CFA Presentation UVU 2014

Extra Space Storage

Salt Lake City, February 2014

Company Overview

Industry & Competitors

Risk Analysis

Financial Analysis Valuation Conclusion

Main Features• 2nd largest self-storage operator• Largest self-storage management company

Introduction

Wholly-Owned;

51%Joint

Venture; 25%

Managed; 24%

Market Profile52-week Price Range 36.50-49.29

Avg. Daily Volume (3mths)

922,567

Shares Outstanding 111.25M

Market Capitalization 4.85B

% Held by Insiders 5%

% Held by Institutions 95%

FFO Multiple 2013E 23.539

Company Overview


Risk Analysis


4166341639

4161441591

4156941547

4152341500

4147841453

4143141408

4138641361

4133941316

4129130

35

40

45

50

55

60

29.2%upside

Target price: $54.44 Upside: 29.2% BUY

Recommendation

Target PriceCurrent PriceClosing Price

Company Overview


Risk Analysis


Tenant Insurance• 80% profit margin• $10 or $35 for $2,000 or $10,000

coverage, respectively

Management

Lease-up Properties• Avg. sq. ft. occupancy at 82.5% as

of Sept. 2013, up from 73.5%• Redeveloping properties

Big Data

Company Overview


Risk Analysis


• Signs of continual aggressive acquisitions• January 8, 2014 announced acquisition of 17 properties in Virginia for

$200 million

Acquisitions

Company Overview


Risk Analysis


Company Overview


Risk Analysis



Key self storage marketcharacteristics:• High barriers to entry• Low product differentiation• Lack of substitute products• Internet enables both buyer and seller

Company Overview


Risk Analysis



Source: FTSE NAREIT U.S. Real Estate Index Series

Source: Cushman & Wakerfield Storage Business Briefing – August 2013

High returns compared to other REITs

Market resilience & increasing rental rates

Company Overview


Risk Analysis


EXR vs. Competitors

Competitive Advantage:•Management Team •Extensive stats & analytics

Risk Analysis

Company Overview


Risk Analysis


Risk Analysis Market Economic

Operational Political

IMPACT

PRO

BABI

LITY

Company Overview


Risk Analysis


Conditional Upside Drivers

• Constant upward trend of rental prices

• EXR’s occupancy rates for same-store properties were at 88.6 percent compared to the national average of 79.7 percent, according to EXR’s 2012 10k filing

• More acquisitions mean more revenue from tenant insurance

Financial Analysis

• EXR’s stock price follows the SPY with a 67% coefficient of determination.

Company Overview


Risk Analysis


EXR’s Stock Growth Compared to S&P

• Over the last two years, the 100-day stock price moving average is below the 50-day stock price moving average until the effects of the November stock price drop become dominant.

• Long-term the stock has shown strong growth in price.• The stock price is still recovering from the November drop.

Company Overview


Risk Analysis


Technical Analysis

• The six month chart shows the possible rebounding from that November drop.

• The 10-day moving average shows that there may be a possibility of a short-term holding profit.

Company Overview


Risk Analysis


Moving Averages

Year 31-Dec-08 31-Dec-09 31-Dec-10 31-Dec-11 31-Dec-12 31-Dec-13Assets: Real estate assets, net $ 1,938,922 $ 2,015,432 $ 1,935,319 $ 2,263,795 $ 2,991,722 $ 3,265,292 Investments in real estate ventures $ 136,791 $ 130,449 $ 140,560 $ 130,410 $ 106,313 $ 116,035 Cash and Cash equivalents $ 63,972 $ 131,950 $ 46,750 $ 26,484 $ 30,785 $ 33,600 Restricted Cash $ 38,678 $ 39,208 $ 30,498 $ 25,768 $ 16,976 $ 18,528 Receivables from related parties and affiliated real estate joint ventures $ 11,335 $ 5,114 $ 10,061 $ 18,517 $ 11,078 $ 12,091 Other assets, net $ 42,576 $ 50,976 $ 49,549 $ 52,550 $ 66,603 $ 72,693 Total Assets $ 2,291,008 $ 2,407,556 $ 2,249,820 $ 2,517,524 $ 3,223,477 $ 3,518,239 Growth 11.5% 5.1% -6.6% 11.9% 28.0% 9.1%

Historical data was taken from SEC filings and Internet resources, run through statistical software, and used for forecasting.

became

Company Overview


Risk Analysis


Data Conversion

• Total Assets = 20983 + (Years Since IPO x 257534)• Total Revenue = -50060 + (Total Assets x 0.143243)• Net Income = -84716 + (Total Assets x 0.059286)

Asset Regression Coefficients Standard Error t Stat P-value

Intercept 20983.16 243118.3 0.086308 0.933342

Year 257533.7 27096.91 9.504174 1.24E-05

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019$0

$1,000,000

$2,000,000

$3,000,000

$4,000,000

$5,000,000

$6,000,000

Year

Tota

l Ass

ets

(tho

usan

ds)

Company Overview


Risk Analysis


Regression Equations for Forecasting

Valuation

Company Overview


Risk Analysis


Valuation Using FFO

• Constant FFO growth• Market cap projected at 5.619 billion

Years 2013 2014

FFO 199.356 M 239.117 M

FFO Multiple 23.539 23.5

Market Cap 4,687 M 5,619 M

Shares Outstanding 111.250 M 113.750 M

Price Per Share 42.1349.40

Company Overview


Risk Analysis


Valuation Using FFO

• Arbitrage Opportunities• Historically low cap rates• Increasing interest rates

Company Overview


Risk Analysis


NAV Valuation

• Historically low cap rates• Strong rental revenue growth

Year 2013 2014

Rental Revenue 426.841 M 239.117 M

Cap Rates 6.4% 23.5

NAV 5,243 M 6,335 M

Price Per Share 47.1355.70

Company Overview


Risk Analysis


Target Price

Target = 54.44

Holding period return = 29%

NAV Valuation FFO Valuation

$55.70 $49.40

80% 20%

Company Overview


Risk Analysis


4166341639

4161441591

4156941547

4152341500

4147841453

4143141408

4138641361

4133941316

4129130

35

40

45

50

55

60

29.2%upside

Target price: $54.44 Upside: 29.2% BUY

Conclusion

Target PriceCurrent PriceClosing Price

Questions?

Data Source: Cushman & Wakefield Storage Business Briefing – August 2013

Average Demand per Person

Virtually No New Supply

Source: Adelante Capital Management, Wilshire Associates, and FactSet

Annual Returns: Ranked By Property SectorWilshire US REIT Index

Rental Trends

1 2 3 4 5 6 7 8 9 10 $-

$500,000

$1,000,000

$1,500,000

$2,000,000

$2,500,000

$3,000,000

$3,500,000

$4,000,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 $-

$1,000,000

$2,000,000

$3,000,000

$4,000,000

$5,000,000

$6,000,000

Total Assets Forecast

Since EXR’s IPO, there has been a steady increase of total assets. In all the regressions run, time showed the most direct correlation with an R Squared of 0.919, t Statistic of 9.5, and P-value of less than 0.0001.

By using the regression model, we were able to forecast total assets using the following equation:Total Assets = 20983 + (257534 x Years since IPO)

Total Assets Since IPO

The correlation between revenue and assets proved exceptionally high for past periods with an R Squared of 0.99, a t Statistic of 28.34, and a P-Value lower than 0.000000003.

Total

Assets

$748,484

$1,420,192

$1,669,825

$2,054,075

$2,291,008

$2,407,556

$2,249,820

$2,517,524

$3,223,477

$3,518,239 $-

$50,000 $100,000 $150,000 $200,000 $250,000 $300,000 $350,000 $400,000 $450,000 $500,000

Total

Assets

$748,484

$1,420,192

$1,669,825

$2,054,075

$2,291,008

$2,407,556

$2,249,820

$2,517,524

$3,223,477

$3,518,239

$3,626,456

$3,883,989

$4,141,523

$4,399,057

$4,656,591

$4,914,124

$5,171,658 $-

$100,000

$200,000

$300,000

$400,000

$500,000

$600,000

$700,000

$800,000

Revenue Forecast

We were able to forecast Revenue for upcoming years by using the following equation: Total Revenue = -50060 + (Total Assets x 0.143243).

Revenue and Asset Correlation

Net Income’s Correlation Coefficient in regards to Assets for historical data was 0.9226, t Statistic is 9.766, and P-Value is than 0.00001.

$748,484

$1,420,192

$1,669,825

$2,054,075

$2,291,008

$2,407,556

$2,249,820

$2,517,524

$3,223,477

$3,518,239

$3,626,456

$3,883,989

$4,141,523

$4,399,057

$4,656,591

$4,914,124

$5,171,658

$(50,000)

$-

$50,000

$100,000

$150,000

$200,000

$250,000

Net Income Forecasted $748,484

$1,420,192

$1,669,825

$2,054,075

$2,291,008

$2,407,556

$2,249,820

$2,517,524

$3,223,477

$3,518,239 $(40,000) $(20,000)

$- $20,000 $40,000 $60,000 $80,000

$100,000 $120,000 $140,000 $160,000

Net Income = -84716 + (Total Assets x 0.059286)

Net Income and Asset Correlation

• Regression models similar to the one used for assets were used to forecast liabilities and equity.

• Growth rates were calculated each year, including forecasted years, for assets, liabilities and equity.

• Those growth rates were used to forecast individual accounts within each section of the balance sheet.

• Example: Cash and Cash Equivalents historical data was input, the last reported number was then multiplied by 1+calculated growth rate for assets.

Balance Sheet Equations

• The correlation coefficient for historic operational cash flows and net income is 0.923, t Statistic of 6.9, and P-Value of 0.002.

• Thus, forecasted net income was used to forecast operational cash flows.

• Those forecasted values were used to determine the growth rate for operational cash flows.

• Those growth rates were applied to individual accounts within the operational cash flows section of the Summary of Cash Flows Statement.

Operational Cash Flow Calculations

• The regression process used to forecast revenue was also used to expenses and income from operations.

• The calculated growth rates from those forecasted accounts was again used to forecast the relevant subordinate accounts.

• Example: 2015 Acquisition Related Expense = forecasted 2014 Acquisition Related Expense x Calculated growth rate for 2015 Total Expenses.

Statement of Operations Calculations

CFA Presentation UVU 2014

Investor Relations

Transcript of CFA Presentation UVU 2014