CFA Presentation UVU 2014

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Slides presented by Third Place team in Utah CFA Research Challenge.

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  • Coefficient of Determination (Adjusted R Squared 0.9889)
  • CFA Presentation UVU 2014

    1. 1. Extra Space Storage Salt Lake City, February 2014
    2. 2. 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 Profile 52-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
    3. 3. Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion 30 35 40 45 50 55 60 1/31/13 2/28/13 3/31/13 4/30/13 5/31/13 6/30/13 7/31/13 8/31/13 9/30/13 10/31/13 11/30/13 12/31/13 29.2% upside Target price: $54.44 Upside: 29.2% BUY Recommendation Target Price Current Price Closing Price
    4. 4. Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion 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
    5. 5. Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion • Signs of continual aggressive acquisitions • January 8, 2014 announced acquisition of 17 properties in Virginia for $200 million Acquisitions
    6. 6. Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion
    7. 7. Industry & Competitors
    8. 8. Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion Industry & Competitors Key self storage market characteristics: • High barriers to entry • Low product differentiation • Lack of substitute products • Internet enables both buyer and seller
    9. 9. Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion Industry & Competitors 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
    10. 10. Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion EXR vs. Competitors Competitive Advantage: •Management Team •Extensive stats & analytics
    11. 11. Risk Analysis
    12. 12. Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion Risk Analysis Market Economic Operational Political IMPACT PROBABILITY
    13. 13. Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion 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
    14. 14. Financial Analysis
    15. 15. • EXR’s stock price follows the SPY with a 67% coefficient of determination. Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion EXR’s Stock Growth Compared to S&P
    16. 16. • 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 Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion Technical Analysis
    17. 17. • 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 Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion Moving Averages
    18. 18. Year 31-Dec-08 31-Dec-09 31-Dec-10 31-Dec-11 31-Dec-12 31-Dec-13 Assets: 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 Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion Data Conversion
    19. 19. • 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 $0 $1,000,000 $2,000,000 $3,000,000 $4,000,000 $5,000,000 $6,000,000 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 TotalAssets (thousands) Year Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion Regression Equations for Forecasting
    20. 20. Valuation
    21. 21. Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion 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 42.13 49.40
    22. 22. Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion Valuation Using FFO • Arbitrage Opportunities • Historically low cap rates • Increasing interest rates
    23. 23. Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion 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 47.13 55.70
    24. 24. Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion Target Price Target = 54.44 Holding period return = 29% NAV Valuation FFO Valuation $55.70 $49.40 80% 20%
    25. 25. Company Overview Industry & Competitors Risk Analysis Financial Analysis Valuation Conclusion 30 35 40 45 50 55 60 1/31/13 2/28/13 3/31/13 4/30/13 5/31/13 6/30/13 7/31/13 8/31/13 9/30/13 10/31/13 11/30/13 12/31/13 29.2% upside Target price: $54.44 Upside: 29.2% BUY Conclusion Target Price Current Price Closing Price
    26. 26. Questions?
    27. 27. Data Source: Cushman & Wakefield Storage Business Briefing – August 2013 Average Demand per Person
    28. 28. Virtually No New Supply
    29. 29. Source: Adelante Capital Management, Wilshire Associates, and FactSet Annual Returns: Ranked By Property Sector Wilshire US REIT Index
    30. 30. Rental Trends
    31. 31. $- $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 $- $1,000,000 $2,000,000 $3,000,000 $4,000,000 $5,000,000 $6,000,000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 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
    32. 32. 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. $- $50,000 $100,000 $150,000 $200,000 $250,000 $300,000 $350,000 $400,000 $450,000 $500,000 $- $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
    33. 33. 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. $(50,000) $- $50,000 $100,000 $150,000 $200,000 $250,000 Net Income Forecasted $(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
    34. 34. • 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
    35. 35. • 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
    36. 36. • 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

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