P6 Econ Pres (Larry Edit)_ARES_Denver 3

101 Montg omery Street, Suite 1350 Sa n Fra nc isc o, CA 94104 P: 877.PILLAR6 F: 415.494.8202
Commercial Real Estate Private Equity:
Capital Flows, Liquidity and Pricing
Presentedby
Dr. LawrenceA. Souza, DBA/CRE/RICS/CCIM
VisitingProfessor–St.Mary’sCollege;SeniorAdvisorandChiefEconomist;Monetarex.com;Senior
–InvestmentEconomist/AdvisorPillar6Advisors,LLC
Olga Koroleva
PresidentandFounder–Monetarex.com
Presentedto
AmericanRealEstateSociety–32nd AnnualMeeting,DenverColorado
Friday April 1st, 2016

Mavericks Surf Contest, Sat February 13th, 2010 (Half Moon Bay California)

Outline
• Hypothesis Research Questions
• Data/Methodology/Literature Review
• Fund Company Evaluation Method
• Real Estate Private Equity (REPE)
• Capital Flows (Offerings)
• Placement Filings by Industry Sector
• Total Offerings by Property Sector – State
• Deals with Commissions and Fees
• Macro Factors Driving Capital Flows
• Return Expectations
• Portfolio Diversification/Concentration
• Fiscal/Monetary Policies
• Business Cycles (Real Estate)
• Employment/Economic Base Concentrations
• Technology/Venture Capital Flows
• International Trade/Infrastructure
• Market Performance/Selection

Hypothesis/Research Questions
• What drives capital to Commercial Real Estate Private Equity
(CREPE)?
• What macro-and-microeconomic factors drive CREPE flows?
• What impact does CREPE flows have on liquidity and pricing?
• What is the level and trend of CREPE capital flows?
• What is the level of CREPE capital flow commitments?
• What property sectors and states receive the most CREPE flows?
• What types of funds are the largest by property sector and state?
• What are the characteristics of the oldest funds?
• What are the characteristics of the funds with the highest
commitment rates?
• What causes these funds to continue to grow?

Data
• Portfolio Level
• Monetarex.com
• Townsend Group
• Institutional Real Estate Inc.
• National Council of Real Estate Investment Fiduciaries
• Microeconomic
• Monetarex.com
• Real Capital Analytics
• CoStar
• REIS Reports, Inc.
• Cushman & Wakefield/CB Richard Ellis/Colliers International/JLL
• Macroeconomic
• Federal Reserve Board of Governors
• US Treasury Department
• Commerce Department
• Bureau of Labor Statistics
• Census Bureau
• Nealson/Claritas/Equifax

Methodology
• Quantitative Analysis
• Principal Components (Factor Analysis)
• Cross-Sectional/Time-Series Regression Analysis (Correlation)
• Chi-Square (Means-Testing)
• Cointegration
• Z-Scores (Weighted)
• Index Development (Performance Scores)
• Qualitative Analysis
• Survey Methods (Experts/Panel)
• Likert Scale
• Weighted Scores
• Interviews
• Hybrid Analysis
• Quantitative Analysis
• Qualitative Analysis
• l Reserve Board of Governors
• Plots

Literature Review – Capital Flows
• Case, B. (2015). WHAT HAVE 25 YEARS OF PERFORMANCE DATA TAUGHT US ABOUT PRIVATE EQUITY REAL ESTATE? Journal of Real Estate Portfolio Management, 21(1), 1-20. Retrieved from
https://stmarys-ca.idm.oclc.org/login?url=http://search.proquest.com.stmarys-ca.idm.oclc.org/docview/1721551204?accountid=25334
• Chervachidze, S., & Wheaton, W. (2013). What determined the great cap rate compression of 2000-2007, and the dramatic reversal during the 2008-2009 financial crisis? Journal of Real Estate
Finance and Economics, 46(2), 208-231. doi:http://dx.doi.org.stmarys-ca.idm.oclc.org/10.1007/s11146-011-9334-z
• Clayton, J., Ling, D. C., & Naranjo, A. (2009). Commercial real estate valuation: Fundamentals versus investor sentiment. Journal of Real Estate Finance and Economics, 38(1), 5-37.
doi:http://dx.doi.org.stmarys-ca.idm.oclc.org/10.1007/s11146-008-9130-6
• Doeswijk, R., Lam, T., C.F.A., & Swinkels, L. (2014). The global multi-asset market portfolio, 1959-2012. Financial Analysts Journal, 70(2), 26-41. Retrieved from https://stmarys-
ca.idm.oclc.org/login?url=http://search.proquest.com.stmarys-ca.idm.oclc.org/docview/1560650489?accountid=25334
• Eichholtz, P. M., A., Gugler, N., & Kok, N. (2011). Transparency, integration, and the cost of international real estate investments. Journal of Real Estate Finance and Economics, 43(1-2), 152-
173. doi:http://dx.doi.org.stmarys-ca.idm.oclc.org/10.1007/s11146-010-9244-5
• Haber, J., Braunstein, A., & Mangiero, G. (2011). The accuracy of the rates of return reported by fund managers: A test in the united states. International Journal of Management, 28(1), 169-
172,199. Retrieved from https://stmarys-ca.idm.oclc.org/login?url=http://search.proquest.com.stmarys-ca.idm.oclc.org/docview/853332556?accountid=25334
• Laposa, S. (2007). Bridging gaps, building portfolios. Journal of Real Estate Portfolio Management, 13(2), 173-178. Retrieved from https://stmarys-
• Lieser, K., & Groh, A. P. (2011). The attractiveness of 66 countries for institutional real estate investments. Journal of Real Estate Portfolio Management, 17(3), 191-211. Retrieved from
• Lieser, K., & Groh, A. P. (2014). The determinants of international commercial real estate investment. Journal of Real Estate Finance and Economics, 48(4), 611-659.
doi:http://dx.doi.org.stmarys-ca.idm.oclc.org/10.1007/s11146-012-9401-0
• Ling, D. C., & Naranjo, A. (2002). Commercial real estate return performance: A cross-country analysis. Journal of Real Estate Finance and Economics, 24(1), 119. Retrieved from
• Malkiel, B. G. (2013). Asset management fees and the growth of finance. The Journal of Economic Perspectives, 27(2), 97-108. doi:http://dx.doi.org.stmarys-
ca.idm.oclc.org/10.1257/jep.27.2.97
• Mueller, G. R. (2002). What will the next real estate cycle look like? Journal of Real Estate Portfolio Management, 8(2), 115-125. Retrieved from https://stmarys-
• Pedersen, N., Page, S., & He, F., C.F.A. (2014). Asset allocation: Risk models for alternative investments. Financial Analysts Journal, 70(3), 34-45. Retrieved from https://stmarys-
• PENNACCHI, G., & RASTAD, M. (2011). Portfolio allocation for public pension funds. Journal of Pension Economics & Finance, 10(2), 221-245. doi:http://dx.doi.org.stmarys-
ca.idm.oclc.org/10.1017/S1474747211000102
• Shilling, J. D., & Wurtzebach, C. H. (2012). Is value-added and opportunistic real estate investing beneficial? if so, why? The Journal of Real Estate Research, 34(4), 429-461. Retrieved from

Introduction
• Commercial Real Estate Private Equity Capital Flows are Driven by
both Micro and Macro Economic Factors:
• Micro: Portfolio, Property, Company and Client Level.
• Macro: Fiscal (Tax) and Monetary Policy, Business Cycle, Trade, and
Performance Level.
• Capital Flows Across Geographies Searching for the Highest Risk-
Adjusted Rates of Return Over the Long Run.
• Real Estate Capital Flows have a Direct and Indirect Impact on
Market Liquidity and Pricing.
• In the Long Run, Real Estate Capital Markets are Efficient, and
Capital Flows to Sectors and Geographies where Public and Private
Human, Physical and Economic Capital Concentrates, Aggregates,
Agglomerates and Clusters.

Firm – Company Level Evaluation

Fund/Company Evaluation
• Property/Portfolio Level
• Average Size/Dollar Value Assets
• Economic Life of Assets (Average Age)
• Total Nominal/Real/Risk-Adjusted Holding Period Returns
• Fee Adjusted (Font Load/Back-End Load)
• Waterfalls/Promotes/Participation
• Portfolio Attribution Analysis (Property Sector/Type/Selection)
• Geographic Concentration/Diversification (Primary/Secondary)
• Supply Constrained vs. Commodity Markets
• Population/Employment Concentrations (Clustering/Economic Base)

Fund/Company Evaluation – Cont.
• Operational/Firm Level
• Headquarters Location (Talent Access/Retention)
• Size of Firm (Number of Employees/Occupied Square Feet)
• Manager Style (Internally/Externally Managed)
• Organizational Structure (Functional/Product/Service Lines)
• Corporate Culture
• Leadership (Senior Level Management/Employees)
• Experience (Years/Other Firm)
• Education/Credentials/Certification/Licenses
• Application/Integration Technological Innovation/Systems
• Customer/Client/Investor Relations (Brand Management)
• Number/Diversification of Investors (Type/Class – Institutional/Accredited)
• Clear Marketing and Communications (Messaging)
• Website/Social Media Presence (Communication Channels)
• Community/Industry Network Relationships

Date Range 1/1/2013 12/31/2015
Company Revenue Range Average of years in business Average of total_offering_amount Average of total_amount_sold % Capital CommitmentChange fromaverage (performance success)
$1 - $1,000,000 9 5,851,660 1,739,854 29.7% Lower Years In Bus/Capital Commitment Rates
$1,000,001 - $5,000,000 16 4,301,390 2,123,080 49.4% Not as Long in Business/But Successful/Middle Market
$25,000,001 - $100,000,000 17 55,639,626 16,185,425 29.1% Larger Funds/Takes Up to 18 Months to Fund
$5,000,001 - $25,000,000 18 10,938,301 7,788,727 71.2% Longest in Business/Not-Institutional/Middle Market
Over $100,000,000 17 75,927,164 17,696,636 23.3% Larger Funds/Takes Up to 18 Months to Fund
Grand Total 15 12,575,729 5,540,274 44.1%
The table above shows the dependency of company revenue range, company years in business, average fund size that these companies are launching and success in raising funds
Average: Years Company In Business = 15 Years
Total Offering Amount = $12.6 million
Total Amount Sold = $5.5 million
Commitment Rate = 44%
Company Revenue $5.0 mil. to $25 mil.
Average: Company In Business = 18 Years
REPE Company Level Economics
Company Revenue $1.0 mil. to $5 mil.
Average: Company In Business = 16 Years

NUMBER OF DEALS PER DEAL SIZE, Q32015
In Q3’15 the average size of the private capital deal was $15 million, an
increase from $12 million in the previous quarter. The change is primarily
due to the fact that the dealflow in the $10 million - $15 million range
almost doubled.
21.3%
37.4%
19.0%
16.5%
5.8%
0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0%
< 1M
1M-5M
10M-50M
5M-10M
> 50M

Commercial Real Estate Private
Equity Capital Flows

TOTAL AMOUNT OF OFFERINGS RISING (Q OVER Q)
7
8
9
7
8
8 8
10642
752
524 572
722
795
611
668
0
100
200
300
400
500
600
700
800
900
-
2
4
6
8
10
12
Q4'13 Q1'14 Q2'14 Q3'14 Q4'14 Q1'15 Q2'15 Q3'15
Billions
Total offering amount Number of deals
Monetarex has aggregated and reviewed the data in 668 Form D filings submitted to the SEC for the real
estate industry group as of September 30, 2015, of which 401 are currently active. Total offering amount
stands at approximately $10.3 billion as of September 30, 2015, with the Total recorded capital
commitments of $3.2 billion (or a 31% capital commitments rate). There is a definite slowdown in the
fundraising activity for the private capital. The average historical capital commitment rate has been
above 50%. In Q3’15 the capital commitments lowered even further (vs. 55% in Q1'15 and vs. 38% in
Q2’15).The total number of active Real Estate Private Placement filings across all sectors increased by
about 10%, from 611 to 668. Average minimum investment for the quarter stands at approximately $136
thousand.

Breakdown by Real Estate
Industry Sector

BREAKDOWN BY REAL ESTATE INDUSTRY SECTOR, Q32015
Almost 40% of Private Placement filings come from the Commercial Sector
representing $3.2 billion across 241 offerings. Construction activity has been
robust in 2015. As a result, private capital activity in the Construction Sector has
increased as well (an increase from 1% to almost 4% of total number of deals).
There were 25 opportunities filed in the Construction Sector during Q3'15
representing $246 million in offerings.
36.1%
3.7%
27.5%
6.4%
26.2%
Commercial Construction Other Real Estate
REITS and Finance Residential

Total Offerings by
Property Sector - State

101 Montg omery Street, Suite 1350 Sa n Fra nc isc o, CA 94104 P: 877.PILLAR6 F: 415.494.8202REPE Sector Level Economics
Sum of total_offering_amount 6 Qtrs
Row Labels Grand Total Rank
Hotels 5,057,854,094
CA 379,940,084 5
DC 310,526,582 6
FL 254,958,000 8
IL 492,373,100 2
MD 143,470,000 10
NY 2,210,821,147 1
OR 151,931,525 9
TX 412,525,901 4
VA 425,807,755 3
WA 275,500,000 7
Industrial 7,726,103,506 Rank
AZ 282,121,325 7
CA 2,228,428,342 1
CO 170,820,000 10
FL 192,953,000 9
IL 505,108,200 5
MA 378,677,346 6
MD 1,108,740,000 3
NY 1,895,161,678 2
TX 715,420,615 4
VA 248,673,000 8
Multifamily 13,680,779,528 Rank
AZ 579,805,000 6
CA 4,193,423,728 1
FL 515,365,000 7
IL 1,109,992,000 5
MA 399,444,343 10
MD 2,177,887,019 3
NY 2,585,646,063 2
TX 1,191,854,276 4
VA 478,315,755 8
WA 449,046,344 9
Office 8,924,459,479 Rank
AZ 272,521,325 9
CA 2,335,086,342 1
CO 219,407,370 10
DC 310,651,582 8
IL 667,366,300 5
MA 336,727,846 7
MD 1,252,750,000 3
NY 2,236,861,160 2
TX 826,765,599 4
VA 466,321,955 6
Retail 8,727,704,590 Rank
AZ 260,496,325 10
CA 1,897,867,101 2
FL 288,187,642 9
IL 618,060,600 5
MA 334,235,198 8
MD 1,383,620,000 3
NY 2,263,063,878 1
TX 818,589,891 4
VA 451,678,955 6
WA 411,905,000 7
Grand Total 44,116,901,197
SUM TOTAL OFFERINGS
Sum Total Offerings (6 Qtrs) = $44.1 billion: Multifamily $13.7 bill (31%), Office $8.9
bill (20%), Retail $8.7 bill (20%), Industrial $7.7 bill (18%), and Hotels $5.1 bill (11%).
Multifamily: CA, NY, MD;
Office: CA, NY, MD; Retail:
NY, CA, MD; Industrial: CA,
NY, MD; Hotels: NY, IL, VA.

DEALS WITH COMMISSIONS AND FEES, Q32015
Despite the rise in popularity of crowdfunding and online investing, the use of
traditional broker-dealers and placement agents still prevails. In Q3’15 17% of
deals were launched through and anticipate to pay commissions on money
raised to broker-dealers. The median commission is 4% assuming the raise is fully
funded. In Q3’15 the commission range was 0.01%-15%.
Deals with
Commissions
Deals with
Commissions to total
Median
Commissions
Maximum
Commissions
Minimum Commissions
114 17.00% $132,900 $6,750,000 $800
Deals with
Finder Fees
Deals with Finder Fees
to total
Median
Fees
Maximum
Fees
Minimum
Fees
18 7.00% $35,000 $5,250,000 $1,000
In Q3’15 7% of deals will have finder fees payouts on the money raised. The
median fee is 2% assuming the raise is fully funded. In Q3’15 the finder fee range
was 0.1%-10%.

Web Portal

Macro Factors
Driving Commercial Real Estate
Private Equity Capital Flows

Commercial Real Estate Valuation –
Income Approach - CAPM
CAPM = E (r) = ie = rf + β (rm – rf)
VRE = NOI
ie
iRE = NOI
Vt
PVRE = NOI (1+g)n + NOI/(i-g)
(1+i)n (1+i)n
Σ
Michael Giliberto, Real Estate in A Capital Markets Context.
i = Discount Rate = Risk Free Rate + Credit RP + illiq RP + σP

i = Discount Rate = Opp Cost of Capital = Exp Rate of Return =
Risk Free Rate (RR + InfExp)
+ Inflation RP
+ Credit RP
+ illiq RP
+ Maturity RP
+ Currency RP
+ Tax RP
+ Political RP
+ Policy RP
+ σRP*
Discount Rate Determination - Volatility

101 Montg omery Street, Suite 1350 Sa n Fra nc isc o, CA 94104 P: 877.PILLAR6 F: 415.494.8202Modern Real Estate Portfolio Theory
- Benefits of Diversification -
N#
SYSTEMATIC RISK
NON-DIVERSIFIABLE
NON-SYSTEMATIC RISK
DIVERSIFIABLE
T
O
T
A
L
R
I
S
K
/

Institutional Real Estate
Capital Allocation Line (CAL)
E (r)
/β
Capital
Allocation/Security
Market Line
(CAL/SML)
LENDING
LEVERAGE
100% High
Risk/Return
Portfolio
100% Low
Return/Risk
Portfolio
Market
Basket
E (r)*
*
Higher Return/Risk
Real Estate
Investments
Lower Risk/Return Real
Estate Investments
Loan Origination
Direct Real Estate
Development
Multi-Asset Portfolio Management/Movements Along the Efficient Frontier
Rf
REAL ESTATE/ENERGY
INSURANCE HEDGE
45% Bonds
25% Stock
10% Insurance
10 % Real Estate
10% Alt. Energy

Applications In Portfolio Theory – Target
Average Standard
Metro Annual Return Deviation
Orange County 13.4% 7.6%
SF Bay Area 15.5% 8.8%
Seattle 14.3% 9.3%
San Diego 13.7% 9.4%
Los Angeles 14.4% 9.9%
Sacramento 13.8% 11.0%
Denver 12.0% 11.2%
Portland 12.5% 10.0%
Salt Lake City 13.0% 11.0%
Phoenix 14.1% 11.4%
Tucson 14.1% 11.4%
Riverside 11.6% 11.9%
Las Vegas 5.1% 6.6%
Albuquerque 2.4% 4.4%
Sources: National Real Estate Index (NREI) and
BRE Properties Research Department
Total Returns are calculated by the year-over-year change in sales price per
square foot on a quarterly basis (Capital Appreciation) plus the annualized cap
rate (Income Return) per quarter.
1.3
0.8
0.5
Risk-Adjusted Rates of Return are calculated by dividing the Total Average
Annual Rate of Return by the Standard Deviation (Risk) for each metro area.
The Risk-Adjusted Rate of Return measures the amount of return for each unit
of risk. For example Orange County provides 1.7 units of return for each unit of
risk.
1.2
1.2
1.2
1.0
1.4
1.4
1.3
1.3
1.7
1.7
1.5
Risk-Adjusted Rate of Return
1986-2000
Risk-Adjusted
Rate of Return
Balanced Conditions for Long
Periods:
• LA/Orange County/Riverside
• San Diego
• Bay Area
• Seattle
Modest Conditions of
Over/Under Supply:
• Sacramento
• Salt Lake City
• Portland
• Denver
• Job Growth
• In-Migration
• Housing Demand
• Positive Net Absorption
• Low Vacancy Rates
• High Effective Rents
• Prices Above
Replacement

Fiscal Policy

• Promote financial stability by improving accountability-transparency in financial system, end to big to fail,
protect taxpayers by ending bailouts, protect consumers from abusive financial services practices.
• Title I: Financial Stability (Oversight Council) by monitoring systematic risk and researching state of
economy.
• Title II: Orderly Liquidation Authority (FDIC/SIPC) banks, broker dealers and insurance companies.
• Title III: Transfer of Powers to Comptroller, FDIC and Fed, elimination of Office of Thrift Supervision
• Title IV: Regulation of Advisors to Hedge Funds and Others, limits exclusion of financial information in
government reporting.
• Title V: Creation of Federal Insurance Office to monitor insurance industry, sales practices.
• Title VI: Bank and Savings Associations Holding Company and Depository Institution Regulation
Improvements, intorducing Volcker Rule to reduce speculative investments, limits on hedge fund and
private equity ownership.
• Title VII: Wall Street Transparency and Accountability in regards to OTC Credit Default
SWAPs/Derivatives.
• Title VIII: Payment, Clearing and Settlement Supervision Act, mitigate systematic risk, promote stability
in payment system.
• Title IX: Investor Protections and Securities Reform Act, Improvements to Regulation of Securities
(SEC), fiduciary duty BDs/RIAs, whistleblower program.
• Title X: U.S. Consumer Financial Protection Bureau (Fed), regulates products and services with federal
law.
• Title XI: Federal Reserve System Provisions.
• Title XII: Improving Access to Mainstream Financial Institutions Act, encourage low income people to
participate in financial system.
• Title XIII: :Pay It Back Act, amends Emergency Economic Stabilization Act and TARP, unused funds can
not be used for new programs, deficit reduction, spending offsets.
• Title XIV: Mortgage Reform and Anti-Predatory Lending Act, organization/servicing mtg standards.
Dodd–Frank Wall Street Reform and Consumer Protection Act
http://en.wikipedia.org/wiki/Dodd%E2%80%93Frank_Wall_Street_Reform_and_Consumer_Protection_Act

$787.0 billion (Spending + Tax Cuts/Credits)
• Tax Credits/Cuts:
• $275B (Co. $51B/Hlth $150B/Ed $91B)
• Infrastructure: $81B (Core $51B/Other $45B)
• Energy: $61 billion
• Housing: $13 billion
• Science: $9 billion
Note: The ability to start and fund projects also comes from
local municipal bond financing and state level block
grants.
American Recovery and Reinvestment Act (2009)
Websites: http://www.recovery.gov/Pages/home.aspx;
http://www.irs.gov/newsroom/article/0,,id=204335,00.html;
http://www.sba.gov/recovery/index.html;
http://www.gsa.gov/Portal/gsa/ep/contentView.do?contentType=GSA_OVERVIEW&contentI
d=25761; http://en.wikipedia.org/wiki/American_Recovery_and_Reinvestment_Act_of_2009

Monetary Policy

101 Montg omery Street, Suite 1350 Sa n Fra nc isc o, CA 94104 P: 877.PILLAR6 F: 415.494.8202Yield Curve Theory and Analysis
-50
bsp
-100
bsp
-75
bsp
-100
bsp
-100
bsp
All debt + equity securities priced off of the yield curve (term structure interest rates)
Although S-T Risk Free Rates near Zero (negative real) debt/equity credit and illiquidity risk premiums still high
+125
bsp+125
bsp+100
bsp+50
bsp
May be the first time in modern monetary history, were the U.S.
economy falls into recession, with out the yield curve inverting first.

101 Montg omery Street, Suite 1350 Sa n Fra nc isc o, CA 94104 P: 877.PILLAR6 F: 415.494.8202Commercial Real Estate Spreads
Spreads Lowest Since 1992
Source: Urban Land Institute Emerging Trends.
Spreads At Cycle High

Business Cycles

Business/Real Estate Cycles
Source: Richard Knutson, Cornish & Carey/Newmark Night Frank, Apartment Advisors.

Real Estate Cycle Theory
E1 E2
Occupancy/ Rent
Growth/Price
Appreciation Line
Rent/Value Spikes
Structural Occupancy Rate/Inflation Rent Growth
Peak Flows/Pricing
Outflows/RedemptionsLow Private Equity Flow
(Contrarian)
Rising Private Equity Flows

Employment

Source: Department of Labor Statistics, Bureau of Labor Statistics.
United States Non-Farm
Employment Growth (YOY)
R
R
R
R
G
G
G
G G
R
G
R
R R
G G
G G G
G
High Probability Recession First 5
Years Every Decade, Growth Last 5
Years Every Decade
R R
G
R

Geographies-Submarkets by Industry Sector:
• High-tech and Bio-tech Manufacturing (SF/Oak/SEA/SD)
• Alternative and Clean Energy Technologies (SF/SJ/PHO)
• Healthcare-Information Systems Services (SF/SJ/SD/SAC/Oak/SEA/PHO)
• Financial Services and Venture Capital (SF/SJ/SM/SEA)
• Telecommunications/Networking (SJ/Marin/Den/Sea)
• Multimedia and Entertainment (SF/Marin/LA)
• Internet and Software Programming (SF/SJ/Oak/Sea)
• International Trade & Tourism (SF/SJ/Sac/SEA/LA/Mon)
• Construction and Engineering Services (SF/SJ/SAC/SEA/LA)
• Education/Government Services (SF/SJ/Oak/SAC/SEA/PHO)
• Defense (SJ/Sac/SEA/LA/PHO/UT/MON)
• Agricultural/Timber Products (Cent Val/SAC/Port/SEA/Mon)
Commercial Demand (Economic Base)

Technology/Venture Capital Flows

Not Important
Average Importance
Highly Important
Note: IT accounts for 10.5% of U.S. Employment
The Importance of IT Industries

Venture Capital Flows
http://www.pwc.com/us/en/technology/moneytree.html
Silicon Valley -46.0% 3Q15 - 4Q15 -39.0% 4Q15 YOY
Silicon Valley $4.3 bil. / 38% of $11.4 bil U.S.
California $5.7 bil/ 50% of U.S. Total VC Funding
U.S. VC Funding Peaked at $17.3 bill. 2Q/2015
Down 34% to $11.4 bill in 4Q/2015

101 Montg omery Street, Suite 1350 Sa n Fra nc isc o, CA 94104 P: 877.PILLAR6 F: 415.494.8202Venture Capital Flows
https://www.pwcmoneytree.com/MTPublic/ns/index.jsp

International Trade/Infrastructure

Global Geography – Export Market Growth
ForeignersBoughta Net $57 billionof U.S. Real Estate LastYear
64% ForeignInvestors to IncreaseAllocation to CRE
60% Believe U.S. Most Stable/Secure Country
Exposure to
Faster
Growing
Southeast
Asian
Economies
Goods/Services
Volume Trade Flows
7.7%
http://www.oecd.org
7.2%
8.2%
6.4%
7.2%
6.5%
6.4%
8.3%
7.1%
8.4%
8.7%
7.9%
7.9%
6.7%
5.2% UK
6.6%
Germ
6.1%
Fran
6.0%
Italy
6.4%
Spain
5.4%
100 –to – 200
bsp Downward
Revisions
OECD Economic Outlook, Volume 2012 Issue 1 - No. 91 - © OECD 2012
Grec
6.3%

Transportation Flows
http://www.dot.gov/ http://www.fhwa.dot.gov/environment/freightaq/appendixc.htm
Trucking carriers 64% of interregional freight tonnage, marine vessels
21%, railroads 14%. Ranked second in total intercity freight tonnage
and tied for first for greatest volume of intercity truck freight.
One of Most Extensive
Networks of Highways
and Arterial Streets in
U.S. (I-5/I-15/I-40/I-10)

Commercial Real Estate Market
Performance and Selection

101 Montg omery Street, Suite 1350 Sa n Fra nc isc o, CA 94104 P: 877.PILLAR6 F: 415.494.8202Oakland CBD

Source: DTZ Research
Core office markets are more expensive globally as yields tighten, but
there remain several attractive markets
Ranking of prominent global office markets
Ranking Market Attractiveness
1
San Francisco HOT
2 Beijing HOT
3
Los Angeles HOT
4 Singapore HOT
5 Shanghai HOT
6 New York WARM
7 Tokyo WARM
8 London WE WARM
9 Sydney WARM
10 London City WARM
Ranking Market Attractiveness
11 Berlin WARM
12 Chicago WARM
13 Brussels WARM
14 Frankfurt WARM
15 Munich WARM
16 Madrid WARM
17 Barcelona COLD
18 Paris CBD COLD
19 Milan COLD
20 Hong Kong COLD
Robert Peto, RICS Global President, Global
Property Outlook.

Top Markets Based on Total Return Forecast
ING/Clarion Partners Research & Investment Strategy.

S.F. Bay Area Submarket Rankings
Existing BRE Communites
A - Deer Valley (171)
B - Blue Rock Village (560)
C - Promontory Point (400)
D - Pinnacle City Centre (192)
E - Verandas (282)
F - Red Hawk Ranch/Sun
Pointe Village (789)
G - Sharon Green (296)
H - Foster’s Landing /Lakeshore
Landing (798)
A
H
G
F
E
D
C
B
1
2
3
4,5,6,7
8
9
10
11
17
19
18
16
15
14
13
12
26
25
24
23
22
21
20
28
27
Submarket Rankings
Mountain View (12)
Central San Mateo (10) (H)
Marina (4)
Cupertino (14)
Sunnyvale (13)
South San Mateo (11) (G)
Russian Hill (5)
San Ramon (25) (C)
Campbell (17)
Fremont (21) (E,F)
South Marin (2)
Santa Clara (15)
South of Market (8)
North San Mateo (9)
West San Francisco (3)
Northeast San Jose (20)
South San Jose (18)
Central San Jose (16)
Haight Ashbury (7)
North Marin (1) (A)
East Contra Costa (26)
Civic Center (6)
East Alameda (22)
Hayward (23) (D)
West Contra Costa (28)
North Alameda (24)
Concord (27)
East San Jose (19)
Home Values
Population/Houeholds
Supply Constraints
Household Income
Executive Occupations
Rent Growth
Occupancy Rates
Zoning
Public Private Goods
Amenities

Conclusion
• Commercial Real Estate Private Equity Capital Flows are Driven by
both Micro and Macro Economic Factors:
• Micro: Portfolio, Property, Company and Client Level.
• Macro: Fiscal (Tax) and Monetary Policy, Business Cycle, Trade, and
Performance Level.
• Capital Flows Across Geographies Searching for the Highest Risk-
Adjusted Rates of Return Over the Long Run.
• Real Estate Capital Flows have a Direct and Indirect Impact on
Market Liquidity and Pricing.
• In the Long Run, Real Estate Capital Markets are Efficient, and
Capital Flows to Sectors and Geographies where Public and Private
Human, Physical and Economic Capital Concentrates, Aggregates,
Agglomerates and Clusters.

Thank You

Questions/Answers

Dr. Lawrence A. Souza
Contact Information:
www.Monetarex.com and www.Pillar6.com
www.the-commercial-group.com
Lsouza@JohnsonSouzaGroup.com
Cell Direct: (415) 713-0213

Dr. Lawrence Souza brings to his clients over 25 years of experience in real
estate economic and financial research experience. Mr. Souza has held senior
positions as Managing Director-Index Services, Charles Schwab Investment
Management (CSIM); Chief Real Estate Economist and Director of Index
Services, Global Real Analytics (GRA); Director of Research for BRE
Properties, Inc. (REIT) in San Francisco and holding Senior Market/Research
Analyst positions at Metric Institutional Realty Advisors and Mellon-
McMahan/MacFarlane Realty Advisors, and market research positions at Norris,
Beggs and Simpson and Grubb & Ellis commercial brokerage. Dr. Souza at
Monetarex and Pillar6, combines traditional fundamental real estate economic
and market research with fundamental and technical financial and capital
market research and investment strategy. This combined approach allows for
the tracking and forecasting of economic, real estate and financial cycles and
efficient portfolio construction, optimization and risk management.
Dr. Souza has degrees in Economics (BA) and Business Administration
(BS/DBA) with concentrations in Accounting, Finance, Banking and Real Estate;
and holds master’s degrees in Applied Economics (MA), Finance/Investments
(MS), Public Administration (MPA), Information Systems (MSIS), and Political
Science (MA). Mr. Souza has been teaching Modern Real Estate Principles and
Finance since 1996 with an emphasis on real estate in a modern and post-
modern portfolio and capital markets context; and the institutionalization,
securitization, internationalization and technologization of real estate markets
and products.

P6 Econ Pres (Larry Edit)_ARES_Denver 3

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