2Q17 U.S. Low Volatility Equity Managed Account...Wells Fargo Managed Account Services | Second Quarter 2017 Analytic Investors U.S. Low Volatility Equity Managed Account FOR INVESTMENT

Wells Fargo Managed Account Services | Second Quarter 2017

Analytic Investors U.S. Low Volatility Equity Managed Account

FOR INVESTMENT PROFESSIONAL USE ONLY—NOT FOR USE WITH THE RETAIL PUBLIC

Overview of Analytic Investors, LLC

WELLS FARGO ASSET MANAGEMENT FOR INVESTMENT PROFESSIONAL USE ONLY—NOT FOR USE WITH THE RETAIL PUBLIC 2

Analytic Investors - Quantitative investment manager

Profile

Organization Clients

Part of WFAM effective October 1, 2016 Headquarters: Los Angeles Investment professionals: 19

19

54

10

10

31 3

Capabilities

54% Financial Services 19% Public 10% Corporations 10% Multiemployer 3% Insurance 3% Superannuation/

Sovereign Wealth Fund 1% Endowments/

Foundations/Charitable

Asset Composition

Benchmark Oriented (Beta 1) Factor Enhanced Core Equity Short Extension

Low Volatility Equity Alternatives Long/Short Equity Covered Call Market Neutral Equity

Total Assets:$19.3B USD*

$2.2 Benchmark Oriented $11.2 Low Volatility Equity $5.7 Alternatives

As of June 31, 2017. *Includes 3 clients/$4.0B of notional assets, representing the total value of client portfolios over which Analytic manages an overlay and 4 clients/$1.8B of non-discretionary assets1, where Analytic does not have trading authority over the client portfolio. 1. Non-discretionary assets are only available with a delay so non-discretionary AUM is dated 5/31/17.

2.3

11.4

5.6

.WELLS FARGO ASSET MANAGEMENT FOR INVESTMENT PROFESSIONAL USE ONLY—NOT FOR USE WITH THE RETAIL PUBLIC 3

http:clients/$1.8Bhttp:clients/$4.0Bhttp:Assets:$19.3B

Analytic Investors team

A pioneer in low volatility equity investing

PORTFOLIO MANAGERS

President / Portfolio Manager Joined firm in 1995 31 years of investment experience Ph.D. in Finance, University of California, Irvine MBA i n Fi nance, University of Rochester MS in Econometrics, University of Rochester BS in Mechanical Engineering, University of Manchester

ANALYSTS

Harindra de Silva, Ph.D., CFA

Zhuanxin Ding, Ph.D. Research Analyst Joined firm in 2010 31 years of investment experience Ph.D. in Economics, University of California, San Diego MS, Shanghai Jiao Tong University, China BS, Shangha i Railway Institute, China

Lucy Jin, Ph.D. Research Analyst Joined firm in 2014 Six years of investment experience Ph.D. in Finance, University of Pennsylvania MA i n Finance, University of Pennsylvania BS i n Economics, Massachusetts Institute of Technology BS i n Computer Science & Engineerin g, Massachusetts Institute of Technology

Flora Tan, CFA Research Analyst Joined firm in 2003 16 years of investment experience Master of Financial Engineering, University of California, Berkeley MS in Financial Accounting, Nationa l University of Singapore Bachelor of Engineering i n Industrial Foreign Trade, Shanghai Jiao Tong University

Monisha Jayakumar Portfolio Analyst Joined firm in 2009 10 years of investment experience MS i n Finance, Princeton University BS in Computer Engineering, Carnegie-Mellon University

Frank Jiang, CFA

Portfolio Analyst Joined firm in 2009 12 years of investment experience MBA in Finance, University of California, Los Angeles MS in Computer Science, Cal State Long Beach BS i n Engineering, Tongj University (China)

John Mahler Portfolio Analyst Joined firm in 2015 Four years of investment experience MBA, Massachusetts Institute of Technology BS in Chemical Engineering, University of California, Berkeley

Matt Robinson, CFA Portfolio Analyst Joined firm in 2008 Nine years of investment experience BS in Mathematics, Cal Poly State University, San Luis Obispo BS in Statistics, Cal Poly State University, San Luis Obispo

Kevin Cole, CFA Risk Analyst Joined firm in 2016 Five years of investment experience BA in Economics, University of Pennsylvania

Dennis Bein, CFA Chief Investment Officer / Portfolio Manager Joined firm in 1995 27 years of investment experience MBA in Finance, University of California, Riverside BS i n Business Administration, University of California, Riverside

Ryan Brown, CFA

Portfolio Manager Joined firm in 2007 11 years of investment experience MS i n Finance, University of Utah BS i n Economics, Brigham Young University

Note: CFA® and Chartered Financial Analyst® are trademarks owned by CFA Institute.



PORTFOLIO SPECIALISTS

Managing Director and Senior Portfolio Specialist Joined firm in 2009 22 years o f investment experience MBA Fi nance, Universi ty of Oregon BS in Business Administration, California State University, Chico

RESEARCH ADVISOR

George Matthews, CFA

Research Advisor Joined firm in 1998 30 years of investment experience BA in Mathematics, The Richard Stockton College of New Jersey BS i n Business Administration, The Richard Stockton College of New Jersey

Doug Savarese, CFA

RESEARCH CONSULTANTS

Research Advisor Joined firm in 1985 40 years of investment experience Ph.D. in Finance , Stanford University MBA, Brigham Young University MS i n Economics, Stanford University BA in Physics, Brigham Young University

TRADERS

Roger Clarke, PhD

Robb Ruhr, CFA Portfolio Specialist Joined Firm in 2014 18 years of investment experience BA in Economics, University of Calgary

Stephen Thorley, PhD, CFA Research Advisor Joined firm in 2000 28 years of investment experience Ph.D. in Financial Economics, University of Washington MBA i n Business, Brigham Young University B.S. in Mathematics, Brigham Young University

Andrew Claeys, CFA Director of Trading Joined firm in 2007 13 years of investment experience BS i n Business Administration, University of Denver

Michael Hetzner Trader Joined firm in 2015 15 years of investment experience MS in Finance, Villanova University BS i n Finance, Northern Michigan University

Richard Yoon

Trader Joined firm in 2009 10 years of investment experience BA i n Finance, Northeastern University




CLIENT SERVICE

Director, Relationship ManagementJoined firm in 2000 22 years of investment experience MBA Finance, University of California, Los Angeles BS in Computer Science and Public Policy, Duke University

Katie Koehler, CFA

FACTOR SOLUTIONS

Ryan Shelby, CAIA Head of Factor Solutions Joined firm in 2010 15 years o f investment experience BA in Law and Political Science, University of California, Santa Barbara

Kevin Clark, CFA Director, Relationship Management Joined firm in 1999 27 years of investment experience BA i n Business Administration, Loyola Marymount University

Chihiro Seko, CAIA Director, Relationship Management Joined firm in 2013 Nine years of investment experience Master i n Finance, Princeton BA in Economics, Tokyo University



The case for low volatility investing


1972 1992 2006

“The Capital Asset Pricing Model: Some Empirical Tests”

Studies in the Theory of Capital Markets by F. Black, M.C. Jensen

and M. Scholes

KEY FINDING Relationship between beta and return is “too flat”. Rejects the CAPM prediction that the premium per unit of beta is the expected market return minus the risk-free rate

“The Cross-Section of Expected Stock Returns”

The Journal of Finance by Fama and French

KEY FINDING Low beta securities keep pace with high beta securities

“Minimum-Variance Portfolios in the U.S. Equity Market”

The Journal of Portfolio Management by Clarke,

de Silva and Thorley

KEY FINDING Low volatility portfolios have about three-quarters the realized risk of the general market and that this risk does not come at the expense of lower realized returns

Empirical research

Low volatility equity capitalizes on lack of systematic relationship between risk and return in the equity market

Investors do not get paid for beta within equity markets


350%

300%

250%

200%

150%

100%

50%

0%

-50%

-100%

US Equity Market VMS Small Value Momentum

2012

2010

2008

2006

2004

2002

2000

1998

1996

1994

1992

1990

1988

1986

1984

1982

1980

1978

1976

1974

1972

1970

1968

1966

1964

1962

The big picture

Cumulative factor returns (1963-2012)

Source: Clarke, de Silva, Thorley “Know Your VMS Exposure,” Journal of Portfolio Management, CRSP Database Market defined as capitalization-weighted U.S. Equity Market minus Risk Free Rate Small defined as return on Small minus Big stocks Value defined as return on High minus Low book-to-market stocks Momentum defined as return on Up minus Down past return stocks VMS defined as return on Volatile minus Stable stocks


AN

NU

ALI

ZED

RET

UR

N (

%)

Across Asset Classes 1

Frontier Markets Developed Markets

Emerging Markets

Corporate Debt

Sovereign Debt

T-Bills

Average Returns

Compound Returns

Q1

Q5

0%

5%

10%

15%

20%

10% 15% 20% 25% 30% 35%

AV

ERA

GE

AN

NU

AL

RET

UR

N

STANDARD DEVIATION

Volatility Quintiles Within US Large Cap2 (1968 - 2005)

STANDARD DEVIATION (%)

Analytic research

Relationship between risk and return

1. For illustrative purposes only 2. Source: Clark, de Silva, Thorley “Minimum-Variance Portfolios in the U.S. Equity Market” The Journal of Portfolio Management, Fall 2006.


$1,200

$1,000

$800

$600

$400

$200

$0

$1,000

$900

$990

$750

$1,000

$500

PERIOD I PERIOD II

Period I Period II Simple Average Volatility

Drag Compounded

Return

Scenario 1 -10% +10% 0% -1%

Scenario 2 -50% +50% 0% -25%

1000%

800%

600%

400%

200%

0%

-200%

Potential Loss 900%

Gain Needed to Recoup Loss

400%

233%

150%

100% 67%43%25%1% 11%5%

-1% -5% -10% -20% -30% -40% -50% -60% -70% -80% -90%

Benefits of reducing volatility

Low volatility investment provides investors with smoother returns, smaller risk of a significant drawdown and less dependence on the timing

Win by not losing – Preservation of capital Implication of a significant market drawdown

For illustrative purposes only


RET

UR

N (

%)

60% Russell 1000 Index 20% Minimum Variance 20% Small Cap Index

Russell 1000 Index

Increase Return


70% Russell 1000 Index 30% Minimum Variance

RET

UR

N (

%)

Russell 1000 Index

Reduce Risk


Effective portfolio allocation – Lower risk / better returns

Risk Budgeting De-Risking

For illustrative purposes only.


ENHANCED PORTFOLIO

Plus Low Volatility Diversifier

Fixed Income1

Equity2

Low Vol3

Manager vs Benchmark: Return October 2004 – June 2017 (not annualized if less than 1 year)

2nd quarter YTD 1 year 3 years 5 years 10 years Since Inception (10-31-04)

60% Russell 1000® / 40% Barclays Aggregate 2.41% 6.44% 10.41% 6.65% 9.66% 6.48% 7.12%

50% Russell 1000® / 20% LV / 30% Barclays Agg 2.29% 6.60% 10.06% 7.49% 10.50% 6.88% 7.70%

Multi-Statistic As of 6-30-17 Sharpe Ratio

60% Russell 1000® / 40% Barclays Aggregate 0.68

50% Russell 1000® / 20% LV / 30% Barclays Agg 0.71

S&P 500 0.52

Portfolio Performance As of 6-30-17

Annualized Cumulative Return Return

(%) (%)

Std Dev (%)

60% Russell 1000® / 40% Barclays Aggregate 7.12% 139.11% 8.62%

50% Russell 1000® , 20% LV, 30% Barclays Agg 7.70% 155.76% 9.14%

Incorporating low volatility strategy into a broader portfolio

TRADITIONAL PORTFOLIO

60/40

Fixed Income1

Equity2

Past performance is no guarantee of future results. Source: Analytic Investor 1. Bloomberg Barclays U.S. Aggregate Bond Index 2. Russell 1000®

3. Analytic U.S. Low Volatility Equity For illustrative purposes only.


An important component in investors’ portfolios

Investor Benefits

Provides a way for investors to naturally be more defensive on the downside while participating on the upside

Avoiding large losses is critical to wealth accumulation and preservation, particularly forlong-term investors

Generates improved risk adjusted returns by capturingthe equity risk premium at lower volatility over the market cycle

Market Opportunity

Low-volatility stocks have historically tended to outperform high-volatility stocks on a risk-adjusted basis over a full market cycle

The Volatility Anomaly has been rigorously testedby academics and has garnered wide acceptance among global investment professionals

Investment markets are inefficient and include anomalies that investment professionals can exploit for better risk-adjusted returns


Investment goals and process


Key attributes

Uses Analytic Investors, LLC’s time-tested quantitative techniques that combine responsive, disciplined individual security selection and unbiased portfolio modeling.

Maintain 20% - 30% less risk than the index while delivering a similar or higher level of return. The strategy helps investors capture equity premium with lower downside risk to help build wealth over time through efficient compounding of returns.

Manage risk exposure at the factor, industry and stock-specific levels. The team builds a diversified portfolio of stocks with below-average forecasted risk characteristics to help achieve market-like returns with considerably less volatility than the U.S. equity market.

Dynamic expected return forecasting model used to enhance expected return.


Investment goals

1

2

3

Reduce volatility Maintain standard deviation of 20% to 30% less than index (U.S.)

Outperform over a full risk cycle Outperform in falling markets Lag in risk-seeking markets Keep up in moderately rising markets

Equity exposure Select stocks from the index Fully invested No derivatives Long only and highly liquid

Advantage: Outperform with significantly less variability


Rus

sell

1000

Ind

ex

Risk Assessment

Fundamental Risk

Statistical Risk

Stock Specific Risk Forward Looking Risk

ESG Consideration News Based Analysis

Low

Vol

Sto

ck U

nive

rse

(~35

0 S

tock

s)

Forecast Returns

70+

Sto

ckC

hara

cter

istic

s

Control for

Transaction Costs

Liquidity/Market Impact

Diversification

Interest Rate Sensitivity

Analytic U.S. Low Volatility Portfolio*

Reduce Volatility 20-30% vs. Index

Excess return target 100bps

80-150 Stocks

Approx. Turnover ~60%

Portfolio Manager Review

Investment process overview

Constructing the Analytic Low Volatility portfolio

*Modifications in the Portfolio Construction Guidelines and portfolio limitations are subject to the discretion of the investment manager.


Risk assessment

Risk assessment

Short-term Intermediate-term Long-term

Implied Volatility Gauge short-term forward looking risk

News Analytics Identify risk not captured by other risk models that may materialize over the intermediate term

ESG Assess long-term risk associated with ESG related concerns. Helps avoid black swan events

Fundamental risk BARRA Risk Model (US4L) – Forecast future risk based on current exposure to factors that have a long standing history of explaining cross sectional variability of stock return

Statistical risk Proprietary Principle Components Model – Forecast future risk based on recent, perhaps transient, factors

Stock-specific risk


Analytic U.S. Low Volatility Equity

Risk constraints

Risk Factor Portfolio constraints (General guidelines under normal circumstances*)

STATISTICAL

Target the lowest standard deviation at the portfolio level, while Volatility considering turnover and liquidity

STRUCTURAL

Industry 15% in any one industry

Risk-scaled maximum position limits up to 2.5% Proprietary Volatility Forecasts News-based AnalysisHoldings ESG

“No one position can risk more than 45 basis points of return”

*Modifications in the Portfolio Construction Guidelines and portfolio limitations are subject to the discretion of the investment manager.


P/

E

30.00

25.00

20.00

15.00

10.00

US Low Vol P/E

Russell 1000 P/E

MSCI USA Min Vol Index P/E

5.00

10/2

9/20

042/

28/2

005

6/30

/200

510

/31/

2005

2/28

/200

66/

30/2

006

10/3

1/20

062/

28/2

007

6/29

/200

710

/31/

2007

2/29

/200

86/

30/2

008

10/3

1/20

082/

27/2

009

6/30

/200

910

/30/

2009

2/26

/201

06/

30/2

010

10/2

9/20

102/

28/2

011

6/30

/201

110

/31/

2011

2/29

/201

26/

29/2

012

10/3

1/20

122/

28/2

013

6/28

/201

310

/31/

2013

2/28

/201

46/

30/2

014

10/3

1/20

142/

27/2

015

6/30

/201

510

/30/

2015

2/29

/201

66/

30/2

016

10/3

1/20

162/

28/2

017

5/31

/201

7

Valuation

Analytic U.S. Low Volatility vs. Russell 1000 and MSCI USA Min Vol (November 2004 – June 2017)

Our strategy i s generally lower

P/E, due to our valuation

component, but when low P/E

stocks become more volatile,

we will move away from them –

we did this during the Global

Financial Crisis. Large cap value

was more affected than large

cap growth stocks in that

period. Th e Min Vol index was

not live in 2008, but their back

test shows that they did not

move away from lower P/E

stocks during crisis. An active

strategy has the ability to move

away from trouble spots.

Source: Factset. Start date reflects inception of strategy.


I

nfor

mat

ion

coef

ficie

nt o

ver i

nves

tmen

t uni

vers

e

0.20

0.15

0.10

0.05

0.00

-0.05

-0.10

-0.15

-0.20

-0.25

0.25

IC Over Russell 1000 (S&P until 11/04; R1K since 11/04) 12-Month Rolling Average

Jan-

02M

ay-0

2Se

p-02

Jan-

03M

ay-0

3Se

p-03

Jan-

04M

ay-0

4Se

p-04

Jan-

05M

ay-0

5Se

p-05

Jan-

06M

ay-0

6Se

p-06

Jan-

07M

ay-0

7Se

p-07

Jan-

08M

ay-0

8Se

p-08

Jan-

09M

ay-0

9Se

p-09

Jan-

10M

ay-1

0Se

p-10

Jan-

11M

ay-1

1Se

p-11

Jan-

12M

ay-1

2Se

p-12

Jan-

13M

ay-1

3Se

p-13

Jan-

14M

ay-1

4Se

p-14

Jan-

15M

ay-1

5Se

p-15

Jan-

16M

ay-1

6Se

p-16

Jan-

17M

ay-1

7

Analytic U.S. Monthly information Low Volatility coefficient –EquityForecasting skill (January 2002 through June 2017)

Information coefficient

The Information Coefficient (IC) is the correlation between the forecasted returns at the beginning of each month and actual returns over the same month. It represents the theoretical power of the stock selection model over a one month horizon.

Source: Analytic Investors


Expo

sure

0.10

0.00

-0.10

June 2017 Exposure

June 2012 Exposure

Ass

et U

tiliz

atio

n

His

tori

cal E

arni

ngs

to P

rice

Pric

e M

omen

tum

Cas

h Fl

ow t

o Pr

ice

Ret

urn

on A

sset

s

Pred

icte

d Ea

rnin

gs t

o Pr

ice

Sal

es t

o Pr

ice

3 M

onth

Ret

urn

6 M

onth

Ret

urn

Proj

ecte

d Ea

rnin

gs G

row

th

Ret

urn

on E

quity

Prof

it M

argi

n

Insi

der

Buy

ing

CPI

Bet

a

Inte

rest

Cov

erag

e

Gro

wth

in P

rofit

abili

ty

Gro

wth

in M

arke

t

Junk

Bon

d B

eta

Gro

wth

in E

quity

Cas

h Fl

ow P

er S

hare

Vol

atili

ty

Mar

ket

Clo

sing

Pri

ce

Yiel

d B

eta

Rec

ent

EPS

Gro

wth

Sal

es P

er S

hare

Vol

atili

ty

Indu

stri

al P

rodu

ctio

n B

eta

Insi

der

Sel

ling

Gro

wth

in V

alua

tion

Leve

rage

Ana

lyst

Dis

pers

ion

Div

iden

d Yi

eld

Trad

ing

Vol

ume

Outlook

Model Analytic U.S. Low Volatility Equityadaptability (June 2012 versus June 2017)

Source: Analytic Investors This example is for illustrative purposes only and uses relative model weights for given points in time. Exposures are measured in units of standard deviation. The factor exposures used in this example may or may not be held in a given portfolio. These factor exposures should not be considered an investment recommendation.



U.S. Factor allocation

Analytic U.S. Equity Model factor allocation (Five years ending June 30, 2017)

Source: Analytic Investors The above example is for illustrative purposes only and is used to display directional similarities or differences. Exposure measured by standard deviation. Payoff measured in units defined by Analytic Investors’ proprietary calculations.



Factor performance

Analytic U.S. Low Volatility factor performance (One year ending June 30, 2017)

Source: Analytic Investors The above example is for illustrative purposes only and is used to display directional similarities or differences. Exposure measured by standard deviation. Payoff measured in units defined by Analytic Investors’ proprietary calculations


-

-

November 1, 2004 (Inception) to June 30, 2017

Ave

rage

12-

mon

th r

etur

n

30% Analytic Investors U.S. Low Volatility Equity Composite - Gross

20%

10%

0%

-10%

-20%

-30%

Down Market 12% Moderately Rising Market 0% to 12%

Russell 1000 Index

20.67% 17.88%

10.81%

6.51%

13.49%

18.52%

25 periods 75 periods 41 periods

+ – +

A history of outperformance during down markets

Downside capital preservation, Up-market participation

Past performance does not guarantee future results. Please see Composite Notes for additional information. Market assignments were made according to each 12-month Russell 1000 Index return, with corresponding composite returns for that time period. The average returns information was calculated by taking the average rolling 12-month return over the entire period shown. Representative account information shown above is supplemental to the fully compliant GIPS presentation.


November 1, 2004 to June 30, 2017 350 70

300

250

200

150

100

50

0

CBOE VIX

U.S. Low Volatility Equity, Gross

Russell 1000 Index 60

50

40

30

20

10

0

CB

OE V

IX Index Price Level

Inde

x V

alue

Nov

-04

Aug

-05

May

-06

Feb-

07

Nov

-07

Aug

-08

May

-09

Feb-

10

Nov

-10

Aug

-11

May

-12

Feb-

13

Nov

-13

Aug

-14

May

-15

Feb-

16

Nov

-16

Risk Aversion

7/07-2/09

Risk Seeking

6/06-6/07

Risk Seeking

3/09-3/10

Risk Cycling

4/10-5/12

Risk Seeking

6/12-7/15

Risk Cycling

8/15-6/16

Risk Seeking

6/16-

Cumulative growth of a dollar

Low volatility better returns and a smoother ride

– + – + – + – Wells Fargo Managed Account Services is a unit within Wells Fargo Asset Management that is responsible for the management and administration of the Wells Fargo Funds Management (“WFFM”) retail separately managed account portfolios. WFFM acts as a discretionary manager for separately managed accounts (“SMA”) and as a non-discretionary model provider in a variety of managed account or wrap fee programs sponsored by third party investment advisers, broker-dealers, or other financial services firms. Performance information shown above is not actual performance for any WFFM retail SMA performance composite but is related institutional composite performance for a similar strategy offered by our affiliated institutional investment adviser, Wells Capital Management (“WellsCap”), which acts as a sub-adviser for the Analytic Investors U.S. Low Volatility Equity managed account. WFFM does not have a retail SMA performance composite, and therefore is showing the performance above solely as supplemental information to help you understand how a similar strategy offered by an affiliated institutional investment adviser has performed. The performance is historical and should not be indicative of the future performance for any SMA. This is not intended as an offer for any WellsCap institutional composites or accounts. Periods greater than one year are annualized. Performance is presented gross of fees and does not reflect the deduction or investment advisory fees. Past performance does not guarantee future results. Please see GIPS Compliant Presentation for additional information.


Analytic Investors U.S. Low Volatility Equity - Gross 30%

Russell 1000 Index

25%

20%

15%

10%

5%

0% Q2 2017 YTD 1 Year 3 Years* 5 Years 7 Years* 10 Years* Since

Inception*

1.69

%

3.06

% 6.62

%

9.27

%

6.96

%

18.0

3%

10.3

5%

9.26

% 12.7

5%

14.6

7%

15.9

2%

15.4

3%

8.31

%

7.29

%

9.66

%

8.69

%

-


Q2 2017 YTD 1 Year 3 Years* 5 Years* 7 Years* 10 Years* Since Inception*

Analytic Investors U.S. Low Volatility Equity, Gross 1.69% 6.62% 6.96% 10.35% 12.75% 15.92% 8.31% 9.66%

Russell 1000 Index 3.06% 9.27% 18.03% 9.26% 14.67% 15.43% 7.29% 8.69%

Value added vs. Russell 1000 Index 1.37% -2.65% -11.07% 1.09% -1.92% 0.49% 1.02% 0.97%

Volatility Reduction vs. Russell 1000 Index 14% 26% 23% 23%

Wells Fargo Managed Account Services is a unit within Wells Fargo Asset Management that is responsible for the management and administration of the Wells Fargo Funds Management (“WFFM”) retail separately managed account portfolios. WFFM acts as a discretionary manager for separately managed accounts (“SMA”) and as a non-discretionary model provider in a variety of managed account or wrap fee programs sponsored by third party investment advisers, broker-dealers, or other financial services firms. Performance information shown above is not actual performance for any WFFM retail SMA performance composite but is related institutional composite performance for a similar strategy offered by our affiliated institutional investment adviser, Wells Capital Management (“WellsCap”), which acts as a sub-adviser for the Analytic Investors U.S. Low Volatility Equity managed account. WFFM does not have a retail SMA performance composite, and therefore is showing the performance above solely as supplemental information to help you understand how a similar strategy offered by an affiliated institutional investment adviser has performed. The performance is historical and should not be indicative of the future performance for any SMA. This is not intended as an offer for any WellsCap institutional composites or accounts. *Periods greater than one year are annualized. Performance is presented gross of fees and does not reflect the deduction or investment advisory fees. Past performance does not guarantee future results. Please see GIPS Compliant Presentation for additional information.

Performance as of 6-30-17

Analytic Investors’ portfolio management skill

Appendix


Analytic Investors – A history of innovation

1970 1996 1999 2002 2004 2009 2017 and Beyond

Volatility Risk Premium Capture

Market Neutral

Low Volatility Equity

Factor Enhanced Equity

Multi-factor stock selection model

130/30 Short Extension

Global Long Short


Mon

thly

Ret

urn

Spr

ead

(%)

35

30

25

20

15

10

5

0

-5

-10

-15

-20

Volatile Minus Stable (Beta) 3 Month Mov. Avg.

Jul-

05

Nov

-05

Mar

-06

Jul-

06

Nov

-06

Mar

-07

Jul-

07

Nov

-07

Mar

-08

Jul-

08

Nov

-08

Mar

-09

Jul-

09

Nov

-09

Mar

-10

Jul-

10

Nov

-10

Mar

-11

Jul-

11

Nov

-11

Mar

-12

Jul-

12

Nov

-12

Mar

-13

Jul-

13

Nov

-13

Mar

-14

Jul-

14

Nov

-14

Mar

-15

Jul-

15

Nov

-15

Mar

-16

Jul-

16

Nov

-16

Mar

-17

High beta versus low beta

VMS Returns (July 2005 – June 2017)

Source: VMS returns calculated as the return spread on quintile portfolios formed based on historical beta as described in Clarke, de Silva, Thorley “Know Your VMS Exposure,” Journal of Portfolio Management.


Strategy enhancements & accolades

Strategy research & enhancements

Currency Consideration (Current)

Uncertainty Adjustment (Current)

Incorporating Short-Sentiment Data (Current)

ESG Risk Based Model (2013, Current)

Trading Enhancements (2013, 2014, 2015, Current)

Country/Industry/Specific Beta Decomposition (2014, 2015)

Value Factor Enhancement (2014)

New Statistical Risk Model (2014)

Volatility and Equity Anomaly Interaction (2014)

Stock Specific Volatility Forecasting (2000, 2006, 2014)

Economic State Conditioning of Alpha Factors (2012, 2013)

Asynchronicity in Statistical Risk Model (2013)

News Analytics for Risk Control (2012)

Factor Aligned Risk Model (2011, 2012)

Statistical Risk Model Enhancement (2009)

Mean Reversion (2009)

Factor Weighting Scheme (Ongoing)

White papers & acknowledgements

Minimum-Variance Portfolio Composition BERNSTEIN FABOZZI/JACOBS LEVY AWARD 2012

Minimum Variance Portfolios in the US Equity Market BERNSTEIN FABOZZI/JACOBS LEVY AWARD 2007

Performance Attribution and the Fundamental Law of Active Management GRAHAM & DODD SCROLL AWARD 2005

A Factor Approach to Asset Allocation BERNSTEIN FABOZZI/JACOBS LEVY AWARD 2005

Portfolio Constraints and the Fundamental Law of Active Management GRAHAM & DODD AWARD OF EXCELLENCE 2002


Primary Index Secondary Index Total Firm Assets Gross Annual Net Annual Primary Index Secondary Index Composite Internal Number of Composite Total Firm Period 3 Yr Std Dev 3 Yr Std Dev w/ Overlay ($-Return (%) Return (%) Return (%) Return (%) 3 Yr Std Dev (%) Dispersion (%) Accounts Assets ($-mm) Assets ($-mm) (%) (%) mm)

YTD 6.62 6.53 9.27 9.40 7.85 10.30 8.59 0.49 18 5,532.8 346,388 351,031 2016 10.51 10.31 12.05 10.67 7.98 10.69 8.79 0.52 19 5,457.5 N.A. N.A. 2015 4.67 4.48 0.92 5.64 8.84 10.48 9.13 0.35 18 4,829.7 N.A. N.A. 2014 15.74 15.52 13.24 16.54 8.42 9.12 7.93 0.27 15 3,646.1 N.A. N.A. 2013 25.09 24.85 33.11 25.33 8.63 12.26 8.44 0.39 12 2,917.3 N.A. N.A. 2012 16.58 16.36 16.42 11.19 9.77 15.40 9.64 0.57 9 1,774.1 N.A. N.A. 2011 14.54 14.30 1.50 12.87 12.75 18.95 14.25 0.46 8 1,564.2 N.A. N.A. 2010 14.86 14.62 16.10 14.70 17.24 22.29 17.45 0.49 6 752.0 N.A. N.A. 2009 12.93 12.69 28.43 18.36 15.80 20.05 16.44 0.47 6 751.3 N.A. N.A. 2008 -29.09 -29.24 -37.60 -25.65 13.27 15.56 12.23 N.A. 4 481.8 N.A. N.A. 2007 10.97 10.75 5.77 4.31 5.74 7.81 6.33 N.A. 4 614.9 N.A. N.A.

GIPS® Compliant Presentation U.S. Low Volatility Equity Composite Performance Summary

Primary Index: Russell 1000 Secondary Index: MSCI USA Minimum Volatility Index Gross 1. Wells Capital Management (“WellsCap”) claims compliance with the Global Investment Performance Standards (GIPS®) and has prepared and presented this report in compliance with the GIPS standards. WellsCap has been independently verified for the periods from January 1, 1997 through December 31, 2016. 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. The Analytic Investors U.S. Low Volatility Equity Composite has been examined for the periods from November 1, 2004 through December 31, 2016. The verification and performance examination reports are available upon request. 2. WellsCap is a registered investment adviser and a wholly owned subsidiary of Wells Fargo Bank, N.A. Since the firm’s creation in 1996, the firm has acquired a number of investment teams and/or assets through mergers and acquisitions. These include assets and/or investment teams from Norwest Investment Management Inc., Sutter Advisors, LLC, Montgomery Asset Management, Benson Associates, Strong Financial Corporation, Evergreen Investments, First International Advisors, LLC, Metropolitan West Capital Management, LLC, EverKey Global Partners and ECM Asset Management Limited. In addition, Analytic Investors, LLC was added to the firm at close of business March 31, 2017. In all cases, the investment teams involved in each acquisition and merger remain autonomous teams within WellsCap. 3. The Analytic Investors U.S. Low Volatility Equity Composite (“Composite”) (formerly named the U.S. Low Volatility Equity Composite) consists of all discretionary accounts managed in this style. From a GIPS perspective, the Analytic Investors team joined WellsCap at close of business March 31, 2017 and as such the "Total Firm Assets" are only applicable since the date of acquisition. The strategy consists of long-only portfolios investing in U.S. equity securities designed to reflect the performance characteristics of the Russell 1000 Index, while focusing on absolute risk reduction. Investment results are measured versus the Russell 1000® Index and the MSCI USA Minimum Volatility (Gross) Index. From September 2006 through July 2008 the Russell 1000 Total Return Index was presented as the benchmark for the US Low Volatility Composite. In August of 2008, the benchmark was changed (retro-actively back to inception) to the MSCI USA Minimum Volatility Index. Effective January 1, 2011, as a result of subsequent methodology changes by the index provider, the benchmark for the composite reverted back to its original benchmark, the Russell 1000 Total Return Index. The Composite creation date and inception date is November 1, 2004. Performance shown prior to April 1, 2017 represents results achieved by the Analytic Investors team prior to their acquisition by WellsCap. 4. Composite returns are net of transaction costs and non-reclaimable withholding taxes, if any, are expressed in U.S. dollars, and reflect the reinvestment of dividends and other earnings. Gross composite returns do not reflect the deduction of investment advisory fees. Net composite returns are calculated using actual investment advisory fees. WellsCap’s fee schedules are available upon request and may also be found in Part 2 of Form ADV. The published fee schedule for this strategy is 0.40% for the first $20mm, 0.30% for the next $80mm, and 0.20% over $100mm. Additional information regarding WellsCap’s policies for valuing accounts, calculating performance and preparing compliant presentations are available upon request. 5. Effective January 1, 2017, internal dispersion is the equal-weighted standard deviation of the annual gross returns of all accounts included in the composite for the entire year. Prior to January 1, 2017, internal dispersion was calculated using the asset-weighted standard deviation of all accounts included in the composite for the entire year. For years where there are 5 or fewer accounts in the composite for the entire year, dispersion is not presented as it is not a meaningful statistical calculation. The 3-year annualized standard deviation measures the variability of the gross composite returns and the index returns over the preceding 36-month time period. 6. Index returns are provided to represent the investment environment existing during the time periods shown and are not covered by the report of independent verifiers. The Russell 1000 Index representing the broad U.S. market. This index measures the performance of the 1,000 largest companies in the Russell 3000 Index, which represents approximately 92% of the total market capitalization of the Russell 3000 Index. Individuals cannot invest directly in this index. Considering the objectives of the strategy, the benchmark’s volatility is anticipated to be significantly higher than that of the investment strategy. The secondary benchmark is the MSCI USA Minimum Volatility Index. This index was created in April of 2008 from the parent index (MSCI USA Index) using the Barra Global Equity Model (GEM) as the risk estimate input. For comparison purposes, both indices are fully invested, which include the reinvestment of income. The returns for the indices do not include any transaction costs, management fees or other costs. 7. Actual performance results may differ from composite returns, depending on the size of the account, investment guidelines and/or restrictions, inception date and other factors. Performance for some accounts in this composite may be calculated by third-parties that use different security pricing and performance methodologies. Past performance is not indicative of future results. As with any investment vehicle, there is always the potential for gains as well as the possibility of losses. Our registration as an Investment Adviser does not imply any level of skill or training. For a complete list of WellsCap composite descriptions, please see https://wellscap.com/about-us/business-risk-compliance.jsp.


https://wellscap.com/about-us/business-risk-compliance.jsp

Disclosure

Wells Fargo Asset Management (WFAM) is a trade name used by the asset management businesses of Wells Fargo & Company. WFAM includes but is not limited to Analytic Investors, LLC; ECM Asset Management Ltd.; First International Advisors, LLC; Galliard Capital Management, Inc.; Golden Capital Management, LLC; The Rock Creek Group, LP; Wells Capital Management, Inc.; Wells Fargo Asset Management Luxembourg S.A.; Wells Fargo Funds Distributor, LLC; and Wells Fargo Funds Management, LLC. Certain investments are distributed by Wells Fargo Funds Distributor, LLC, Member FINRA. Wells Fargo Funds Distributor, LLC, is a subsidiary of Wells Fargo & Company. Neither Wells Fargo Funds Management nor Wells Fargo Funds Distributor has fund customer accounts/assets, and neither provides investment advice/recommendations or acts as an investment advice fiduciary to any investor.

Wells Fargo Managed Account Services (the firm) is a unit within Wells Fargo Asset Management and is responsible for the management and administration of the Wells Fargo Funds Management, LLC, retail separately managed account portfolios (wrap portfolios).

Subadvisory services provided by Wells Capital Management, a registered investment adviser and wholly-owned subsidiary of Wells Fargo Bank, N.A.

The investment process and limitations described in this presentation are intended as an illustration of the manager’s general investment philosophy. Any client-specific investment guidelines or restrictions must be detailed in a written agreement between Wells Fargo Funds Management, LLC and the client.

Modifications in the Portfolio Construction Guidelines and portfolio limitations are subject to the discretion of the investment manager.

304254 08-17

NOT FDIC INSURED – NO BANK GUARANTEE – MAY LOSE VALUE


BookmarkAnalytic Investors U.S. Low Volatility Equity Managed Account Overview of Analytic Investors, LLC Analytic Investors -Quantitative investment manager Profile Organization Clients Capabilities Asset Composition Analytic Investors team A pioneer in low volatility equity investing PORTFOLIO MANAGERS Harindra de Silva, Ph.D., CFA Dennis Bein, CFA Ryan Brown, CFA ANALYSTS Zhuanxin Ding, Ph.D. Lucy Jin, Ph.D. Flora Tan, CFA Monisha Jayakumar Frank Jiang, CFA John Mahler Matt Robinson, CFA Kevin Cole, CFA Analytic Investors team PORTFOLIO SPECIALISTS George Matthews, CFA Robb Ruhr, CFA RESEARCH ADVISOR Doug Savarese, CFA RESEARCH CONSULTANTS Roger Clarke, PhD Stephen Thorley, PhD, CFA TRADERS Andrew Claeys, CFA Michael Hetzner Richard Yoon Analytic Investors team CLIENT SERVICE Katie Koehler, CFA Kevin Clark, CFA Chihiro Seko, CAIA FACTOR SOLUTIONS Ryan Shelby, CAIA The case for low volatility investing Empirical research Investors do not get paid for beta within equity markets The big picture Cumulative factor returns (1963-2012) Analytic research Relationship between risk and return Benefits of reducing volatility Win by not losing – Preservation of capital Implication of a significant market drawdown Effective portfolio allocation – Lower risk / better returns Risk Budgeting De-Risking Incorporating low volatility strategy into a broader portfolio Past performance is no guarantee of future results. For illustrative purposes only. An important component in investors’ portfolios Investment goals and process Key attributes Investment goals Reduce volatility Outperform over a full risk cycle Equity exposure Investment process overview Risk assessment Risk constraints Risk Factor STATISTICAL STRUCTURAL Valuation Information coefficient Outlook U.S. Factor allocation Factor performance A history of outperformance during down markets Cumulative growth of a dollar Performance as of 6-30-17 Analytic Investors’ portfolio management skill Appendix Strategy research & enhancements White papers & acknowledgements

Documents

2Q17 U.S. Low Volatility Equity Managed Account...Wells Fargo Managed Account Services | Second Quarter 2017 Analytic Investors U.S. Low Volatility Equity Managed Account FOR INVESTMENT