INVESTMENT COMMITTEE MEETING SENATOR …s3.amazonaws.com/boardaudio/5.30.2019 Investment...Katie Koch, Co-Head of Fundamental Equity Goldman Sachs Asset Management C Information Item:

INVESTMENT COMMITTEE MEETING SENATOR FABIAN CHAVEZ JR. BOARD ROOM

PERA BUILDING

May 30, 2019 Immediately following Board Meeting

COMMITTEE MEMBERS John Melia, Chair Steve Neel, Vice Chair Dan Mayfield Loretta Naranjo-Lopez

AGENDA

1. Roll Call 2. Approval of Agenda 3. Approval of Consent Agenda 4. Current Business ITEM PRESENTER

A Information Item: Performance Update

1. CIO Update 2. Quarterly Performance Review 3. Quarterly Market Review

Dominic Garcia Chief Investment Officer

Thomas Toth

Managing Director, Wilshire

B Information Item: Guest Speaker: Impact of Disruptive Technologies

Hugh Lawson, Global Head of Institutional Client Strategy and

Impact Investing

Katie Koch, Co-Head of Fundamental Equity

Goldman Sachs Asset Management

C Information Item: Quarterly Staff Consultant Report, Credit Portfolio Review

Thomas Toth Managing Director, Wilshire

Andrew Hayward & James Walsh,

Albourne America

Joaquin Lujan Co-Head Alpha & Director of Rates

& Credit D Information Item: Reference Portfolio Update Thomas Toth, Managing Director,

Wilshire

E Information Item: Investment Division Updates

1. Cash Plan & Rebalance Update

Kristin Varela Deputy Chief Investment Officer

(January 2019 – March 2019) 2. Manager Selection Activity Report 3. Securities Lending Update – Q1 2019

5. Other Business 6. Adjournment

Consent Agenda Approval of minutes of February 28, 2019 Investments Committee meeting.

Any person with a disability who is in need of a reader, amplifier, qualified sign language interpreter, or any other form of auxiliary aid or service to attend or participate in the hearing or meeting, please contact Trish Winter at (505) 476-9305 at least one week prior to the meeting, or as soon as possible. Public documents, including the agenda and minutes, can be provided in various accessible formats. Please contact Trish Winter if a summary or other type of accessible format is needed.

Chief Investment Officer’s Update

May 30, 2019

Dominic Garcia, Chief Investment Officer

Slide 2

Develop a Sustainable PERA Edge A More Robust Operating Model

Mission Centric Pension Best Practices Value Creation

• Sustainability of Funding Status

• Culture of Success

• Long-term View

• Flexible Pension Design

• Good Governance• Attract & Retain

Talent• Portfolio Best

Practices

• FundingSurplus/Shortfall

• Value Add vs. Passive, Reference Portfolio

• Value Add vs. Internal Benchmarks

Adapted from Peter Drucker “Model”, research from Keith Ambacthsheer, and Clark and Irwin, (2008) “Best-practice pension fund governance”, Journal of Asset Management, vol 9, 1, 2-21

Slide 3

Maintain appropriate strategic asset allocation to meet the actuarialdiscount rate assumption (7.25%) over the long run In process: portfolio enhancements to meet expected hurdle for

next 10 years

Work toward 30 year funding period of unfunded actuarial accruedliability (in process)

Meet ten-year annualized returns to equal or exceed the policybenchmark

Achieve a total investment cost at or below 85 bps

5- Year Strategic Plan

Slide 4

Meeting Long Term Assumed Returnsas of 03/31/19

10.0%

6.0%

8.5%8.9%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

10 years 20 years 30 years Since Inception (1985)

Net of Fees Performance

Average Actuarial Return Hurdle 7.71%

Slide 5

PERA Long Term Performance vs. Passive Portfolio (net of fees)

Period 1Passive

Period 2Passive +Active`

Period 3Passive + Active + Private Assets

RETURN as of 12/31/18 10 year 15 year 20 year 30 yearSince Inc (5/31/85)

NM PERA TF NOF 8.43 5.65 5.77 8.33 8.74Passive Portfolio 7.36 5.66 5.15 7.26 7.85RISK as of 12/31/18 10 year 15 year 20 year 30 year Since IncNM PERA TF NOF 8.60 9.48 9.28 9.40 9.59Passive Portfolio 8.66 9.12 9.37 9.13 9.56

Slide 6

PERA Excess Return Statistics & Histogram

• From 1989 to 2019, PERA outperformed the passive portfolio in 219 out of 361 months or 61% of the time, with an average outperformance of 2.87%

• During the same time period, PERA underperformed the passive portfolio 119 out of 361 months or 33% of the time, with an average underperformance of 2.02%

• Resulting in a Win/Loss Ratio of 1.42

Excess Return StatsOmega Ratio 2.61Mean 1.07Standard Error 0.15Median 0.87Standard Deviation 2.77Sample Variance 7.69Kurtosis -0.71Skewness 0.28Range 13.22Minimum -4.36Maximum 8.86Sum 387Count 361

0

5

10

15

20

25

30

35

40

-9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9

Num

ber o

f Mon

ths (

Tota

l 361

)

Excess Return %

PERA Active vs Passive Portfolio(4-Year rolling returns from March 1989 to March 2019)

Slide 7

Value Add of Private Assets

Total Portfolio, 4.41%

Illiquid Credit, 1.26%

Private Equity, 3.95%

Real Assets, 6.93%

-60

-50

-40

-30

-20

-10

0

10

20

30

40

50

Dec-

06

Jun-

07

Dec-

07

Jun-

08

Dec-

08

Jun-

09

Dec-

09

Jun-

10

Dec-

10

Jun-

11

Dec-

11

Jun-

12

Dec-

12

Jun-

13

Dec-

13

Jun-

14

Dec-

14

Jun-

15

Dec-

15

Jun-

16

Dec-

16

Jun-

17

Dec-

17

Jun-

18

Dec-

18

Alph

a (p

erce

nt)

Rolling Direct Alpha

Total Portfolio Illiquid Credit Private Equity Real Assets

Note: See Appendix A for description of Direct Alpha

Slide 8

1. “ Bridge the Gap”• Meeting Actuarial Returns in a Low Return Environment

2. Maneuvering through Late Cycle Economy

3. “Pig in the Python”• Managing liability bulge and burgeoning negative cash flow of the system

The Three Big Challenges Ahead

Slide 9

PERA Investment Strategy

Market ReturnCompound & produce better terminal wealth over time

Keep-up, but lag in boom times

Minimize Market Drawdowns

PERA

Slide 10

Bridging the Return Gap

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

Passive + Risk Balance + Private Assets + Active = Total

5.60% 5.60%

0.40% 0.40%

0.60% 0.60%

0.40% 0.40%

10 Year Targeted Expected Returns

Passive Reference Portfolio Risk Balance Diversified Private Assets Active Management

7.00%

Strategy #1:Improved Risk Diversification

Strategy #2: Private Asset Allocation

Strategy #3:Selective ActiveManagement

ValueAdd

Slide 11

What If We Risk-Up and Buy More Stocks?

PERA Current Strategy (passive + private assets +active)

Reference Portfolio

Nevada Strategy

Concentrated Risk Portfolio (70% Equity)

Concentrated Risk Portfolio (90% Equity)

4.00

4.50

5.00

5.50

6.00

6.50

7.00

7.50

4.00 6.00 8.00 10.00 12.00 14.00 16.00 18.00

Expe

cted

Ret

urn

Expected Risk

10 Year Portfolio Expectations Comparison

Source: Wilshire 10 Year capital market expectationsas of 3/31/2019

Slide 12

Appendix

Slide 13

• Direct Alpha:

• Background - First proposed by Oleg Gredil, Barry Griffiths, and Rudiger Stucke in 2014 (Benchmarking PrivateEquity The Direct Alpha Method).

• Methodology - Both the contributions and distributions are discounted back to the initial cash flow date by thegrowth in the selected benchmark. An IRR is calculated on the PV of all cash flows.

• Rationale - The underlying rationale of compounding all PE cash flows to the same single point in time is to‘remove’ or ‘neutralize’ the impact of any changes in the public equity index from the series of actual PE cashflows. By doing so, the resulting capitalized net cash flows no longer ‘contain’ any changes of the index, but reflectonly the sole value creation that is attributable to PE (i.e., the rate of return above or below the index returns). *

PME Definition

Sources: eVestment TopQ and Landmark Partners Private Equity Brief – March 2014, “An ABC of PME”, Rudiger Stucke, PhD

May2019

ThomasToth,ManagingDirector– WilshireAssociatesKristinVarela,DeputyCIO

Slide 2

‐40.00%

‐20.00%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

140.00%

160.00%

180.00%

Apr‐09

Sep‐09

Feb‐10

Jul‐1

0

Dec‐10

May‐11

Oct‐11

Mar‐12

Aug‐12

Jan‐13

Jun‐13

Nov‐13

Apr‐14

Sep‐14

Feb‐15

Jul‐1

5

Dec‐15

May‐16

Oct‐16

Mar‐17

Aug‐17

Jan‐18

Jun‐18

Nov‐18

Total Fund v. Reference PortfolioCumulative Distribution, 95% confidence interval7.76% return and 11.24% risk expectation

Cumulative Reference Portfolio Return

Cumulative NOF Total Fund Return

Lower Band

Target

Upper Band

Expectations based on PERA target asset allocation and Wilshire asset class assumptions as of 2009

Slide 3

‐40.00%

‐20.00%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

140.00%

160.00%

180.00%

Apr‐09

Sep‐09

Feb‐10

Jul‐1

0

Dec‐10

May‐11

Oct‐11

Mar‐12

Aug‐12

Jan‐13

Jun‐13

Nov‐13

Apr‐14

Sep‐14

Feb‐15

Jul‐1

5

Dec‐15

May‐16

Oct‐16

Mar‐17

Aug‐17

Jan‐18

Jun‐18

Nov‐18

Total Fund v. Reference PortfolioCumulative Distribution, 95% confidence interval7.76% return and 11.24% risk expectation

Cumulative Policy Index Return


Lower Band

Target

Upper Band

Slide 4

‐5.00%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

Apr‐09

Sep‐09

Feb‐10

Jul‐1

0

Dec‐10

May‐11

Oct‐11

Mar‐12

Aug‐12

Jan‐13

Jun‐13

Nov‐13

Apr‐14

Sep‐14

Feb‐15

Jul‐1

5

Dec‐15

May‐16

Oct‐16

Mar‐17

Aug‐17

Jan‐18

Jun‐18

Nov‐18

Total Fund v. Policy IndexCumulative Distribution, 95% confidence interval

1.0% active return and 1.5% active risk expectation

Cumulative Excess NOF Total Fund Return

Lower Band

Target

Upper Band

Slide 5

Selection

Allocation

Market Beta Risk

(Passive)Expected Risk of 9.90% (Expected Return of 6.35%)

Expected Active Risk of 1.4% (Expected Return of 0.6%)

Expected Active Risk of 0.6% (Expected Active Return of 0.4%)

TargetReturn 7.35%TargetRisk 10.2%

Slide 6

Cumulative Reference Portfolio Return, 3/31/2019, 2.14%

Cumulative NOF Total Fund Return, 3/31/2019, 3.84%

‐20.00%

‐10.00%

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

Jan‐18

Mar‐18

May‐18

Jul‐1

8

Sep‐18

Nov‐18

Jan‐19

Mar‐19

May‐19

Jul‐1

9

Sep‐19

Nov‐19

Jan‐20

Mar‐20

May‐20

Jul‐2

0

Sep‐20

Nov‐20

Cumulative Distribution, 95% confidence interval6.75% return and 10.50% risk expectation

Cumulative Reference Portfolio Return


Lower Band

Target

Upper Band

FYTD value add = 0.35%

PERA Fund volatility (FYTD) = 7.85%

Reference Portfolio volatility (FYTD) = 10.24%

Slide 7

Cumulative NOF Total Fund Return, 3/31/2019, 3.84%

Cumulative Policy Return, 3/31/2019, 3.33%

‐20.00%

‐10.00%

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

Jan‐18

Mar‐18

May‐18

Jul‐1

8

Sep‐18

Nov‐18

Jan‐19

Mar‐19

May‐19

Jul‐1

9

Sep‐19

Nov‐19

Jan‐20

Mar‐20

May‐20

Jul‐2

0

Sep‐20

Nov‐20

Cumulative Distribution, 95% confidence interval6.75% return and 10.50% risk expectation


Cumulative Policy Return

Lower Band

Target

Upper Band

FYTD value add = ‐0.53%

PERA Fund volatility (FYTD) = 7.85%

PERA Policy volatility (FYTD) = 10.58%

Slide 8

Cumulative Monthly Excess, 3/31/2019, 0.50%

‐4.00%

‐2.00%

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

Excess Return over Policy Cumulative Distribution, 95% confidence interval

100 bps excess return and 150 bps tracking error expectation

Cumulative Monthly Excess

Lower Band

Target

Upper Band

Total Fund One‐Year Tracking Error as of Mar 31, 2019 = 2.59%

Slide 9

Asof3/31/2019

MarketValue

%MarketValue

%Target

TotalFundPerformance

Q3FY19 FYTD 1‐yr 3‐yr 5‐yr 10‐yr

TotalFund $14.6b 100% 100%NOF Return 6.49% 3.22% 4.03% 7.64% 5.43% 10.07%

ValueAddv.Policy ‐2.50% ‐0.53% ‐0.74% ‐0.13% ‐0.29% 0.24%

GlobalEquity $6.8b 44.2% 43.5%NOF Return 10.38% 2.72% 3.22% 11.36% 7.08%

ValueAddv.Policy ‐1.54% 0.09% ‐0.76% 0.46% ‐0.47%

RiskReduction $3.2b 20.7% 21.5%

NOF Return 3.09% 4.69% 4.53% 2.34% 2.94%

ValueAddv.Policy 0.14% 0.04% ‐0.01% 0.22% 0.12%

Credit $2.3b 15.2% 15.0%NOF Return 1.77% 2.71% 2.26% 6.03% 3.35%

ValueAddv.Policy ‐4.28% ‐2.16% 0.70% ‐1.24% ‐0.71%

RealAssets $3.1b 20.0% 20.0%NOF Return 5.72% 2.93% 6.38% 6.09% 4.41%

ValueAddv.Policy ‐5.70% ‐0.52% ‐1.86% ‐0.75% 0.56%

Note:Pre‐ July2018SAATargets

Slide 10

‐0.53%

‐0.07% ‐0.03%

‐2.37%

0.14%0.00%

0.16%0.07%

0.21%

‐0.66%

‐2.50%

‐2.00%

‐1.50%

‐1.00%

‐0.50%

0.00%

0.50%

TotalFund GlobalEquity RiskReduction&Mitigation

CreditOrientedFixedIncome

RealAssets

AllocationReturn SelectionReturnReturnsarenetoffees

Slide 11

‐0.57% ‐0.55%

0.02%

‐0.20%

‐0.77%

‐0.17% ‐0.21%

‐0.03%

0.90%

‐1.09%

‐1.50%

‐1.00%

‐0.50%

0.00%

0.50%

1.00%



RealAssets


Slide 12

‐0.02%

0.63%

0.06%

‐0.35%

‐0.69%

‐0.10%‐0.18%

0.16%

‐0.89%

‐0.07%

‐1.00%

‐0.80%

‐0.60%

‐0.40%

‐0.20%

0.00%

0.20%

0.40%

0.60%

0.80%



RealAssets


Slide 13

‐0.48%‐0.42%

0.05%

‐0.05%‐0.15%

0.19%

‐0.05%

0.07%

‐0.67%

0.71%

‐0.80%

‐0.60%

‐0.40%

‐0.20%

0.00%

0.20%

0.40%

0.60%

0.80%



RealAssets


Slide 14

As ofMarch2019 CapitalAllocation

Volatility SharpeRatio

TrackingError

InformationRatio*

Beta Alpha**

TotalFund 100% 6.41% 0.65 2.59% ‐0.07 0.73 0.13%

PolicyBenchmark 8.64% 0.50

GlobalEquity 44.2% 11.72% 0.27 0.78% ‐0.16 0.86 ‐0.06%

RiskReduction 20.7% 2.83% 1.49 0.21% 0.57 0.98 0.04%

Credit 15.2% 1.87% 1.26 4.72% 0.26 0.27 0.22%

RealAssets 20.0% 5.59% 1.33 6.09% ‐0.07 0.49 0.72%

*GOF**Jensen’salpha

Slide 15

TotalFund 1.18%

PolicyBenchmark 1.33%

ExcessReturnv.PolicyBenchmark ‐0.15%

ReferencePortfolio 1.93%

ExcessReturnv.ReferencePortfolio ‐0.75%

TotalFundNAVasof4/30/2019 $15,460,094,862

ApproximateApril$ValueAddedoverPolicyPortfolio ‐ $23,006,000

ApproximateApril $ValueAddedoverReferencePortfolio ‐ $115,000,000

Slide 16

• Longterm10yearperformanceonbothanabsoluteandrelativebasisremains

strongforthePERATotalFund

• ThePERAfundunderperformedthepolicybenchmarkby250bpsforQ3FY19and

underperformedthepolicybenchmarkby74forthe1‐yearperiod,netoffees

• ThePERAfundunderperformedthepassivereferenceportfolioby185bpsforQ3

FY19,butoutperformedby80bpsforthe1‐yearperiod,netoffees

• AsofMarch31st,thefundisattargetweightsforallassetclasses /‐ 1%

Slide 17

• Selectionreturn portfolioreturn– dynamicallyweightedselectionbenchmarkreturn

• Allocationreturn dynamicallyweightedselectionbenchmarkreturn– policybenchmarkreturn

• HistoricalAlpha R– Beta*P *√12Where:Betaisportfoliobeta;R‐ meanoftheportfoliorealreturns portfolioreturn‐ 91dayTbill return ;P‐ meanofthepolicyrealreturns policyreturn– 91dayTbill return

W i l s h i r e C o n s u l t i n g

WILSHIRE ASSOCIATES

First Quarter 2019

Q u a r t e r l y M a r k e t R e v i e w

©2019 Wilshire Associates. 2


ECONOMIC REVIEW

Data sources: Bureau of Labor Statistics, U.S. Treasury, University of Michigan, Institute for Supply Management, Bureau of Economic Analysis

AS OF MAR. 31, 2019

CPI (ALL ITEMS)SEASONALLY ADJUSTED Mar-19 0.4 3-Mo. 0.6

Feb-19 0.2 12-Mo. 1.9Jan-19 0.0 10-Yr. (Annual) 1.8

BREAKEVEN INFLATION 10-Yr. 1.9CONSUMER SENTIMENT Mar-19 98.4U. OF MICHIGAN SURVEY Feb-19 93.8

1-Yr. Ago 101.4 10-Yr. Avg 83.4MANUFACTURING Mar-19 55.3INST. FOR SUPPLY MGMT Feb-19 54.2 >50 ExpansionPURCHASING MNGRS' IDX 1-Yr. Avg. 57.7 <50 ContractionNote: Seasonally adjusted CPI data is utilized to better reflect short-term pricing activity. March/2019 CPI is based on Federal Reserve of Philadelphia Survey of Professional Forecasters

MONTHLY CHANGE CUMULATIVE CHANGE

KEY ECONOMIC INDICATORS

CHANGE IN SECTOR

Real GDP

Consumer Spending

$(15,000)

$(10,000)

$(5,000)

$-

$5,000

$10,000

$15,000

$20,000

-7.5%

-5.0%

-2.5%

0.0%

2.5%

5.0%

7.5%

10.0%

Qua

rter

ly G

DP

($bi

l)

Annu

aliz

ed G

row

th

CHANGES IN REAL GDP (2012 BASE YEAR)

Annualized Change in Real GDP Private Investment Series9 Government Spending

(5.0)

-

5.0

10.0

15.0

(200)

(100)

-

100

200

300

400

Une

mpl

oym

ent

Rat

e (%

)

Job

Gro

wth

/Los

s (t

hou)

UNEMPLOYMENT RATE AND JOB GROWTH/LOSS

Job Growth (Loss) Unemployment Rate


• Estimates show that U.S. fiscal policy added nearly three-quarters of a percent to real GDP growth in 2018

• Slight detraction from growth forecasted as fiscal support fades


FISCAL POLICY BOOST

0.7%0.5%

-0.2%

2.2%

2.2%

2.0%

2.0%

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

2017 2018 2019 Forecast 2020 Forecast

U.S. FISCAL POLICY AND REAL GDP GROWTH

Real U.S. GDP Growth before StimulusContribution to U.S. GDP from Fiscal Stimulus

Data source: Prudential Financial


• Surveys provide up-to-date proxy for economic activity

• Business activity continues to grow but has slowed; Consumer confidence proxies future demand

• Rate-sensitive sectors are slowing


SIGNS OF SLOWING

Data sources: Institute for Supply Management, University of Michigan, National Association of Home Builders

30

35

40

45

50

55

60

65ISM MANUFACTURING INDEX

50

60

70

80

90

100

110

120U. OF MI CONSUMER SENTIMENT INDEX

0

10

20

30

40

50

60

70

80

90HOME BUILDERS HOME MARKET INDEX


Text


NON-U.S. GROWTH AND INFLATION

Data sources: Bloomberg

Text

Text Text

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

5.0DEVELOPED MARKETS REAL GDP GROWTH YoY (%)

USA Eurozone Japan UK

-8.0

-6.0

-4.0

-2.0

0.0

2.0

4.0

6.0

8.0

10.0

12.0EMERGING MARKETS REAL GDP GROWTH YoY (%)

China India Brazil Russia South Korea

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5DEVELOPED MARKETS CPI GROWTH YoY (%)

USA Eurozone Japan UK

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0EMERGING MARKETS CPI GROWTH YoY (%)

China India Brazil Russia South Korea


Text


RISK MONITOR

Data sources: Federal Reserve, Bloomberg Barclays

Text

Text Text

-4.00

-3.00

-2.00

-1.00

0.00

1.00

2.00

3.00

4.00

5.00

10-Year Treasury -3-Month TBill (%)

YIELD CURVE SLOPE VS RECESSIONS (IN GRAY)

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

18.00

20.00

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

Opt

ions

Adj

uste

d Sp

read

(%

)

BLOOMBERG BARCLAYS CREDIT INDEXES

Investment Grade

High Yield

< — Investment Grade High Yield — >

-2.00

-1.00

0.00

1.00

2.00

3.00

4.00

5.00

6.00

Mar

ket

Stre

ss R

elat

ive

to A

vera

ge (

Zero

)

ST. LOUIS FED FINANCIAL STRESS INDEX

Constructed from seven interest rate series, six yield spreads and five other financial stress indicators.0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

30-D

ay E

xpec

ted

Vola

tility

(%

)

CBOE VOLATILITY INDEX


• Federal Reserve changed their forecast for rate increases for 2019 to zero

• Longer term, the market expects the short-term rate to fall during the next couple years


SHORT-TERM RATES

Data sources: U.S. Treasury, J.P. Morgan

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00FEDERAL FUNDS RATE EXPECTATIONS (%)

Effective Federal Funds Rate FOMC year-end estimates Market expectations


• Federal Reserve began their balance sheet normalization program during October 2017; targeting $10B in reductions per month while increasing to $50B per month in Q4 2018

• Fed stated in early January that future reductions will be data dependent; total reductions so far equal $500 billion


FED BALANCE SHEET

Data sources: Federal Reserve

$-

$0.5

$1.0

$1.5

$2.0

$2.5

$3.0

$3.5

$4.0

$4.5

$5.0FEDERAL RESERVE: BALANCE SHEET FORECAST ($T)

U.S. Treasuries Mortgage-backed Securities Other Original Forecast

April 2019



ASSET CLASS PERFORMANCE

Data sources: Wilshire Compass Note: Developed asset class is developed equity markets ex-U.S., ex-Canada

ANNUALIZED5-YEAR

2014 2015 2016 2017 2018 2019 YTD AS OF 3/2019REITs REITs MLPs Emrg Mrkts T-Bills MLPs U.S. Equity31.8% 4.2% 18.3% 37.7% 1.9% 16.8% 10.5%

U.S. Equity U.S. Equity High Yield Developed Core Bond REITs REITs12.7% 0.7% 17.1% 25.6% 0.0% 16.0% 9.0%

Core Bond Core Bond U.S. Equity U.S. Equity U.S. TIPS U.S. Equity High Yield6.0% 0.6% 13.4% 21.0% -1.3% 14.1% 4.7%MLPs T-Bills Commodities High Yield High Yield Developed Emrg Mrkts4.8% 0.1% 11.8% 7.5% -2.1% 10.1% 4.1%

U.S. TIPS Developed Emrg Mrkts REITs REITs Emrg Mrkts Developed3.6% -0.4% 11.6% 4.2% -4.8% 10.0% 2.8%

High Yield U.S. TIPS REITs Core Bond U.S. Equity High Yield Core Bond2.5% -1.4% 7.2% 3.6% -5.3% 7.3% 2.7%T-Bills High Yield U.S. TIPS U.S. TIPS Commodities Commodities U.S. TIPS0.0% -4.5% 4.7% 3.0% -11.2% 6.3% 1.9%

Emrg Mrkts Emrg Mrkts Core Bond Commodities MLPs U.S. TIPS T-Bills-1.8% -14.6% 2.6% 1.7% -12.4% 3.2% 0.7%

Developed Commodities Developed T-Bills Developed Core Bond MLPs-4.5% -24.7% 1.5% 0.8% -13.4% 2.9% -4.7%

Commodities MLPs T-Bills MLPs Emrg Mrkts T-Bills Commodities-17.0% -32.6% 0.3% -6.5% -14.2% 0.6% -8.9%

ASSET CLASS RETURNS - BEST TO WORST



MARCH 2019 ASSET CLASS ASSUMPTIONS

DEV EMG GLOBAL LT NON-USUS EX-US MRKT EX-US GLOBAL PRIVATE CORE CORE US HIGH BOND US GLOBAL PRIVATE REAL US

STOCK STOCK STOCK STOCK STOCK EQUITY CASH BOND BOND TIPS YIELD (HDG) RES RES RE CMDTY ASSETS CPIEXPECTED COMPOUND RETURN (%) 6.25 6.75 6.75 7.00 6.70 8.95 2.45 3.40 3.85 2.70 4.80 1.05 5.15 5.35 6.70 4.35 6.10 1.90EXPECTED ARITHMETIC RETURN (%) 7.55 8.20 9.70 8.60 8.00 12.30 2.45 3.55 4.30 2.85 5.25 1.10 6.50 6.50 7.60 5.40 6.45 1.90EXPECTED RISK (%) 17.00 18.00 26.00 18.80 17.05 28.00 1.25 5.15 9.85 6.00 10.00 3.50 17.00 15.80 14.00 15.00 8.75 1.75CASH YIELD (%) 2.00 3.50 2.50 3.25 2.55 0.00 2.45 3.55 4.75 3.10 8.00 1.65 3.75 3.75 2.60 2.45 2.65 0.00

CORRELATIONSUS STOCK 1.00DEV EX-US STOCK (USD) 0.81 1.00EMERGING MARKET STOCK 0.74 0.74 1.00GLOBAL EX-US STOCK 0.83 0.96 0.86 1.00GLOBAL STOCK 0.94 0.92 0.82 0.94 1.00PRIVATE EQUITY 0.74 0.64 0.62 0.67 0.74 1.00CASH EQUIVALENTS -0.05 -0.09 -0.05 -0.08 -0.07 0.00 1.00CORE BOND 0.28 0.13 0.00 0.09 0.20 0.31 0.19 1.00LT CORE BOND 0.31 0.16 0.01 0.12 0.23 0.32 0.11 0.93 1.00US TIPS -0.05 0.00 0.15 0.05 0.00 -0.03 0.20 0.60 0.47 1.00HIGH YIELD BOND 0.54 0.39 0.49 0.45 0.51 0.34 -0.10 0.25 0.32 0.05 1.00NON-US BOND (HDG) 0.16 0.25 -0.01 0.18 0.18 0.26 0.10 0.67 0.66 0.39 0.26 1.00US RE SECURITIES 0.59 0.47 0.44 0.49 0.56 0.50 -0.05 0.17 0.23 0.10 0.56 0.05 1.00GLOBAL RE SECURITIES 0.65 0.59 0.56 0.62 0.66 0.58 -0.05 0.17 0.22 0.11 0.62 0.03 0.94 1.00PRIVATE REAL ESTATE 0.54 0.44 0.44 0.47 0.52 0.51 -0.05 0.19 0.25 0.09 0.57 0.05 0.77 0.76 1.00COMMODITIES 0.25 0.34 0.39 0.38 0.32 0.27 0.00 -0.02 -0.02 0.25 0.29 -0.10 0.25 0.28 0.25 1.00REAL ASSET BASKET 0.42 0.43 0.50 0.48 0.47 0.43 0.01 0.24 0.25 0.41 0.53 0.06 0.65 0.69 0.69 0.59 1.00INFLATION (CPI) -0.10 -0.15 -0.13 -0.15 -0.13 -0.10 0.10 -0.12 -0.12 0.15 -0.08 -0.08 0.05 0.03 0.05 0.44 0.26 1.00

EQUITY FIXED INCOME REAL ASSETSREAL ESTATE

APPENDIX: MARKET PERFORMANCE



U.S. EQUITY MARKET

Data sources: Wilshire Compass, Wilshire Atlas

AS OF MARCH 31, 2019 QTR YTD 1 YR 3 YR 5 YR 10 YR

WILSHIRE 5000 INDEX 14.1 14.1 8.9 13.6 10.5 16.0WILSHIRE U.S. LARGE CAP 14.0 14.0 9.5 13.7 10.9 15.9WILSHIRE U.S. SMALL CAP 15.5 15.5 3.7 12.4 7.2 17.1WILSHIRE U.S. LARGE GROWTH 15.7 15.7 10.1 16.4 12.6 16.9WILSHIRE U.S. LARGE VALUE 12.4 12.4 9.0 11.0 9.2 14.8WILSHIRE U.S. SMALL GROWTH 16.4 16.4 3.6 14.7 7.3 17.6WILSHIRE U.S. SMALL VALUE 14.6 14.6 3.9 9.9 7.0 16.5WILSHIRE REIT INDEX 16.0 16.0 19.3 5.4 9.0 18.7MSCI USA MIN. VOL. INDEX 12.5 12.5 14.9 11.9 12.0 15.4FTSE RAFI U.S. 1000 INDEX 12.2 12.2 5.5 11.4 8.6 19.4

8.9

-1.7

20.2

19.6

-0.3

9.6

6.2

2.1

10.5

-4.7

15.0

16.8

14.1

11.6

11.4

17.3

16.4

11.4

14.3

17.0

14.6

8.7

8.4

20.8

Wilshire 5000

Materials

Utilities

Real Estate

Energy

Consumer Staples

Communication Services

Industrials

Consumer Discretionary

Financials

Health Care

Information Technology

2.5%

3.3%

4.3%

5.1%

6.8%

9.3%

10.0%

10.5%

13.5%

13.8%

20.9%

WILSHIRE 5000 SECTOR WEIGHT & RETURN (%)

1st Quarter 1-Year

-10.00%

-8.00%

-6.00%

-4.00%

-2.00%

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

Larg

e C

ap in

exc

ess

of S

mal

l C

ap

LARGE CAP VS SMALL CAP

QTD Excess Return Rolling 3-Year Excess Return

-10.00%

-8.00%

-6.00%

-4.00%

-2.00%

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

Gro

wth

in e

xces

s of

Val

ue

GROWTH VS VALUE

QTD Excess Return Rolling 3-Year Excess Return



NON-U.S. EQUITY MARKET

Data sources: Wilshire Compass


MSCI ACWI EX-US ($G) 10.4 10.4 -3.7 8.6 3.0 9.3MSCI EAFE ($G) 10.1 10.1 -3.2 7.8 2.8 9.5MSCI EMERGING MARKETS ($G) 10.0 10.0 -7.1 11.1 4.1 9.3MSCI FRONTIER MARKETS ($G) 6.9 6.9 -14.8 7.2 0.9 8.2MSCI ACWI EX-US GROWTH ($G) 12.4 12.4 -2.7 8.8 4.4 9.9MSCI ACWI EX-US VALUE ($G) 8.5 8.5 -4.8 8.4 1.7 8.8MSCI ACWI EX-US SMALL ($G) 10.4 10.4 -9.1 7.6 3.7 12.3MSCI ACWI MINIMUM VOLATILITY 10.1 10.1 9.7 9.7 9.7 13.0MSCI EAFE MINIMUM VOLATILITY 8.0 8.0 1.8 6.5 6.5 10.8FTSE RAFI DEVELOPED EX-US 8.7 8.7 -5.2 8.7 2.2 9.9MSCI EAFE LC (G) 10.7 10.7 3.4 9.1 6.5 10.3

-3.2

6.7

-13.3

8.5

-2.8

0.1

-7.5

10.1

12.3

7.0

13.5

10.8

11.9

6.9

MSCI EAFE

Australia

Germany

Switzerland

France

United Kingdom

Japan

6.9%

8.6%

8.9%

11.3%

17.1%

24.0%

MSCI EAFE: LARGEST COUNTRIES & RETURN (USD)

1st Quarter 1-Year

-7.1

-17.2

-4.0

6.8

-5.4

-16.2

-6.0

10.0

4.6

8.1

7.2

9.0

4.9

17.7

MSCI Emrg Mrkts

South Africa

Brazil

India

Taiwan

South Korea

China

5.9%

7.2%

9.2%

11.4%

13.0%

33.0%

MSCI EM: LARGEST COUNTRIES & RETURN (USD)

1st Quarter 1-Year



U.S. FIXED INCOME

Data sources: Wilshire Compass, Bloomberg Barclays, U.S. Treasury

0

200

400

600

800

1,000

1,200

1,400

Opt

ion

Adju

sted

Spr

ead

(bps

)

BLOOMBERG BARCLAYS FIXED INCOME INDEXES

Securitized IG Corporate Aa Corporate High Yield

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

0 5 10 15 20 25 30

Yiel

d (%

)

Maturity (yrs)

TREASURY YIELD CURVE

Current Quarter Previous Quarter One Year Ago

AS OF MARCH 31, 2019 YTM DURATION QTR YTD 1 YR 3 YR 5 YR 10 YR

BLOOMBERG BARCLAYS AGGREGATE 2.9 5.8 2.9 2.9 4.5 2.0 2.7 3.8BLOOMBERG BARCLAYS TREASURY 2.4 6.2 2.1 2.1 4.2 1.0 2.2 2.4BLOOMBERG BARCLAYS GOV'T-REL. 3.0 5.5 3.1 3.1 4.5 2.4 2.8 3.2BLOOMBERG BARCLAYS SECURITIZED 3.1 4.1 2.2 2.2 4.5 1.8 2.6 3.5BLOOMBERG BARCLAYS CORPORATE 3.6 7.4 5.1 5.1 4.9 3.6 3.7 6.7BLOOMBERG BARCLAYS LT G/C 3.7 15.3 6.5 6.5 5.2 3.8 5.3 7.2BLOOMBERG BARCLAYS LT TREASURY 2.8 17.7 4.7 4.7 6.2 1.5 5.4 5.1BLOOMBERG BARCLAYS LT GOV't-REL. 4.1 12.1 6.6 6.6 5.7 4.7 5.6 7.0BLOOMBERG BARCLAYS LT CORP. 4.4 13.9 8.0 8.0 4.4 5.3 5.3 9.2BLOOMBERG BARCLAYS U.S. TIPS * 2.4 7.6 3.2 3.2 2.7 1.7 1.9 3.4BLOOMBERG BARCLAYS HIGH YIELD 6.7 3.4 7.3 7.3 5.9 8.6 4.7 11.3TREASURY BILLS 2.4 0.25 0.6 0.6 2.1 1.2 0.7 0.4

* Yield and Duration statistics are for a proxy index based on similar maturity, the Bloomberg Barclays U.S. Treasury 7-10 Year Index



HIGH YIELD BOND MARKET

Data sources: Wilshire Compass, Bloomberg Barclays


BLOOMBERG BARCLAYS HIGH YIELD 7.3 7.3 5.9 8.6 4.7 11.3CREDIT SUISSE LEVERAGED LOAN 3.8 3.8 3.3 5.9 3.8 8.0HIGH YIELD QUALITY DISTRIBUTION WEIGHTBa U.S. HIGH YIELD 45.7% 7.2 7.2 6.3 6.8 5.1 10.1B U.S. HIGH YIELD 40.0% 7.2 7.2 6.4 8.4 4.2 10.0Caa U.S. HIGH YIELD 13.2% 7.2 7.2 2.7 12.9 4.7 14.1Ca to D U.S. HIGH YIELD 0.8% 17.5 17.5 13.5 32.2 -8.0 9.3Non-Rated U.S. HIGH YIELD 0.3% 3.6 3.6 4.6 7.9 -1.0 7.7

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

Opt

ion

Adju

sted

Spr

ead

(bps

)

BLOOMBERG BARCLAYS HIGH YIELD INDEXES

HY Index Ba B Caa



NON-U.S. FIXED INCOME

Data sources: Wilshire Compass, Bloomberg Barclays, Federal Reserve Bank of St. Louis


DEVELOPED MARKETSBLMBRG BRCLYS GLBL AGGREGATE xUS 1.5 1.5 -4.1 1.0 -0.3 2.5BLMBRG BRCLYS GLBL AGGREGATE xUS * 3.0 3.0 5.2 3.3 4.3 4.3BLMBRG BRCLYS GLOBAL INF LNKD xUS 4.4 4.4 -4.8 3.0 1.2 4.7BLMBRG BRCLYS GLOBAL INF LNKD xUS * 4.4 4.4 5.0 6.5 6.6 6.2EMERGING MARKETS (HARD CURRENCY)BLMBRG BRCLYS EM USD AGGREGATE 5.4 5.4 4.4 5.3 4.8 8.5EMERGING MARKETS (FOREIGN CURRENCY)BLMBRG BRCLYS EM LOCAL CURR. GOV'T 2.4 2.4 -3.9 3.3 0.7 5.1BLMBRG BRCLYS EM LOCAL CURR. GOV'T * 2.2 2.2 3.9 2.9 3.2 3.5EURO vs. DOLLAR -1.8 -1.8 -8.7 -0.5 -4.0 -1.7YEN vs. DOLLAR -0.9 -0.9 -3.9 0.5 -1.4 -1.1POUND vs. DOLLAR 2.3 2.3 -7.1 -3.2 -4.8 -0.9* Returns are reported in terms of local market investors, w hich removes currency effects.

0.00

2.00

4.00

6.00

8.00

10.00

12.00

Yiel

d to

Wor

st (

%)

BLOOMBERG BARCLAYS FIXED INCOME INDEXES

U.S. Treasury Global xUS Gov't EM USD Sovereign EM Foreign Gov't

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

0

10

20

30

40

50

60

70

80

90

100

Rolli

ng 1

-Yea

r Re

turn

Inde

x Le

vel

U.S. DOLLAR INDEX: MAJOR CURRENCIES

Index Level Rolling 1-Year Return



GLOBAL INTEREST RATES

Data sources: Organization for Economic Co-operation and Development

Negative short-term rates remain in Europe; Long rates are down globally during the past three months

Germany

France

United Kingdom

Canada

Australia

Italy

Spain

South Korea

Portugal

U.S.

0.00

0.50

1.00

1.50

2.00

2.50

3.00

-1.00 -0.50 0.00 0.50 1.00 1.50 2.00 2.50 3.00

Long

-Ter

m /

10-

Year

Yie

lds

(%)

Short-Term / 3-Month Yields (%)

GOVERNMENT BOND YIELDS



REAL ASSETS

Data sources: Wilshire Compass, National Council of Real Estate Investment Fiduciaries


BLOOMBERG BARCLAYS U.S. TIPS 3.2 3.2 2.7 1.7 1.9 3.4BLOOMBERG COMMODITY INDEX 6.3 6.3 -5.3 2.2 -8.9 -2.6WILSHIRE GLOBAL RESI INDEX 15.0 15.0 14.8 6.3 7.9 16.4NCREIF ODCE FUND INDEX 1.4 1.4 7.5 8.0 10.2 8.7NCREIF TIMBERLAND INDEX 0.1 0.1 2.4 3.3 4.6 3.7ALERIAN MLP INDEX (OIL & GAS) 16.8 16.8 15.1 5.7 -4.7 10.1

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

Cur

rent

Yie

ld

Cur

rent

Cap

Rat

e

REAL ESTATE VALUATION

NPI Current Value Cap Rate Wilshire RESI Current Yield 10-Year Treasury Yield

-40.0

-30.0

-20.0

-10.0

0.0

10.0

20.0

30.0

Retu

rn (

%)

NCREIF ODCE FUND INDEX RETURN

Appreciation Income Total Return

Goldman Sachs Asset Management

Speaker Bios

Katie Koch, Co-head of Fundamental Equity

Katie is co-head of the Fundamental Equity business within Goldman Sachs Asset Management (GSAM). The Fundamental Equity team manages a broad range of equity solutions on behalf of institutional and individual clients around the world. Previously, Katie worked in GSAM’s London office, where she led several businesses over ten years. Most recently, Katie was head of the Global Portfolio Solutions (GPS) Group for the international business, managing multi-asset class portfolios and serving on the GPS Investment Committee. Katie joined Goldman Sachs as an analyst in 2002 and was named managing director in 2011 and partner in 2016. In 2015, Katie was honored as a Young Global Leader by the World Economic Forum. Katie has also been named as one of the Top Women in Asset Management by Money Management Executive and as a Rising Star in Asset Management by Financial News. Additionally, she has contributed to the firm’s research efforts on the economic enfranchisement of women in the developing world. Katie serves on the Board of Trustees for Patton’s Veterans Project. Katie earned a BA, magna cum laude, in English and Economics from the University of Notre Dame in 2002.

Hugh Lawson, Global Head of Institutional Client Strategy and Impact Investing Hugh Lawson is a member of the leadership team for Goldman Sachs Asset Management (GSAM)'s Client Business with global responsibility for Institutional Client Strategy and the division's Environmental, Social and Governance investing efforts. In addition, he leads GSAM's efforts focused on Public Pensions in North America. Hugh was previously co-head of Alternative Capital Markets and co-head of Hedge Fund Strategies. He joined Goldman Sachs in 1997 and was named managing director in 2003 and partner in 2012. Prior to joining the firm, Hugh worked in New York for the Rockefeller Brothers Fund and the Boston Consulting Group. He is a member of the Council on Foreign Relations and of the Columbia College Board of Visitors, and serves as a trustee and Investment Committee chair of the Rockefeller Brothers Fund. Hugh earned a JD from Yale Law School and a BA from Columbia University, summa cum laude, Phi Beta Kappa.

Five Transformational Changes Driven by Technological Innovation

THESE MATERIALS ARE PROVIDED SOLELY ON THE BASIS THAT THEY WILL NOT CONSTITUTE INVESTMENT ADVICE AND WILL NOT FORM A PRIMARY BASIS FOR ANY PERSON'S OR PLAN'S INVESTMENT DECISIONS, AND GOLDMAN SACHS IS NOT A FIDUCIARY WITH RESPECT TO ANY PERSON OR PLAN BY REASON OF PROVIDING THE MATERIAL OR CONTENT HEREIN. PLAN FIDUCIARIES SHOULD CONSIDER THEIR OWN CIRCUMSTANCES IN ASSESSING ANY POTENTIAL INVESTMENT COURSE OF ACTION.

May 2019

1

Technological Innovation is Reshaping Our World Tech is No Longer an Industry; Every Industry is Tech

Sources (clockwise from centre top): Organization for Economic Co-operation and Development; Evercore ISI Investment Research; Goldman Sachs Global Investment Research; Deloitte; Euromonitor. For illustrative purposes only. The economic and market forecasts presented herein are for informational purposes as of the date of this presentation. There can be no assurance that the forecasts will be achieved. Please see additional disclosures at the end of this presentation.

Technology is impacting all

aspects of our everyday lives

Consumer Trends Up to 45% of global retail industry revenue will be generated by e-commerce by 2025

Manufacturing By 2020, 75% of manufacturing operations worldwide could use 3D-printed tools for the production of finished goods

Big Data The average household will own 50 internet connected

devices by 2022

Financial Services Mobile payment volumes

in the U.S. are expected to triple by 2021

Health Care The Human Genome Project cost $2.7bn

and took 15 years to complete. Within the next 5 years, it will cost $100

and take less than a day.

2

GSAM Has Identified Five Key Transformational Changes Underpinned by Structural Growth & Broadly Defined

Source: GSAM. For illustrative purposes only.

Finance Reimagined Digitization of Finance Asset Management Makeover Blockchain

Data-Driven World Artificial Intelligence Big Data Cybersecurity Internet of Things Data InfrastructureNew Age Consumer

E-Commerce Social Media Online Gaming Online Music & Video Evolution of Education Health & Wellness Experiences Over Goods

Human Evolution Precision Medicine Robotic Surgery Genomics Life Extension Digital Health

Manufacturing Revolution Robotics 3D Printing Future Mobility Drones Clean Energy

5 Transformational

Changes 25

Innovations

3

Data-Driven World The Proliferation of Data is a Defining Theme of the 21st Century

Sources: 1 Goldman Sachs Global Investment Research. The economic and market forecasts presented herein are for informational purposes as of the date of this presentation. There can be no assurance that the forecasts will be achieved. Please see additional disclosures at the end of this presentation. The data prepared by Goldman Sachs Global Investment Research is not a product of GSAM. The views and opinions expressed may differ from those of GSAM or other departments or divisions of Goldman Sachs and its affiliates. Please see additional disclosures.

0

20

40

60

80

100

120

140

160

180

2010 2013 2016 2019 2022 2025

Zetta

byte

s of

Dat

a

Annual Data Generation Worldwide

The Evolution of the “Internet of Things” The Explosion of Data1

4

Data-Driven World Today’s Investment in Data Infrastructure is Enabling the Next Wave of Innovation

5G Efforts to Scale are Underway1Inflection of Artificial Intelligence (“AI”) and

Machine Learning (“ML”)2

5G Connected Devices (bn)

Population Coverage (%)

0

5

10

15

20

25

30

35

40

0

0.2

0.4

0.6

0.8

1

1.2

2020 2021 2022 2023 2024 2025

5G Connections Population Coverage

1950’s 1980’s 2010’s

Deep Learning

Machine Learning

Artificial Intelligence

Sources: 1 GSAM, 2 GSAM. Artificial Intelligence = enables computers to exhibit human-like behavioral traits including knowledge, reasoning, common sense, learning, and decision making. Machine Learning = branch of AI that enables computers to learn from data on their own. Deep Learning = branch of ML that trains computers to perform human-like tasks. The economic and market forecasts presented herein are for informational purposes as of the date of this presentation. There can be no assurance that the forecasts will be achieved.

5

Sources: 1 Evercore ISI Investment Research, 2 Gartner. The data prepared by Goldman Sachs Global Investment Research is not a product of GSAM. The views and opinions expressed may differ from those of GSAM or other departments or divisions of Goldman Sachs and its affiliates. Please see additional disclosures. The economic and market forecasts presented herein have been generated by GSAM for informational purposes as of the date of this presentation. They are based on proprietary models and there can be no assurance that the forecasts will be achieved. Please see additional disclosures at the end of this presentation.

The Evolution of Payments Towards Electronic1

0%

20%

40%

60%

80%

100%

2006 2008 2010 2012 2014 2016

Paper

Cards

Electronic

U.S. Purchase Volume

Finance Reimagined Finance is Becoming Increasingly Digital and Blockchain Technology is Here to Stay

Blockchain Business Value2

$ 0

$ 500

$ 1,000

$ 1,500

$ 2,000

$ 2,500

$ 3,000

$ 3,500

$3.1 trillion

$176 billion$21 billion$4 billion

2017 2020 2025 2030

6

Human Evolution The Genome Revolution Means Customized Health Solutions

Sources: 1 National Human Genome Institute, GSAM, Goldman Sachs Global Investment Research, 2 GSAM, Personalized Medicine Coalition, FDA. As of October 2016. Moore's Law is the observation made by Gordon Moore that the number of transistors on a chip doubles every year while the costs are halved.

…Means Healthcare is no Longer a ‘One Size Fits All’ Model2

The Lower Cost of Reading Genetic ‘Instructions’ 1…

$1,000

$10,000

$100,000

$1,000,000

$10,000,000

$100,000,000

'01 '03 '05 '07 '09 '11 '13 '15

Cost per Genome

Moore's Law

0

20

40

60

80

100

120

140

2008 2010 2012 2014 2016

Personalized medicine apply genomic insights to select the most effective and tailored treatment

Number of Personalized Medicines

7

Human Evolution The Use of Technology in Healthcare Can Improve Outcomes

Sources: ¹ PWC. 2 Mega, National Center for Health Statistics, data for the US. The economic and market forecasts presented herein are for informational purposes as of the date of this presentation. There can be no assurance that the forecasts will be achieved. Please see additional disclosures at the end of this presentation.

…Means Better Informed Decisions and Reduced Medical Errors2

0 200 400 600

Nephritis

Influenza

Diabetes

Alzheimer's Disease

Stroke

Accidents

Respiratory Disease

Medical Error

Cancer

Heart Disease

‘000s

Annual Casualties By Cause In The US

Use of Technologies In Healthcare1…

8

Manufacturing Revolution Innovation Leads to Higher Productivity

1 Source: Bain. Notes: Labor productivity measured in dollars of gross output per employee; projections do not include baseline forecasts of labor productivity growth Sources: US Bureau of Economic Analysis; US Bureau of Labor Statistics; Bain Macro Trends Group analysis, 2017. The economic and market forecasts presented herein are for informational purposes as of the date of this presentation. There can be no assurance that the forecasts will be achieved. Please see additional disclosures at the end of this presentation.

Innovation and Automation Across Industries Will Drive a Resurgence in Productivity1

55

39

30

25

10

0

10

20

30

40

50

60

Manufacturing Utilities Average Finance and insurance Educational services

Perc

enta

ge

Automation-driven productivity growth 2015-2030

9

Manufacturing Revolution The Digital and Physical Worlds are Converging

The economic and market forecasts presented herein are for informational purposes as of the date of this presentation. There can be no assurance that the forecasts will be achieved.

0

10

20

30

40

50

60

70

80

2000 2005 2010 2015 2020E 2025E

Industrial Commercial Military Personal

Global Robotics Market ($bn)

7.4 10.8

15.1

26.9

42.9

66.9

Growth in Robotics is Broad-based and Accelerating

10

New Age Consumer “Digital Natives”: Easy Access to Technology Has Changed How We Interact

Sources: 1 Bloomberg, 2Euromonitor, GS Global Investment Research, and GSAM. Populations are listed in millions. Any reference to a specific company or security does not constitute a recommendation to buy, sell, hold or directly invest in the company or its securities. For illustrative purposes only.

Smartphone Penetration Has Increased >10x Since 20081…

%

... and E-commerce Penetration is Set to Boom2

11

New Age Consumer “Smart Consumers”: New Digital Platforms and Evolved Preferences Have Revolutionised Consumption

Sources: 1 McCrindle, Statista, U.S. Census Bureau Current Population. Populations are listed in millions. 2 PWC. For illustrative purposes only. The economic and market forecasts presented herein are for informational purposes as of the date of this presentation. There can be no assurance that the forecasts will be achieved. Please see additional disclosures at the end of this presentation.

Access vs. Ownership Has Redefined All Businesses2Social Media ‘Populations’ Have Overtaken Key Countries1

Popu

latio

n (M

n)

2013 2025

$335bn $335bn

$240bn

$15bn

12

Descriptions of Transformational Changes

Data-Driven World Artificial Intelligence – companies that may benefit from the development of ‘Artificial Intelligence’ (the ability of a machine to perform cognitive tasks typically associated with human brains such as perception, reasoning, learning, interacting with the environment, and problem solving). Big Data – companies that may benefit from the development of ‘Big Data’ technologies (the software associated with the storage, processing and analytics of large-scale structured and unstructured data). Cybersecurity – companies that may benefit from the need to secure data in an online world (ensuring the integrity, confidentiality and availability of information). Internet of Things – companies that may benefit from the development of the ‘Internet of Things’ (the collection of consumer and industrial network-connected devices beyond traditional appliances). Data Infrastructure – companies that may benefit from the expansion in physical infrastructure to transmit and store data (including the hardware components needed for the transmission and storage of large quantities of data, such as routers and switches, wired and wireless transmission networks, and high-density storage).

Finance Reimagined Digitization of Finance – companies that may benefit from the digitization of traditional financial services (including the support and delivery of payments, lending and insurance). Asset Management Makeover – companies that may benefit from the bifurcation of strategies in the asset management industry (the movement of assets into either low cost, often passive, investments such as exchange-traded funds (“ETFs”) and index funds, or into high cost, often complex, investments such as private equity and hedge funds). Blockchain – companies that may benefit from the development of blockchain technology (the technology underlying distributed ledgers, applicable to payments, currencies and to other fields and industries that depend on a trusted intermediary).

Human Evolution Precision Medicine – companies that may benefit from the development of precise medical treatments or techniques (that are either physically precise, targeting a specific group or type of cells, or tailored to a group of patients). Robotic Surgery – companies that may benefit from the development of robotic surgery (technology that enables minimally invasive surgery, as well as the use of miniaturized surgical instruments and robotic systems to assist in surgical procedures). Genomics – companies that may benefit from the development of genomics (the study of genomes, including genome sequencing and bioinformatics, and its application to healthcare as genomic medicine and pharmacogenomics, including gene therapy, gene editing and the use of biomarkers). Life Extension – companies that may benefit from the long-term demographic shift towards an older population (including medical products and services geared towards managing the health of an ageing population). Digital Health – companies that may benefit from growth in demand for consumer healthcare devices and procedures that enhance the daily life of the consumer.

Manufacturing Revolution Robotics – companies that may benefit from the increased sophistication of robotics (the ability of a machine to perform physical tasks that previously either were not possible or required a human) used in the manufacturing process. 3D Printing – companies that may benefit from the development of 3D printing (manufacturing a three-dimensional object from a digital design) and its application in manufacturing. Future Mobility – companies that may benefit from the development of new methods of mobility (road vehicles that apply either electrification or autonomous driving capabilities or both). Drones – companies that may benefit from the development of drones (aerial, land or sea-based unmanned vehicles, either remotely operated or autonomous, used in military, consumer or industrial applications). Clean Energy – companies that may benefit from the development of clean energy sources (energy from renewable resources such as solar, wind and biofuel, as well as battery technology needed for the storage of intermittent power sources).

New Age Consumer E-Commerce – companies that may benefit from the expansion of e-commerce (the purchase and delivery of goods and services over the internet).Social Media – companies that may benefit from the development of social media (online platforms that connect people and allow members to interact with one another).Online Gaming – companies that may benefit from the popularity of online gaming (a game that is either partially or primarily played through the internet, including video games and games that may have traditionally been delivered in person, suchas betting). Online Music & Video – companies that may benefit from demand for music and videos delivered over the internet (the digital distribution of music and videos).Evolution of Education – companies that may benefit from the evolution of education (the delivery of educational materials over the internet, such as interactive and non-interactive multimedia content, the streaming of lectures and the delivery ofteaching and tutoring services online, and for-profit education services in emerging markets). Health & Wellness – companies that may benefit from consumer interest in health and wellness (consumer health-related goods and services outside of traditional healthcare, for example relating to nutrition, exercise and health tracking).Experiences Over Goods – companies that may benefit from demand by consumers for experiences relative to goods (demand for experiences and the goods that relate to those experiences, relative to the demand for physical goods unrelatedto those experiences).

13

Disclosures

This material is provided at your request for educational purposes only. It is not an offer or solicitation to buy or sell any securities.

Views and opinions expressed are for informational purposes only and do not constitute a recommendation by GSAM to buy, sell, or hold any security. Views and opinions are current as of the date of this presentation and may be subject to change, they should not be construed as investment advice.

This information discusses general market activity, industry or sector trends, or other broad-based economic, market or political conditions and should not be construed as research or investment advice. This material has been prepared by GSAM and is not financial research nor a product of Goldman Sachs Global Investment Research (GIR). It was not prepared in compliance with applicable provisions of law designed to promote the independence of financial analysis and is not subject to a prohibition on trading following the distribution of financial research. The views and opinions expressed may differ from those of Goldman Sachs Global Investment Research or other departments or divisions of Goldman Sachs and its affiliates. Investors are urged to consult with their financial advisors before buying or selling any securities. This information may not be current and GSAM has no obligation to provide any updates or changes.

Economic and market forecasts presented herein reflect a series of assumptions and judgments as of the date of this presentation and are subject to change without notice. These forecasts do not take into account the specific investment objectives, restrictions, tax and financial situation or other needs of any specific client. Actual data will vary and may not be reflected here. These forecasts are subject to high levels of uncertainty that may affect actual performance. Accordingly, these forecasts should be viewed as merely representative of a broad range of possible outcomes. These forecasts are estimated, based on assumptions, and are subject to significant revision and may change materially as economic and market conditions change. Goldman Sachs has no obligation to provide updates or changes to these forecasts. Case studies and examples are for illustrative purposes only.

Although certain information has been obtained from sources believed to be reliable, we do not guarantee its accuracy, completeness or fairness. We have relied upon and assumed without independent verification, the accuracy and completeness of all information available from public sources.

The Motif Data-Driven World Index is designed to deliver exposure to companies with common equity securities listed on exchanges in certain developed markets that may benefit from the on-going rapid increase in electronically recorded data in the world and its impact on the lifecycle of data delivery and processing. The Motif Finance Reimagined Index is designed to deliver exposure to companies with common equity securities listed on exchanges in certain developed markets that may benefit from the on-going structural changes in the support and delivery of financial services. The Motif Human Evolution Index is designed to deliver exposure to companies with common equity securities listed on exchanges in certain developed markets that may benefit from the development of new knowledge, medicines and technologies for the medical treatment of the human condition, from birth to end-of-life care. The Motif Manufacturing Revolution Index is designed to deliver exposure to companies with common equity securities listed on exchanges in certain developed markets that may benefit from the on-going technology-driven transformation of the manufacturing industry. The Motif New Age Consumer Index is designed to deliver exposure to companies with common equity securities listed on exchanges in certain developed markets that may benefit from the on-going structural shifts in the consumer market due to changes in demographics, technology and preferences.

14

Disclosures

Confidentiality

No part of this material may, without GSAM’s prior written consent, be (i) copied, photocopied or duplicated in any form, by any means, or (ii) distributed to any person that is not an employee, officer, director, or authorized agent of the recipient.

© 2019 Goldman Sachs. All rights reserved. Compliance Code: 167989-OTU-980149 Date of first use: 5/20/2019

N e w M e x i c o P E R A

WILSHIRE ASSOCIATES

May 2019

Thomas Toth, CFA – Managing DirectorRose Dean, Managing Director

C r e d i t P o r t f o l i o R e v i e w


• Balance of exposures to economic growth and income opportunities

– Growth opportunities driven by improving economic fundamentals

– Income generation with current yields above government securities andinvestment grade fixed income

– Opportunities to generate alpha through idiosyncratic exposure in both liquidand private markets

– Broad opportunity set provides diversification benefits to the Total Fund


St rategic Rat ionale for Credi t Assets



Key Credi t RisksRisk Category Elements of Consideration

Macro-economic / Cyclicality • Credit risk (corporate debt)• Default rate (distressed debt)

Credit Risk

• Default rate• Loss rate• Recovery rate• Covenants• Private equity sponsorship

Interest-rate Risk • Fixed vs. floating• Duration

Illiquidity • Size• Illiquidity premium

Manager selection• Market efficiency & ability to differentiate• Sourcing advantage• Strategy complexity & due diligence insight

Regulatory • Bank lending activity


• 2015 was a year of transition to a dedicated exposure to Credit oriented portfolios

– Previously, credit exposure was consolidated within Core Plus Fixed Income manager mandates

– Added dedicated High Yield, Emerging Market Debt, and Multi Sector Credit mandates

• Change in allocation allows the portfolio to be managed in a more granular fashion and assumes control of exposures outside of core fixed income/risk mitigation assets

• Following slides detail the performance evolution of the total Credit portfolio


Credi t Or iented Por t fo l io Per formance



Credit Oriented Fixed Income Performance


• Portfolio Positioning

– Defensively positioned from a market exposure (beta) perspective

» Beneficial in 2018 credit market sell off, but will negatively impact portfolio ascredit spreads tightened to start 2019

– Reduced exposure to EMD as part of rebalancing and adjusted mandate to utilizetactical risk budgeting component to increase/decrease risk as opportunitiesexpand/contract

– Remains diversified across credit opportunity set

» Opportunities on both the liquid and illiquid side continue to be evaluated toimprove portfolio outcomes

» Case for holding dry powder for Distressed and Special Situation opportunitieshas gotten stronger as economic cycle progresses

– Credit portfolio underweight to market sensitivity (beta) seems prudent at this point inthe cycle


Credi t Or iented Por t fo l io Summary

LIQUID CREDIT

LIQUID CREDIT MARKETENVIRONMENT



Non- Investment Grade Credi t

Data sources: 1. S&P, Neuberger Berman2. BofAML, Neuberger Berman



Non- Investment Grade Credi t

Data sources: S&P, BofAML, Neuberger Berman

Yield Spread between Loans and High Yield

• Recent performance supported by more accommodating Federal Reserve outlook, improving commodity prices and limited new issue supply

• Earnings growth may slow but fundamentals appear stable and defaults are not projected to pick up

• Yield spread of leveraged loans vs. high yield are low relative to the last 8 years on higher demand for fixed rate products (high yield)

• Leverage and interest coverage metrics have improved for bank loans



Secur i t ized Credi t

Data sources: Voya Investment Management

Correlations of Securitized Sectors vs. Other Asset Classes

• In addition to larger mortgage backed security sector, securitized market includes a number of sub-sectors to enhance diversification opportunities in the broader Credit portfolio

Senior Loans

US High Yield

IG Corporates Treasuries

US Aggregate S&P 500 CLOs

Agency RMBS ABS CMBS

Securitized Credit

Non-Agency RMBS

Senior Loans 100% 81% 27% -34% -9% 62% 80% -17% -6% 44% -11% 40%

High Yield 81% 100% 51% -17% 14% 72% 66% 6% 8% 49% 11% 42%

IG Corporates 27% 51% 100% 67% 87% 9% 22% 69% 66% 72% 72% 64%

Treasuries -34% -17% 67% 100% 93% -46% -26% 83% 82% 48% 83% 42%

US Aggregate -9% 14% 87% 93% 100% -22% -8% 91% 83% 65% 92% 52%

S&P 500 62% 72% 9% -46% -22% 100% 48% -23% -30% 17% -20% 7%

CLOs 80% 66% 22% -26% -8% 48% 100% -19% -9% 16% -16% 48%

Agency RMBS -17% 6% 69% 83% 91% -23% -19% 100% 75% 55% 99% 34%

ABS -6% 8% 66% 82% 83% -30% -9% 75% 100% 66% 78% 42%

CMBS 44% 49% 72% 48% 65% 17% 16% 55% 66% 100% 63% 54%

Securitized Products -11% 11% 72% 83% 92% -20% -16% 99% 78% 63% 100% 36%

Non-Agency RMBS 40% 42% 64% 42% 52% 7% 48% 34% 42% 54% 36% 100%



Secur i t ized Credi t

Data sources: Bloomberg, JP Morgan, Brown Brothers Harriman

• The universe can be further broken down into ‘non-traditional’ securitized product which have seen significant growth over the past 10 years



Emerging Market DebtSpread Over Treasuries

Data sources: JP Morgan, Bloomberg Barclays, Neuberger Berman

• Spreads on investment grade emerging market debt compare favorably to developed market investment grade credit

• Below investment grade emerging market debt provides an elevated pick up relative to U.S. high yield


This material contains confidential and proprietary information of Wilshire Associates Incorporated (Wilshire), and is intended for the exclusive use of the person to whom it is provided. It may not be disclosed, reproduced or redistributed, in whole or in part, to any other person or entity without prior written permission from Wilshire. Third party information contained herein has been obtained from sources believed to be reliable. Wilshire gives no representations or warranties as to the accuracy of such information, and accepts no responsibility or liability (including for indirect, consequential or incidental damages) for any error, omission or inaccuracy in such information and for results obtained from its use. Information and opinions are as of the date indicated, and are subject to change without notice.

This material is intended for informational purposes only and should not be construed as legal, accounting, tax, investment, or other professional advice.

This report may include estimates, projections and other "forward-looking statements." Due to numerous factors, actual events may differ substantially from those presented.

Wilshire® is a registered service mark of Wilshire Associates Incorporated, Santa Monica, California. All other trade names, trademarks, and/or service marks are the property of their respective holders.

Copyright © 2019 Wilshire Associates Incorporated. All rights reserved.


IMPORTANT INFORMATION

DISCLOSURE AUTHORIZED



N e w M e x i c o P E R A

WILSHIRE ASSOCIATES

May 2019

Thomas Toth, CFA – Managing DirectorRose Dean, Managing Director

R e f e r e n c e P o r t f o l i o R e c o m m e n d a t i o n


• Reference Portfolio should:

– Be a simple and low cost portfolio that could be implemented passively

– Be diversified

– Reflect an appropriate risk level for PERA

– Take into account PERA’s long term investment horizon

– Be relevant to PERA as a global investor


Reference Por t fo l io Design


• Used as a benchmark to determine if utilization of additional asset classes and/or taking on illiquidity risk provides benefit

– Return enhancement

– Risk reduction

• Reference portfolio concept meets the objectives of a good benchmark– Predefined, investable, unambiguous, measurable, and appropriate

• Serves as a clear and objective means of evaluating performance over a long-term time horizon– Long-term time horizon is important to remember as the valuation lags introduced

by illiquid investments will introduce deviations when comparing the Total Fund’s actual performance to that of the Reference Portfolio

» Ex. – positive impact in Q4 2018 as liquid markets sold off sharply and a negative impact in Q1 2019 as liquid markets rallied strongly


Use for a Reference Por t fo l io


• Focus on most liquid markets with inexpensive passive implementation options

– Global Equity provides exposure to global economic growth

– Cash provides risk mitigation

– Core Fixed Income provides income and risk mitigation

– Treasury Inflation Protected Securities provides a hedge against inflation along with some income

• Optimization process generates a series of portfolios with the highest return for a specified risk level


Reference Por t fo l io Construct ion

March 31, 2019 ACA (10 Years) Global Equity Cash Core Fixed Income TIPS

Expected Return 6.70 2.45 3.40 2.70

Risk 17.05 1.25 5.15 6.00

Cash Yield 2.55 2.45 3.55 3.10

Correlation

Global Equity 1.00

Cash -0.07 1.00

Core Fixed Income 0.20 0.19 1.00

TIPS 0.00 0.20 0.60 1.00



What Risk Level is Appropr ia te?

Portfolio AGlobal Equity 30%Cash 18Core Bond 52%

Portfolio BGlobal Equity 58%Core Bond 42%

Portfolio CGlobal Equity 85%Core Bond 15%

Current Portfolio

• Relative to analysis last year, rising short term interest rates make cash attractive for lower risk portfolios, but optimizer moves towards core bonds at PERA risk level

• TIPS are not preferred in the optimization



Reference Por t fo l io Simulat ions – 1 Year








• Recommend utilizing a Reference Portfolio that targets similar total risk level as the current PERA portfolio– Indicative of the risk tolerance of the Board

– Return seeking, but cognizant of continued risk concentration

• The PERA’s current portfolio has an expected risk of 10.2%, inclusive of Beta risk, Allocation, and Selection active risk

• Recommend maintaining Reference Portfolio weights:


Reference Por t fo l io Recommendat ion

Asset Class RecommendedWeight

Appropriate Benchmark

Global Equity 58% MSCI AC World IMI

Core Fixed Income 42% Barclays U.S. Aggregate


This material contains confidential and proprietary information of Wilshire Associates Incorporated (Wilshire), and is intended for the exclusive use of the person to whom it is provided. It may not be disclosed, reproduced or redistributed, in whole or in part, to any other person or entity without prior written permission from Wilshire. Third party information contained herein has been obtained from sources believed to be reliable. Wilshire gives no representations or warranties as to the accuracy of such information, and accepts no responsibility or liability (including for indirect, consequential or incidental damages) for any error, omission or inaccuracy in such information and for results obtained from its use. Information and opinions are as of the date indicated, and are subject to change without notice.

This material is intended for informational purposes only and should not be construed as legal, accounting, tax, investment, or other professional advice.

This report may include estimates, projections and other "forward-looking statements." Due to numerous factors, actual events may differ substantially from those presented.

Wilshire® is a registered service mark of Wilshire Associates Incorporated, Santa Monica, California. All other trade names, trademarks, and/or service marks are the property of their respective holders.

Copyright © 2019 Wilshire Associates Incorporated. All rights reserved.

170445 E0318


IMPORTANT INFORMATION


NM Public Employees Retirement AssociationCash Flow Projection - FY 19

July August September October November December January February March April May June

Month Beginning Cash, BNYM $154 $104 $330 $147 $133 $135 $151 $157 $168 $179 $190 $201

Uses of Cash

Illiquid Asset Capital Calls PE, RE, RA, Credit 85 105 111 97 86 109 117 80 80 80 80 80 Private Asset Drawdowns

Asset Class PurchasesLiquid Asset Purchases 213 348

Total Benefit Payments 99 100 100 100 100 100 102 100 100 100 100 100Benefit Payments (BNYM) 55 63 57 62 53 57 55 50 50 50 50 50

Benefit Payments (STO) 44 36 43 38 47 43 46 50 50 50 50 50Refunds 4 6 4 5 5 5 3 4 4 4 4 4

Operational Expense 1 1 1 2 5 1 2 2 2 2 2 2Other 0 0 0 0 0 0 0

Sources of CashAsset Class Sales

Liquid Asset Redemptions 0 346 163 110 100 485 135 100 100 100 100 100

Illiquid Asset Distributions 88 43 31 29 40 42 41 40 40 40 40 40 Private Asset DistributionsIlliquid Asset Redemptions 0 0 0 4 0 0 2 Hedge Fund/Portable Alpha

Employee / Employer Contributions 50 63 38 54 53 46 53 50 50 50 50 50Other 2 4 4 2 1 2 1 1 1 1 1 1 Suspense Account / Corporate Action / Overlay

Month Ending Cash, BNYM $104 $330 $147 $133 $135 $151 $157 $168 $179 $190 $201 $212

Corporate Action 4 5 3 3 3 2 2 4 4 4 4 4 Overlay Cash 90 93 89 82 87 81 93 90 90 90 90 90Month Ending Cash, STO 18 38 28 36 31 28 29 20 20 20 20 20

Month-End Capital AllocationsActual Target Var. Range

Global Equity 6,800 6,671 6,819 6,399 6,496 6,190 6,530 6,559 6,553 5,343 5,338 5,333 340 43.2% 35.5% 7.7% +/-5%Risk Reduction & Mitigation 3,195 3,440 3,236 3,197 3,218 3,187 3,230 3,242 3,239 2,935 2,932 2,929 43 21.4% 19.5% 1.9% +/-3%Credit Oriented Fixed Income 2,375 2,354 2,309 2,301 2,298 2,267 2,333 2,262 2,260 2,257 2,255 2,253 66 15.4% 15.0% 0.4% +/-4%Real Assets 3,145 3,139 3,173 3,032 3,013 2,915 2,989 3,015 3,013 3,010 3,007 3,004 74 19.8% 20.0% -0.2% +/-4%Multi-Risk Allocation 0 0 0 0 0 0 - 0 0 1,505 1,504 1,502 0 0.0% 10.0% -10.0% +/-4%STO Cash 18 38 28 36 31 28 29 20 20 20 20 20 2 0.2% 0.0% 0.2%

Total (net of cash flows) $15,534 $15,642 $15,565 $14,965 $15,055 $14,587 $15,111 $15,097 $15,084 $15,070 $15,056 $15,042 524 100.0% 100.0%

Month-End Percentage AllocationsFund Balance (less STO) $15,515 $15,604 $15,537 $14,929 $15,024 $14,559 $15,082 $15,077 $15,064 $15,050 $15,036 $15,022Global Equity 43.8% 42.8% 43.9% 42.9% 43.2% 42.5% 43.3% 43.5% 43.5% 35.5% 35.5% 35.5%Risk Reduction & Mitigation 20.6% 22.0% 20.8% 21.4% 21.4% 21.9% 21.4% 21.5% 21.5% 19.5% 19.5% 19.5%Credit Oriented Fixed Income 15.3% 15.1% 14.9% 15.4% 15.3% 15.6% 15.5% 15.0% 15.0% 15.0% 15.0% 15.0%Real Assets 20.3% 20.1% 20.4% 20.3% 20.1% 20.0% 19.8% 20.0% 20.0% 20.0% 20.0% 20.0%Multi-Risk Allocation 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 10.0% 10.0% 10.0%

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Actuals Projected

Current Month's Weights

Month's Activity

January Change in Value

Restructure: $55m residual proceeds from EM liquidation Rebalance: $80m to fund cash account - $18m REITS, $17m Listed Infra., $45m Liquid Credit


July August September October November December January February March April May June

Month Beginning Cash, BNYM $154 $104 $330 $147 $133 $135 $151 $157 $88 $99 $110 $121

Uses of Cash

Illiquid Asset Capital Calls PE, RE, RA, Credit 85 105 111 97 86 109 117 46 80 80 80 80 Private Asset Drawdowns

Asset Class PurchasesLiquid Asset Purchases 213 348

Total Benefit Payments 99 100 100 100 100 100 102 102 100 100 100 100Benefit Payments (BNYM) 55 63 57 62 53 57 55 57 50 50 50 50

Benefit Payments (STO) 44 36 43 38 47 43 46 45 50 50 50 50Refunds 4 6 4 5 5 5 3 5 4 4 4 4

Operational Expense 1 1 1 2 5 1 2 5 2 2 2 2Other 0 0 0 0 0 0 0 0


Liquid Asset Redemptions 0 346 163 110 100 485 135 0 100 100 100 100Illiquid Asset Distributions 88 43 31 29 40 42 41 30 40 40 40 40 Private Asset DistributionsIlliquid Asset Redemptions 0 0 0 4 0 0 2 1 Hedge Fund/Portable Alpha





Global Equity 6,800 6,671 6,819 6,399 6,496 6,190 6,530 6,715 6,623 5,400 5,396 5,391 185 44.0% 35.5% 8.5% +/-5%Risk Reduction & Mitigation 3,195 3,440 3,236 3,197 3,218 3,187 3,230 3,161 3,273 2,966 2,964 2,961 (69) 20.7% 19.5% 1.2% +/-3%Credit Oriented Fixed Income 2,375 2,354 2,309 2,301 2,298 2,267 2,333 2,335 2,284 2,282 2,280 2,278 1 15.3% 15.0% 0.3% +/-4%Real Assets 3,145 3,139 3,173 3,032 3,013 2,915 2,989 3,015 3,045 3,042 3,040 3,037 26 19.8% 20.0% -0.2% +/-4%Multi-Risk Allocation 0 0 0 0 0 0 0 - 0 1,521 1,520 1,519 0 0.0% 10.0% -10.0% +/-4%STO Cash 18 38 28 36 31 28 29 32 20 20 20 20 3 0.2% 0.0% 0.2%



100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%


Month's Activity

February Change in Value

Actuals Projected


July August September October November December January February March April May JuneMonth Beginning Cash, BNYM $154 $104 $330 $147 $133 $135 $151 $157 $88 $34 $45 $56

Uses of CashIlliquid Asset Capital Calls

PE, RE, RA, Credit 85 105 111 97 86 109 117 46 35 80 80 80 Private Asset DrawdownsAsset Class Purchases

Liquid Asset Purchases 213 348Total Benefit Payments 99 100 100 100 100 100 102 102 102 100 100 100

Benefit Payments (BNYM) 55 63 57 62 53 57 55 57 58 50 50 50 Benefit Payments (STO) 44 36 43 38 47 43 46 45 44 50 50 50

Refunds 4 6 4 5 5 5 3 5 4 4 4 4Operational Expense 1 1 1 2 5 1 2 5 1 2 2 2

Other 0 0 0 0 0 0 0 0 0


Liquid Asset Redemptions 0 346 163 110 100 485 135 0 0 100 100 100Illiquid Asset Distributions 88 43 31 29 40 42 41 30 38 40 40 40 Private Asset DistributionsIlliquid Asset Redemptions 0 0 0 4 0 0 2 1 1 Hedge Fund/Portable Alpha





Global Equity 6,800 6,671 6,819 6,399 6,496 6,190 6,530 6,715 6,774 6,671 6,562 6,474 59 44.1% 35.5% 8.6% +/-5%Risk Reduction & Mitigation 3,195 3,440 3,236 3,197 3,218 3,187 3,230 3,161 3,167 3,297 3,293 3,269 6 20.6% 19.5% 1.1% +/-3%Credit Oriented Fixed Income 2,375 2,354 2,309 2,301 2,298 2,267 2,333 2,335 2,336 2,300 2,297 2,294 1 15.2% 15.0% 0.2% +/-4%Real Assets 3,145 3,139 3,173 3,032 3,013 2,915 2,989 3,015 3,060 3,067 3,063 3,059 45 19.9% 20.0% -0.1% +/-4%Multi-Risk Allocation 0 0 0 0 0 0 0 0 - 0 100 199 0 0.0% 10.0% -10.0% +/-4%STO Cash 18 38 28 36 31 28 29 32 37 20 20 20 5 0.2% 0.0% 0.2%



100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Projected Actuals


Month's Activity

March Change in Value

Manager Selection Activity ReportMay 2019

Slide 2

Overview: Manager Selection Process

Slide 3

Manager Selection Pipeline (Liquid)

Allocation Stage 1 Stage 2 Stage 3 Stage 4 Stage 5

Global Core Fixed Income Risk Reduction

Completed Completed Completed Completed ApprovedSummary: Evaluation of Current Manager (contract expiration)

Total Fund Overlay

Total Fund Completed Completed Completed Completed ApprovedSummary: Risk Overlay/Structure Management (new mandate)

Slide 4

Allocation Stage 1 Stage 2 Stage 3 Stage 4 Stage 5

Contingent Capital Credit Completed ON HOLDSummary: Opportunistic Private Debt

(new mandate)

AgIS Capital Club FundReal Assets Completed In Process Summary: Value-Add Illiquid Farmland

(new mandate)

Petershill IVGlobal Equity Completed Completed Completed In ProcessSummary: Private Equity GP Stakes

(follow-on investment)

Montagu VIGlobal Equity Completed Completed Completed In Process Summary: European Buyout

(new mandate)

Rockwood Real Estate Partners XI Real Assets Completed Completed Completed Completed ApprovedSummary: Value-Add Illiquid Real Estate

(follow-on investment)

Manager Selection Pipeline (Illiquid)

Slide 5

Global Core Fixed Income

Slide 6

On March 13, 2019 the Alpha Team completed their diligence efforts and proposed utilizing the investmentmanagement services of Blackrock, Inc., for the Bloomberg Barclay’s Global Aggregate Mandate, replacingManulife as the current manager of that strategy due to a contract expiration.

The Alpha Team proposes utilizing Blackrock, Inc. at the current capital asset allocation weight of 2.5%, withflexibility around that as determined by near term rebalancing and cash flow considerations.

Summary of Proposal

Slide 7

RFI Overview: Scope of Work

• Discretionary investment management services for a global core fixed income mandate, at an approximatemandate size of $375 million.

• Products should exhibit relatively tight active risk versus the performance benchmark.• Broad guidelines for the mandate were included:

Core Global Aggregate Mandate Investment Objective Seek to outperform the Bloomberg Barclays

Global Aggregate Bond Index Hedged to US Dollar over a full market cycle, typically defined as 3-5 years, with limited performance deviation relative to the benchmark.

Benchmark Bloomberg Barclays Global Core Aggregate (Hedged)

Target Excess Return 25-75 bps Target Tracking Error 75 bps (Information Ratio between 0.3-1.0) Expected Turnover 20-40% Duration Limit Benchmark +/- 1 year Country/Currency/Sector Limits Consistent with target tracking error Non-Investment Grade Maximum Consistent with target tracking error, not to

exceed 15% Foreign Currency Limit Consistent with target tracking error, not to

exceed 15% in non-US dollar currency exposure (i.e. portfolio must be a minimum of 85% hedged to USD)

Slide 8

• An RFI was issued on February 22, 2018, to 9 managers, all of whom were:

a) deemed capable of managing a “passive global core bond” mandate, AND

b) “managers in good standing” (i.e., currently managing some other or similar mandate for NMPERA).

• Wilshire and Staff screened and ranked the 9 respondents using quantitative and qualitative data.Quantitative data ranking as most important were ability to provide beta=1 exposure, with the smallestamount of tracking error, and lowest fee, given the purely “on benchmark” exposure NM PERA seeks.

• Three managers were selected as “top picks” given the quantitative metrics mentioned above.

• The top three managers were then evaluated based on:

a) familiarity with the team, and operational suitability related to their ability to execute NMPERA’s standard professional service agreement;

b) ability to work with our custody bank to open country accounts; and

c) ability to take the existing Global Core book in-kind.

• Based on the screening and analysis, stated above, Blackrock was selected as a finalist for this mandate.

RFI Overview: Selection of Semi-Finalists

Slide 9

Highlights

Beta =1 philosophy and process

Target:

Fees:

This would be additional capitalto a Blackrock, Inc., a firm andteam who also manages NMPERA’s Domestic AGG mandate.

Risk Culture and Philosophy

Consistency and repeatable process

Finalist: Blackrock, Inc.Investment Philosophy

Edge

PRIVATE AND CONFIDENTIAL

Slide 10

Finalist: Blackrock Inc. Beta-1 Philosophy


Slide 11

Finalist: Blackrock Inc. Beta-1 Results


Slide 12

Finalist: Blackrock Inc. Beta-1 Results


Slide 13

Blackrock

Flat Fee

Base Fee bp

Minimum $

Finalist: Blackrock Inc. Fee Review

Proposed fee schedule:

Flat annual fee applied to the average quarter-end values


Slide 14

Total Fund Overlay

Slide 15

On May 3, 2019 the Alpha Team completed their diligence efforts and proposed hiring Legal and GeneralInvestment Management America (“LGIMA”) for Total Fund Overlay Services

The objective will be to identify and manage “Structure Risk” (i.e. “Off Benchmark Risk”)

a) Identify/quantify “Structure Risk”b) Identify/quantify that which is Intentionalc) Identify/quantify that which is Unintentional

1) Decrease /’save’ liquid only structure risk (measured in tracking error)

2) “Re-spend” the risk “saved” in 1) via optimized TAA with 6 month – 18 month horizon (short-term)while being cognizant of long term active decisions and SAA (10 year horizon)

3) Translate PERA SAA from Asset Class centric view to macro factor and style premia view; and helpcodify the classification such that PERA can reorient its risk systems to identify macro and styleexposure ‘load’s versus Policy (i.e., are we long Value, short Trend etc.). This is the next step in ourevolution from allocators of capital to allocators of risk

Summary of Proposal

Slide 16

• The Total Fund Overlay RFP (NM-INV-001-FY19) was issued on August 3, 2018

• The services requested was for discretionary investment management services for total fundoverlay services. PERA sought proposals for optimization of the structure decisions andportfolio drift, or systematic sources of risk relative to the benchmark target allocations, notto exceed some portion of the 65 bps tracking error budget. Proposals should identify howthe strategy would optimize structure decisions and portfolio drift through a risk allocationlens, including but not limited to the following:

1. Expected excess return

2. Expected tracking error3. Expected information ratio4. Systematic risk exposures5. Expected max drawdown, Conditional Value-at-Risk (“CVaR”), tail risk, etc.6. Expected correlation of strategy returns to NM PERA Strategic Asset Allocation betareturns7. Stress testing8. Scenario analysis

• Ten firms responded by the due date of September 7, 2018

RFP Process:Overview

Slide 17

• A 2nd DDQ was sent to five firms in October 2018

• The DDQ was sent to further clarify the firms responses in regards to the mandate

• Firms were reviewed based on the following criteria

• Institutional Quality

• Ability to provide a customized product

• Risk management systems and expertise

• Understanding of PERA risk budget

• A 3rd DDQ was sent to three firms prior to Santa Fe presentations

• The scope was changed from Risk Parity/Portable Alpha/Total Fund Overlay to aprovider for Total Fund Overlay

• The three semi-finalists provided presentations to staff and consultants on January 30, 2019in the Santa Fe PERA office

• Two Finalists were chosen based on these presentations

Selection of Semi-Finalists:Overview

Slide 18

• Staff and Wilshire attended on-sites with LGIMA on March 7, 2019 in Chicago, IL andRussell Investments on March 8, 2019 in Seattle, WA

• The onsite presentations were focused on the review of the Finalist’s

• risk management system capabilities

• TAA capabilities

• Customized products

• PERA risk budget

• Staff and Wilshire proposes hiring LGIMA for their fully customizable Total Fund Overlayproduct

• Albourne provided an Operational Due Diligence review with an A rating

Finalist Interviews:Overview

Slide 19

Highlights

Costs:

Performance Target:

Finalist: LGIMAOrganization

Investment Team

Investment Strategy

The Total Fund Overlay aims to capture unintended structure risk and re-spend that risk across 25 various tactical asset allocation strategies to enhance returns, reduce correlation and mitigate tail risk. The Unconstrained Multi-Asset Total Return strategy includes fundamental, value, carry, market dynamics, diversification and tail risk trades and LGIMA’s existing factor model set includes Market, Credit, Duration, Oil and Dollar factors, which can be further developed through discussions with PERA.

Edge


Slide 20

Finalist: LGIMATeam Structure


Slide 21

• Identify Structure Risk Across Total Portfolio

Proposed Solution (Part 1): Structure Management


Slide 22

Every OffBenchmark

Active Decision Entails 3 Parts

Sell the Policy index(short)

Buy the Selection index

(long)

Buy the Active Return (+/-) around the

Selection index

Structure / Allocation / OffBenchmark Riske.g., Short ACWI, Long EAFEe.g., Short GHY, Long Lev Loans

Selection Risk i.e., Manager Active Return perunit of Active Risk Given vsSelection Index

Proposed Solution (Part 1): Structure Management

Slide 23

• Re-spend the risk in TAA (more optimal long-term risk/reward)

• LGIMA TAA has more optimal IR track record.

• Objective 1 : TAA return/risk ratio .5 or better

• Target 2 : Zero to negative correlation with SAA (smoother compounding pathover 10 years, without loss of 10-year assumed structure risk premia of SAA)

Proposed Solution (Part 2): Unconstrained TAA

Slide 24

Proposed Solution (Part 2): Unconstrained TAA


Slide 25

Additional synergy Alpha team can size, make active decision on just the selection active return/risktradeoff without constraint to allocation/structure/off benchmark mismatch. This allows for better(lesser constrained) optimization of alphas while staying closer to Policy

Eliminate Structure Risk

-TE/ +/-P&L

Re-spend risk via TAA

+TE, +/-P&L

Tracking error is neutral or less and cumulative

P&L is positive and diversifying versus Policy

and SAA

Proposed Solution: Structure Management + Unconstrained TAA

Slide 26

Proposed fee schedule (2 separate components):1) Management fee for structure management2) Carry on Unconstrained TAA

1) Management Fee 2) Carry

Additional Points:

• Structure risk overlay consultative review between PERA and LGIMA• TAA structured as separate account and bespoke to PERA SAA• TAA Zero correlation to SAA major objective• Directional longs limited with majority relative value trades

Finalist: LGIMAFee Review


Slide 27

Rockwood Real Estate Partners XI

Slide 28

On May 3, 2019 the Alpha Team completed their diligence efforts and proposed a commitment up to $50million to Rockwood Capital Real Estate Partners Fund XI (“Rockwood”), an illiquid real estate partnership,focusing on real estate properties across the U.S. The Fund will focus primarily on office and other workspace,multifamily residential, retail, and hotel assets, and will target investments in large, knowledge-driven marketssuch as the San Francisco Bay Area, Seattle, New York, Los Angeles, Boston and Washington, D.C. Rockwoodwill seek to add value through active asset management, such initiatives include: repositioning, re-leasing,redeveloping and/or development, and will endeavor to assemble and manage the Fund using their “bucket”portfolio construction approach through which each investment is classified, and reclassified over time, basedon its risk and “speed-to-income”. The Fund will target a net IRR of 12-14%, and will seek to commit toapproximately 20-40 properties over their 3 year investment period.

A commitment to Rockwood would be a follow-on investment for NM PERA, who previously committed $20million to Fund VIII in 2008, $35 million to Fund IX in 2012, $60 million to Fund X in 2015, and $150million to New Rock in 2017.

This presentation is based on due diligence material and data obtained by the investment division and consultant, directly from the manager, and focuseson the strategy of the recommended manager as it fits within the current portfolio. Additionally, PERA defers to the consultant’s primary diligence onmatters relating to the quality and sufficiency of the fund’s back office, compliance, and other operational matters.

Proposal

Slide 29

• PERA and Rockwood maintain a successful relationship, dating back to2008, which has contributed to favorable strategy diversification andmeaningful outperformance, as compared to the portfolio’s policy index;5.76% direct alpha and 1.13 KS PME, net of fees performance for PERA’spositions in funds VIII – X.

Existing Relationship

• The Rockwood principals have worked together for decades, initially asreal estate investment managers for high net worth families and currentlyas commingled fund and separate account managers for an expanding setof global institutional investors Rockwood possesses a deep,interdisciplinary team with experience that spans multiple real estatecycles. PERA’s access to such experienced professionals and their extendednetwork provide a strong strategic advantage when allocating across RealEstate opportunities.

Experienced Team

• Rockwood’s team approach, and a history of developing staff by focusingon their career path, and affording them the opportunity to take ondifferent roles and responsibilities over time, aligns well with PERA’sinternal views. Philosophically, the founding partners have created asuccessful, sustainable privately held firm, with a reputation for bothintegrity and superior real estate investment management performance.

Culture

• Rockwood’s established reputation, with investors, and with prospectivepartners in joint venture real estate, has been widely recognized. They areknown for being a trustworthy, open partner with the best in class businesspractices and a high level of integrity, which helps provide access tocapital, and to attractive investment opportunities.

Firm Pedigree

Reasons to Invest

Slide 30

Firm Summary: Rockwood XI

Firm Rockwood Capital, LLC Founded 1995

Locations• Headquartered in New York, NY• Additional locations: San Francisco, CA,

and Los Angeles, CAFirm Pedigree

• Rockwood’s real estate professionals havediverse skill sets and experience that spanseveral real estate and capital marketscycles

• Rockwood is led by a senior team with anaverage tenure of 25 years of real estateexperience

Firm AUM Existing GP

• Yes• $20 million to Fund VIII in 2008• $35 million to Fund IX in 2012• $60 million to Fund X in 2015

Ownership

Alignment


Slide 31

TargetSize

FundraisingStatus

Strategy

• Employ active portfolio management with the goals ofenhancing returns while mitigating risk.

• Capitalize on secular changes driven by the widespreadadoption of new technologies and the ongoingevolution of cities- changes that are reshaping propertydemand in the United States, affecting where assets arelocated and how they are designed, fitted-out andoperated.

• U.S. metropolitan areas with highly educated workforces and significant exposure to the “knowledgeindustries” that are prospering from technologicaladvances and globalization. Within these metro areas-which largely are outperforming the rest of the nationin terms of economic, employment and income growth

• Employ active asset management to reposition, re-lease,rehabilitate and/or develop real estate assets but willnot pursue investment opportunities predicated onsignificant land entitlements.

TargetProfile

Team Structure

TrackRecord

NotableLPs

Fund Summary: Rockwood XI


Slide 32

ManagementFee

GPCommitment

CarriedInterest

GovernanceCommittees

PreferredReturn

LP AdvisoryCommittee

InvestmentPeriod

Key Person

TermSuccessionPlanning

Terms and Governance: Rockwood XI


Slide 33


Performance Review: Rockwood VIII - X

Slide 34


Performance Review: Rockwood V – X

Slide 35


Performance Review: Rockwood III – X

Slide 36


Performance Review: Rockwood VIII - X

Slide 37

Date Item

December 2008 – Ongoing• PERA and Rockwood partnership begins with an initial investment in Rockwood Fund

VIII. PERA and consultant conduct ongoing diligence calls, annual meeting attendance,and periodic onsite meetings with Rockwood to monitor current funds

Ongoing • Oversight and monitoring of existing commitment

February 2019 • Launch of diligence on Rockwood XI

April 2019• Due diligence documents - received access to all fund related documents, including legal

agreements and PERA specific due diligence requests

April 2019• PERA on-site with Rockwood - visited the San Francisco office and met with strategy

focused team members to discuss various responsibilities within the fund

Ongoing• Albourne conducts primary diligence on matters relating to the quality and sufficiency of

the Fund’s back office, compliance, and other operational matters

Due Diligence Performed: Rockwood XI

Documents

INVESTMENT COMMITTEE MEETING SENATOR …s3.amazonaws.com/boardaudio/5.30.2019 Investment...Katie Koch, Co-Head of Fundamental Equity Goldman Sachs Asset Management C Information Item: