B/E/S and AB

Energy, Financials, Semis Exhibit Relative Value…Global Equity Sectors: Valuation Relative to History*

0

25

50

75

100

0 25 50 75 100

Price to Forward Earnings

Price to Book

Food & Drug Retailing

Materials

Utilities

Energy Real Estate

HC Equip & Svcs.

Banks

Diversified FinancialsInsurance

Transports

HW &Semis

Autos &Components

Food, Beverage & Tobacco

ConsumerSvcs.

TelecomSvcs.

ConsumerDurables &Apparel

Retailing

Software Svcs. Media

Pharma

HHProducts

Capital Goods

Commercial Svcs.

Unattractive

Attractive

Attractive Unattractive

Through August 31, 2015*MSCI All-Country World universe, medians, January 1, 1988–August 31,2015Source: FactSet, MSCI, Thomson Reuters I/B/E/S and AB

…as Do EM Equities; Rest ExpensiveOverall Valuations (Percentile)*

–40

–32

–24

–16

–8

0

0

20

40

60

80

100

DMEquity

EMEquity

DMBonds

EMBonds

Current

Rising

Declining

Una

ttractive

Attractive

Current(Left Scale)

Change

Change vs. Four M

onths Ago

Through August 31, 2015*Stocks and bonds relative to history (percentile rank since 1970)Source: FactSet, MSCI, Thomson Reuters I/B/E/S and AB

Wider Credit SpreadsGlobal Credit Valuation

–10

0

10

20

30

40

–1.0 –0.5 0.0 0.5 1.0

Widen

ing

Wide

Tigh

tening

Glbl. HY [558]

Narrow

EM HY [733]

EM IG [235]

Glbl. ABS [73]

Glbl. IG [154]

Spread vs. History

Spread

Cha

nge vs. Last Mon

th

As of August 31, 2015[ ] indicates current spread level.Source: AB

Real-Yield Slope Attractive in US, EMReal Interest Rates and Slope (Percent)*

–1.5

–0.5

0.5

1.5

2.5

–2.0 –1.0 0.0 1.0 2.0 3.0 4.0

Real-Yield Slope

Real Yields

Less Attractive

EM

USCanada

UK

Germany

DM

Japan

More Attractive

Less Steep

Steeper

Australia

EU ex UKAsia ex Japan

As of August 31, 2015*Regional 10-year bonds relative to global universeSource: AB

1 2

3 4

5 6

14

Valuation (Currencies/Commodities)

Commodities Collapse; Few Currency Tilts

CNY, GBP Are Modestly UnattractiveCurrency Valuation and Technical Signals

AUD

CAD

EUR

NOK

CHF

GBP

USD

–2.0

–1.5

–1.0

–0.5

0.0

0.5

1.0

–2.0 –1.5 –1.0 –0.5 0.0 0.5 1.0 1.5 2.0 2.5

CNY

Technical Signals

Valuation

BRL

Poised toAppreciate

Poised toDepreciate

Poor Value,FavorableSentiment

Good Value, Poor Sentiment

JPY


Long-Term Oil Trades at Marginal CostWTI Crude Futures Curve

40

50

60

70

80

90

100

Nov15

Aug16

May17

Feb18

Nov18

Aug19

May20

Feb21

Nov21

Aug22

May23

Future Expiration MonthUSD/Barrel

WTI Crude 1 Year Ago

WTI Crude Current


Copper Pessimism PersistsLME Copper Futures Curve*

220

240

260

280

300

320

Aug15

Apr16

Dec16

Aug17

Apr18

Dec18

Aug19

Apr20

USD/Tonne

Future Expiration Month

Copper Current

Copper 1 Year Ago

As of August 31, 2015*London Metal ExchangeSource: AB

Uniform Downward Move in GoldGold Futures Curve

1,100

1,200

1,300

1,400

1,500

Sep15

Apr16

Nov16

Jun17

Jan18

Aug18

Mar19

Oct19

May20

Dec20

Gold Current

Gold 1 Year Ago

Future Expiration Month

USD

/Tro

y O

unce



1 2

3 4

15

Risk and Correlation

Opportunities to Take Cross-Sectional Risk Are Limited

Volatility Up SlightlyHistorical Volatility

0

2

4

6

8

0

10

20

30

40

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

Percen

t

Global SovereignDebt (Right Scale)

Global Equity

Global Investment-Grade CDX

Percent


Limited Geographic Diversification OpportunitiesMacro Impact on Cross-Sectional Pricing*

20

30

40

50

60

70

80

1971 1977 1983 1989 1995 2001 2007 2013

Equities Percentile = 88

Percent of Variance Explained

by a Single Factor

Bonds Percentile = 89

Equities/CreditsBonds

Through August 31, 2015*Equities/credits and bondsSource: AB

Increase in Correlation Among CommoditiesMacro Impact on Cross-Sectional Pricing*

20

25

30

35

40

45

50

55

60

1971 1977 1983 1989 1995 2001 2007 2013

Commodities Percentile = 52

Percent of Variance Explained

by a Single Factor

Through August 31, 2015*CommoditiesSource: AB

Surprisingly, Still Crowding in EMCrowding by Global Regions

9589 83

42

29 24

8293

97

5

22

39

EmergingMarkets

Japan UK NorthAmerica

Asiaex Japan

Europeex UK

Percent of Market CapPercent of Companies

Crowding

More

Less

January 1, 1988–August 31, 2015Note: 100 means most crowded; 0 means least crowded.Source: AB

Consumer, Tech Crowded, Commodities UnderownedCrowding by Global Sectors

86 8575

67 63

40 3725 20

3

5365

94

54

84 81

4232

39

3

Technology

Consumer

Discretionary

Telecom

Utilities

Health

care

Consumer

Staples

Industrials

Financials

Materials

Energy

Percent of Market CapPercent of Companies

Crowding

More

Less

Consumer

Staples

Consumer

Discretionary

January 1, 1988–August 31, 2015Note: 100 means most crowded; 0 means least crowded.Source: AB


3 4

5 6

Correlations Reverting Toward ZeroHistorical Correlation

–80

–40

0

40

80

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

Percent

Global Equity vs. Global Bonds

Global Equity vs. USD

Global Equity vs. Oil

Through August 31, 2015Source: MSCI and AB

1 2

16

PERFORMANCE (Page 8)Equity Returns by Region: Total returns, in local-currencyterms, of countries and regions from the MSCI family of globalindices. Three-year percentiles are compared with historicalreturns since January 1970 or the earliest available returns fordeveloped markets, and since January 2001 for emergingmarkets (EM) and emerging-market subregions.

Equity Global Sector Returns: Various sector returns, inlocal-currency terms, of the MSCI All-Country World Index.Three-year percentiles are compared with historical returns sinceJanuary 1999.

Equity Risk Premium Returns: Value, growth, income, high-riskand high-beta premium returns are calculated by applying aquantitative screen to a global universe of large-cap stocks toassemble a group of stocks that embody the specific premium.

The MN Quant return applies a similar methodology to a globaluniverse of large-cap stocks to create groups of stocks withdeep-value, current-value, capital-use, profitability, quality andmomentum factors, and then equally weights those groups.

Three-year percentiles are compared with historical returns sinceJanuary 2003.

Bond Returns by Region: Various country and regional returnsare derived from the Barclays Global Treasury Bond Index.Regional treasury returns are weighted using the countryweights from the Barclays Global Aggregate Bond Index.Three-year percentiles are compared with historical regionalbond returns since January 1970 and with historical globaltreasury returns since September 2000.

Bond Strategy Returns: Global-investment-grade, global-high-yield, EM-investment-grade, EM-high-yield and global-asset-backed returns are from the Barclays Global Aggregate BondIndex.

Duration returns are calculated by combining a long position inthe Barclays Global Treasury 7–10 Year Index (Hedged) and a shortposition in the Barclays Global Treasury 1–3 Year Index (Hedged).

Fixed Income Carry returns are calculated from the seven-year/three-month government-bond yield-curve slopes of 10countries: the US, the UK, Japan, Germany, Australia, NewZealand, Norway, Sweden, Switzerland and Canada. Longexposures in hedged seven-year bonds in countries with steepslopes are combined with short positions in hedged seven-yearbonds in countries with flat slopes.

Three-year percentiles are compared with historical regionalbond returns since 1970 or the earliest available returns.

Commodities Spot Returns: Commodity returns based on theBloomberg Commodity Index and subcomponents. Three-yearpercentiles are compared with historical returns since January1991 for all returns except gold, which is compared withhistorical returns since January 1970.

Spot Currency Returns: Spot returns versus the US dollar forall currencies except the US dollar, based on data fromBloomberg. The US dollar is measured as a spot return versus abasket of other countries’ currencies weighted by grossdomestic product (GDP), based on data from Bloomberg.Three-year percentiles are compared with historical returns sinceJanuary 1971 or the earliest available returns.

ATTRACTIVENESS (Page 9)Each display looks at a specific asset class and shows measuresof yield and their current percentile rankings versus history.

Attractiveness 1: The first display shows attractiveness ofeach asset class. Notes: (1) DM Equity, EM Equity and DM BondRegions are relative to their DM aggregates. (2) Currencies arevs. USD, except for USD, which is vs. the GDP-weighted basket.(3) Global and Regional Credit are relative to their duration-equivalent treasuries. (4) EU ex UK Bonds are weighted by theEU index weight, but the underlying asset is DEU Bondspost-1998.

GROWTH (Page 10)Growth 1: By capturing recent changes in sentiment andeconomic data, this display identifies those regions with strongand improving growth and those with weak and deterioratinggrowth.

“Fundamentals” shows the views of company managements bymeasuring the degree of deviation versus the average for thelevel of the Purchasing Managers’ Index survey results by region.“Change in unemployment” is calculated over the last fourmonths—negative change is good, since employment is rising.

Growth 2: This display shows consumer spending trends bycomparing the degree of deviation versus the average for thelast four-month change in Purchasing Managers’ Index surveyresults with recent market data for consumer-cyclicals stocks.

Growth 3: By capturing recent changes in sentiment andprofitability data, this display identifies those equity regions andsectors with strong and improving growth and those with weakand deteriorating growth.

Glossary

17

Growth 4: This display shows market-capitalization-weightedearnings revisions for equity sectors across different regions togauge investor sentiment. Cyclicals: consumer cyclicals, financials,autos & housing; defensives: defense, consumer staples, utilities,healthcare, telecom; industrials: capital equipment, energy,commodities, transports; technology: technology.

Growth 5, 6: Each series in this display is a proprietary compos-ite of periodic economic data releases expressed as the degreeof deviation versus the average for employment and output fordifferent countries and regions.

INFLATION (Page 11)Inflation 1: This display captures three dimensions of inflationand identifies regional outliers. The three measures are actualinflation (the year-over-year percent change in the ConsumerPrice Index [CPI] on the vertical axis), the market’s view of futureinflation (“Breakevens” on the horizontal axis) and how that haschanged recently (indicated by up or down next to the country/region name).

“Breakeven” implied inflation is calculated as the differencebetween five-year nominal and real yields.

Inflation 2: This display captures the market-derived cost ofinflation insurance and how that has changed recently indifferent regions of the world.

“’Inflation insurance’ cost” is the degree of deviation versus theaverage for the 10-year inflation-indexed bond yield. The“change in ‘inflation insurance’ cost” is the one-month changein the 10-year inflation-indexed bond yield.

Inflation 3: This display looks at two measures of potentialinflation in different regions of the world: housing prices andconsumer-loan growth.

Inflation 4: This display looks at inflationary pressures withincommodities and how they’re reflected in the futures market.

“Contango” is the degree of deviation versus the average forthe price difference between spot and the next available futurescontract. “Daily cost yield” is the degree of deviation versus theaverage for the average cost of production as a percent of thecurrent spot price. Spot returns are month-over-monthprice changes.

Inflation 5: This display looks at the potential for inflationbuilding up as a consequence of rising import prices inselect economies.

Inflation 6: This display examines trends in unit labor costsby region.

“Unit labor cost” measures the average cost of labor per unit ofoutput and is calculated as the ratio of total labor cost to realoutput year over year. “Change in inflation” is the six-monthchange in the year-over-year unit labor cost.

CREDIT/SENTIMENT (Page 12)Credit/Sentiment 1: This display establishes the relativeattractiveness of credit by looking at current credit spreads byregion and the recent changes in those credit spreads.

“Regional credit spread” is expressed as the degree of deviationversus the historical average. “Spread momentum” is acomposite degree of deviation versus the historical average ofthe change in spreads over the intermediate term.

Credit/Sentiment 2: This display looks at the market senti-ment, as expressed through the equity volatility risk premium(VRP)—both the average over the last month and over the lastfour months. A higher reading for both indicates persistingmarket fear or uncertainty.

“Equity VRP” is measured by the difference between theone-month implied and the observed volatility in each regionalequity market.

Credit/Sentiment 3: This display looks at the current level andtrend of risk aversion across various regions.

“Current level of risk aversion” is measured by the difference inthe degree of deviation versus the historical average of thebond slope (as defined by the 10-year yield minus the two-yearyield) minus the degree of deviation versus the historicalaverage of option-adjusted spreads (OASs). “Change in riskaversion” is the four-month change in this signal.

Credit/Sentiment 4: This display measures current loan growthand the trend of loan growth for different countries, as a way todetermine the fundamental pressure on rates.

“YoY % bank-loan growth” is defined as the degree ofdeviation versus the historical average for each region’syear-over-year bank loan growth. “Change in loan growth” isdefined as the four-month change in that score.

Credit/Sentiment 5: Each series in this display shows thedegree of deviation versus the average for consumer sentimentfor different countries and regions over time.

“Consumer Sentiment Surprise Index” is a proprietary compositeindex level created by combining various economic releases.

18

Credit/Sentiment 6: Each series in this display shows thedegree of deviation versus the average for business sentimentfor different countries and regions over time.

“Business Sentiment Surprise Index” is a proprietary compositeindex level created by combining various economic releases.

VALUATION (EQUITIES/BONDS) (Page 13)Valuation (Equities/Bonds) 1: This display confirms therelative attractiveness of regions by looking at two differentmeasures of equity valuations (Shiller P/E and forward P/E).Each measure shows the current percentile versus historysince 1970.

Valuation (Equities/Bonds) 2: This display confirms the relative attractiveness of global equity market factors by looking at two different measures of equity valuation (P/FE and P/B). Each measure shows the current percentile versus history since 1988.

Valuation (Equities/Bonds) 3: This display confirms the relative attractiveness of global equity market sectors by looking at two different measures of equity valuation (P/FE and P/B). Each measure shows the current percentile versus history since 1988.

Valuation (Equities/Bonds) 4: This display uses a proprietaryvaluation composite that covers a broad range of inputs toexpress percentile rankings versus history since 1970 and thefour-month change in those rankings for developed- andemerging-market equities and bonds.

Valuation (Equities/Bonds) 5: This display looks at currentlevels and recent changes in credit spreads for different regionsand sectors of the bond markets.

“Spread versus history” is measured as the OAS and shows thedegree of deviation versus the historical average. The verticalaxis shows the month-over-month change in OAS.

Valuation (Equities/Bonds) 6: This display looks at the leveland slope of real bond yields as a valuation measure forinflation-indexed bonds across regions.

“Real yields” are the current yields for 10-year inflation-indexedbonds (using nine-year when 10-year wasn’t available), and the“real-yield slope” is the difference in real yields between the10-year and three-month bonds.

VALUATION (CURRENCIES/COMMODITIES) (Page 14)Valuation (Currencies/Commodities) 1: This display rates theattractiveness of various currencies by looking at bothfundamental valuations and technical signals.

Both measures are shown as a degree of deviation versus thehistorical average versus USD (except for USD, which is shownrelative to a GDP-weighted basket of currencies). The valuationscore is a proprietary composite based on interest-ratedifferentials and purchasing power parity (PPP) divided by FXrate. “Technical signals” is a proprietary composite based on thelevel of and change in option skew.

Valuation (Currencies/Commodities) 2: This display looks atthe market’s expectations of future prices of WTI crude now anda year ago.

Valuation (Currencies/Commodities) 3: This display looks atthe market’s expectations of future prices of gold now and ayear ago.

Valuation (Currencies/Commodities) 4: This display looks atthe market’s expectations of future prices of LME copper nowand a year ago.

RISK AND CORRELATION (Page 15)Risk and Correlation 1: This display provides perspective oncurrent risk levels by looking at current and historical equity andfixed-income volatility.

Levels of risk are calculated as volatility over an intermediate-term decay with a six-month half-life.

Risk and Correlation 2: This display looks at current andhistorical cross-asset correlations.

Correlations are calculated over an intermediate-term decaywith a six-month half-life. Oil is represented by a composite ofWTI crude, Brent crude, gasoline and heating oil prices.

Risk and Correlation 3: This display looks at the impact ofmacro factors on stock and bond returns. The smaller thepercentile number, the less the impact from a single macrofactor and the greater the chance that security selection will berewarded. This number is based on a proprietary model.

Risk and Correlation 4: This display looks at the impact ofmacro factors on commodity returns. The smaller the percentilenumber, the less the impact from a single macro factor and thegreater the chance that security selection will be rewarded. Thisnumber is based on a proprietary model.

Risk and Correlation 5: This display looks at the level ofcrowding in equities by regions.

“Crowding” is based on proprietary models that look at metricssuch as high analyst ratings, elevated valuations, strong recentperformance and large holdings of institutional investors. Eachnumber is relative to history.

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Risk and Correlation 6: This display looks at the impact ofcrowding on equities by global sectors.

“Crowding” is based on proprietary models that look at metricssuch as high analyst ratings, elevated valuations, strong recentperformance and large holdings of institutional investors. Eachnumber is relative to history.

Note to All Readers: The information contained here reflects the views of AllianceBernstein L.P. or its affiliates and sources it believes are reliable as of the date of thispublication. AllianceBernstein L.P. makes no representations or warranties concerning the accuracy of any data. There is no guarantee that any projection, forecast or opinionin this material will be realized. Past performance does not guarantee future results. The views expressed here may change at any time after the date of this publication. Thisdocument is for informational purposes only and does not constitute investment advice. AllianceBernstein L.P. does not provide tax, legal or accounting advice. It does nottake an investor’s personal investment objectives or financial situation into account; investors should discuss their individual circumstances with appropriate professionalsbefore making any decisions. This information should not be construed as sales or marketing material or an offer or solicitation for the purchase or sale of any financialinstrument, product or service sponsored by AllianceBernstein or its affiliates.

Note to Canadian Readers: This publication has been provided by AllianceBernstein Canada, Inc. or Sanford C. Bernstein & Co., LLC and is for general informationpurposes only. It should not be construed as advice as to the investing in or the buying or selling of securities, or as an activity in furtherance of a trade in securities. NeitherAllianceBernstein Institutional Investments nor AllianceBernstein L.P. provides investment advice or deals in securities in Canada.

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Note to New Zealand Readers: This document has been issued by AllianceBernstein New Zealand Limited (AK 980088, FSP17141). Information in this document isintended only for persons who qualify as “wholesale clients,” as defined by the Financial Advisers Act 2008 (New Zealand), and should not be construed as advice.

Note to Singapore Readers: This document has been issued by AllianceBernstein (Singapore) Ltd. (“ABSL”, Company Registration No. 199703364C). ABSL is a holder of aCapital Markets Services Licence issued by the Monetary Authority of Singapore to conduct regulated activity in fund management and dealing in securities. AllianceBernstein(Luxembourg) S.à r.l. is the management company of the portfolio and has appointed ABSL as its agent for service of process and as its Singapore representative.

Note to Hong Kong Readers: This document is issued in Hong Kong by AllianceBernstein Hong Kong Limited , a licensed entity regulated by the HongKong Securities and Futures Commission. This document has not been reviewed by the Hong Kong Securities and Futures Commission.

Note to Readers in Vietnam, the Philippines, Brunei, Thailand, Indonesia, China, Taiwan and India: This document is provided solely for the informational purposesof institutional investors and is not investment advice, nor is it intended to be an offer or solicitation, and does not pertain to the specific investment objectives, financialsituation or particular needs of any person to whom it is sent. This document is not an advertisement and is not intended for public use or additional distribution.AllianceBernstein is not licensed to, and does not purport to, conduct any business or offer any services in any of the above countries.

Note to Readers in Malaysia: Nothing in this document should be construed as an invitation or offer to subscribe to or purchase any securities, nor is it an offering offund-management services, advice, analysis or a report concerning securities. AllianceBernstein is not licensed to, and does not purport to, conduct any business or offer anyservices in Malaysia. Without prejudice to the generality of the foregoing, AllianceBernstein does not hold a capital-markets services license under the Capital Markets &Services Act 2007 of Malaysia, and does not, nor does it purport to, deal in securities, trade in futures contracts, manage funds, offer corporate finance or investment advice,or provide financial-planning services in Malaysia.

MSCI Note: MSCI makes no express or implied warranties or representations and shall have no liability whatsoever with respect to any MSCI data contained herein. The MSCIdata may not be further redistributed or used as a basis for other indices or any securities or financial products. This report is not approved, reviewed or produced by MSCI.

© 2015 AllianceBernstein L.P.

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