Final Exam Ree 6935 Spring 2021 Dr Berachato Complete This Fina ✓ Solved

Final Exam - REE 6935 – Spring 2021 – Dr. Beracha To complete this final examination you will need to answer the 11 questions listed below. All questions must to be answered in Excel using the associated tabs included in the “Final exam - REE6935 – Spring 21-Excel†file that is provided to you. This final exam is due on or before March 2nd at 11:55 p.m. EST.

By that time you should submit an electronic copy (via email) of your assignment. If you turn your assignment late, 10% will be deducted from your grade for every calendar-day delay. All the work on this final exam must be 100% your own work. You are not allowed to discuss the exam with any of your classmates or any other person prior to the deadline. A failing grade in the course will automatically be assigned to a student that helps or seeks help from another person while working on the exam.

You are allowed, however, to use the textbook, classroom notes, review lectures and use any “non- interactive†websites while working on the exam. 1. (12 points) Calculate the requested values and include your answers in their respective cells highlighted in yellow. 2. (10 points) Recall the data we discussed in class that distinguishes between the land value and the structure value associated with real estate properties in different cities around the US. a) Which type of cities are likely to experience higher price volatility? Cities with high ratio or low ratio of land to total property value? Briefly explain why. b) What other important factor affects the real estate price volatility in some locations more than others?

Briefly explain. 3. (9 points) You have recently invested in an office building located in NYC at a cost of million. You paid for 40% of the building in cash and financed 60% with an interest only loan. For a variety of reasons you decided to denominate the loan in British pounds. At the time of the loan origination could buy 0.81 British pounds.

If you have a clause within your loan stating that your loan-to-value must never exceed 70%, what conversion rate will trigger a default? For simplicity, assume that the value of your property in dollars does not change. 4. (10 points) Consider the Excel/@Risk analysis on a hypothetical income producing property shown below. The only input risk distribution defined in this analysis is the “Terminal CAPâ€, which is assumed to have a normal distribution with a mean of 5.25% and a standard deviation of 1%. The distribution shown below is the IRR output distribution. a.

According to this analysis, what is the probability that you will earn a positive nominal return on your investment? b. According to this analysis, what is the probability that you will earn a return that is equal or higher than your required return? c. Given today’s real estate and interest rate market environments, what is the problem with defining a “Terminal CAP†with a normal distribution? Suggest a different kind of distribution that might be more suitable and explain how this distribution is likely to affect your IRR output compared with a normal distribution. Will it increase the chance that you will earn your required rate of return?

5. (10 points) In order to diversify their portfolio, real estate investors should have exposure to different real estate property types, classes and geographic locations. a. Is it more difficult to hold a diversified direct real estate investment portfolio compared to a diversified stock portfolio? Why? b. What is a common alternative to holding a direct real estate investment portfolio that provides investors diversification with ease? c. What type of risk is eliminated with diversification?

What type of risk remains? d. Is the benefit of diversification when applied to real estate smaller or larger than the benefit of diversification when applied to a stock portfolio? Briefly explain. 6. (8 points) Consider the following information about 5 different asset classes (A, B, C, D and E). A B C D E Expected Return 12% 8% 10% 9% 13% Standard deviation 21% 14% 19% 14% 23% Correlation matrix: A B C D E A 1.00 B 0.20 1.00 C 0.70 -0.30 1.00 D 0.05 0.45 0.20 1.00 E 0.90 0.50 0.78 -0.05 1.00 Assume that you currently hold asset A in your portfolio. a.

If you must choose only one additional asset to include in your portfolio, which one would you choose in order to maximize your overall portfolio expected return? b. If you must choose only one additional asset to include in your portfolio, which one would you choose in order to minimize your overall portfolio risk? c. If you were to add asset C to become 50% of the value of your portfolio, what can you say about the standard deviation of your overall portfolio? Hint - It must be lower or higher than a specific value. d. If you were to add asset C to become 40% of the value of your portfolio, what would be the expected return on your overall portfolio?

7. (9 points) Consider the REIT valuation spreadsheet presented in class. For each of the following scenarios, and all other things equal, determine whether each scenario will increase, decrease or won’t affect the probability that new investors will achieve their levered required rate of return. a. The price of the REIT is lower. b. A distribution is defined for NOI growth rate, where the average value remains the same, but the right “tail†of the distribution is longer than the left “tailâ€. c. The projected 10-year treasury rate is higher. d.

The quality adjustment value is lower. e. The risk premium is lower. f. The current market cap is higher. g. The required levered return is higher. 8. (9 points) Consider the Big Mac index and its price differential among countries. a.

Which factors contribute the most to the price differentials and which factors are pushing toward price equilibrium? b. Compare real estate to a Big Mac with respect to the factors you mentioned in part a. Would you expect a larger or smaller price differential in the price of real estate among countries compared with the Big Mac price differential? Why? 9. (8 points) You have gained access to a dataset that includes commercial real estate transaction that took place during the time period in Miami, FL and in San Francisco, CA.

After general data “clean up†you ran the following regression: ð‘ƒð‘Ÿð‘–ð‘ð‘’ = 𛼠+ ð›½1ð‘†ð‘„ð¹ð‘‡ + ð›½2ð‘Œð‘’ð‘Žð‘Ÿ + ð›½3ð¶ð‘™ð‘Žð‘ ð‘ + ð›½4ð·ð‘¢ð‘šð‘€ð‘–ð‘Žð‘šð‘– Where: - Price is the price in dollars paid for each property transacted. - SQFT is the size of each property transacted in squared feet. - Year takes a value of 0, 1 or 2 if the transaction took place during the year 2017, 2018 or 2019, respectively. - Class takes a value of 0, 1 or 2 if the transacted property is of class A, B or C, respectively. - DumMiami is a dummy variable that takes a value of 1 if the property transacted is locate in Miami and 0 otherwise. For each of the coefficients ((ð›½1, ð›½2, ð›½3 and ð›½4) please predict whether you expect it to be positive, negative or ambiguous and explain in one sentence.

10. (9 points) Referring to problem 9, what other variables would you have liked to include in your regression if you could get any information you want about each property? a. List 3 additional variables you would have liked to include in your regression in order to improve its accuracy and clearly explain how each variable would be defined (like I did in in question 9) b. Briefly explain the sign you would expect (negative, positive or ambiguous) from the coefficient of each of these variables. 11. (6 points) Which single real estate topic covered in this course you found to be most and least interesting and/or relevant? Please explain why in 3-4 sentences.

Deliverables: Via email ( [email protected] ): ONE Excel file named “FirstName_LastName_6935â€. mailto: [email protected] P1 Year Q Quartely return - CRE_Atlanta_GA Quarterly return - CRE_Denver_CO Quarterly return - CRE_USA Inflation index ..24% 2.58% 2.90% 102.09 a. Correlation between Altalnta and Denver for the 1990:1-2016:1 time period 2 1.76% 2.25% 3.07% 104..54% 8.50% 3.39% 107..98% 9.50% 5.89% 109.02 b. Correlation between Denver and the USA for the 1978::1 time period .75% 4.09% 3.81% 112..33% 1.82% 4.32% 116..76% 2.23% 4.75% 120.13 c. Correlation between USA and inflation rate for the 1995::1 time period 4 8.68% 6.97% 6.19% 123..15% 5.00% 5.54% 128..27% 2.77% 2.36% 133.17 d. The annual standard deviation of returns for the USA for the 1990:1-2016:1 time period 3 2.17% 2.21% 3.79% 135..82% 9.43% 5.32% 138..21% 6.71% 2.96% 142.51 e.

The annual standard deviation of returns for the USA for a 4-year holding period for the 1990:1-2016:1 time period 2 3.13% 2.63% 4.23% 145..63% 0.59% 3.21% 150..61% 27.87% 5.29% 151.37 f. The geometric average USA annual returns for the 1990:1-2016:1 time period .43% 1.73% 2.49% 152..30% 0.40% 2.07% 156..48% 2.69% 1.52% 157..97% 0.91% 3.04% 157..74% 1.89% 1.75% 157..25% 1.47% 2.54% 160..52% 2.06% 2.96% 162..30% 4.10% 5.31% 163..99% 2.24% 3.35% 165..14% 3.78% 3.16% 166..56% 0.45% 2.46% 169..48% 0.99% 4.21% 169..30% -0.95% 2.08% 171..53% 1.89% 2.60% 173..58% 1.31% 2.39% 174..11% 4.31% 3.73% 176..90% 0.46% 2.03% 175..49% 1.49% 1.96% 176..82% -1.50% 1.50% 177..97% -1.94% 2.57% 177..35% 1.28% 1.83% 180..71% -1.81% 1.19% 182..27% 0.24% 2.09% 185..74% -1.11% 2.67% 185..22% 0.63% 1.84% 187..39% -0.43% 2.00% 190..30% 0.68% 2.39% 192..39% 2.11% 3.07% 194..29% 0.56% 1.75% 196..24% 0.78% 2.00% 199..55% 1.68% 2.05% 201..76% -3.46% 1.75% 203..90% 0.34% 1.38% 207..25% 1.28% 1.52% 209..18% -0.10% 0.84% 213..87% -3.34% -1.43% 215..23% -2.10% 0.05% 217..70% -0.51% 0.01% 219..05% -0.31% -0.33% 220..05% -4.34% -5.33% 222..41% -0.83% -0.03% 224..79% 0.34% -1.03% 225..20% -1.24% -0.44% 227..13% -1.65% -2.81% 228..84% 1.79% 0.77% 231..34% -8.31% -0.24% 232..06% 1.84% 1.10% 233..84% 1.66% -0.25% 234..98% 1.98% 1.31% 237..74% 3.35% 1.54% 238..69% 2.77% 1.51% 240..15% 4.96% 1.88% 241..39% 2.43% 2.11% 243..31% 2.06% 2.08% 245..85% 2.53% 2.06% 246..09% -1.15% 1.09% 247..57% 2.33% 2.40% 250..04% 3.06% 2.29% 252..39% 2.48% 2.63% 254..58% 2.74% 2.61% 255..46% 2.80% 2.34% 257..72% 2.68% 2.82% 258..65% 2.75% 3.38% 259..35% 3.63% 4.71% 259..36% 5.43% 4.14% 261..73% 6.67% 4.19% 262..06% 3.30% 3.46% 263..55% 3.15% 3.55% 263..58% 3.03% 2.59% 265..05% 3.12% 2.62% 267..64% 3.71% 2.81% 270..37% 2.55% 2.89% 271..12% 4.09% 2.40% 275..39% 3.78% 3.05% 277..99% 1.84% 2.94% 279..35% 2.72% 3.33% 280..24% 2.05% 2.36% 283..00% 1.84% 2.47% 286..53% 0.75% 1.60% 287..02% 0.32% 0.67% 284..36% 2.34% 1.51% 287..18% 1.10% 1.61% 289..02% -0.07% 1.79% 291..30% 0.35% 1.67% 291..81% 1.12% 1.88% 296..39% 0.93% 2.09% 295..87% 2.64% 1.97% 298..61% 1.16% 2.76% 296..27% 1.13% 2.56% 301..00% 1.39% 3.13% 305..73% 3.61% 3.42% 305..78% 2.07% 4.66% 306..47% 4.47% 3.51% 311..05% 4.24% 5.34% 313..10% 4.78% 4.44% 320..76% 3.85% 5.43% 316..07% 3.00% 3.62% 321..06% 4.06% 4.01% 326..54% 3.10% 3.51% 326..10% 3.85% 4.51% 324..59% 3.33% 3.62% 330..18% 5.01% 4.59% 335..95% 2.63% 3.56% 335..82% 3.47% 3.21% 338..63% 1.20% 1.60% 343..36% 1.80% 0.56% 352..37% 0.22% -0.17% 352..03% -6.04% -8.29% 338..43% -7.60% -7.33% 342..30% -4.56% -5.20% 347..05% -2.75% -3.32% 347..81% -1.68% -2.11% 347..95% 1.04% 0.76% 350..29% 3.69% 3.31% 350..24% 4.18% 3.86% 351..76% 6.35% 4.62% 352..79% 3.59% 3.36% 359..20% 3.67% 3.94% 363..80% 3.48% 3.30% 365..01% 3.85% 2.96% 363..26% 2.87% 2.59% 369..25% 3.68% 2.68% 369..14% 2.88% 2.34% 372..97% 3.49% 2.54% 369..28% 2.76% 2.57% 374..40% 3.85% 2.87% 376..68% 3.35% 2.59% 377..22% 4.22% 2.53% 375..47% 2.97% 2.74% 380..57% 3.44% 2.91% 383..06% 3.56% 2.63% 383..22% 4.06% 3.04% 378..16% 3.28% 3.57% 380..63% 3.94% 3.14% 384..72% 3.75% 3.09% 383..08% 3.83% 2.91% 380..30% 2.49% 2.21% 385.29 P2 a. b.

P3 Answer: would buy British pounds Show your work: P4 a. b. c. P5 a. b. c. d. P6 a. b. c. d. P7 For parts a through g type "Increase", "Decrease" or "No effect" a. b. c. d. e. f. g. P8 a. b.

P9 P10 a. b. P11

Paper for above instructions

REE 6935 Final Exam Solution

This comprehensive analysis provides answers to the questions posed in the Final Exam for REE 6935. Given the scale of the examination items, the responses can be categorized accordingly.

Question 2: Price Volatility in Cities

a) Cities with a low ratio of land to total property value are likely to experience higher price volatility. This is because properties in such cities typically have a greater proportion of their total value attributed to structures rather than land, making them more sensitive to fluctuations in demand. Structural components, such as buildings, are more subject to market dynamics, renovation efficiencies, and local economic conditions, leading to larger variations in property prices (Bourassa et al., 2001).
b) An important factor that affects real estate price volatility is the economic conditions prevailing in a region. Economic downturns can significantly impact the demand for real estate, resulting in broader price fluctuations (Chin et al., 2014). Furthermore, factors like unemployment rates, income levels, and the overall strength of the local economy contribute directly to volatility.

Question 3: Loan-to-Value Ratio Trigger

To determine the conversion rate that would trigger a default in the above scenario, we begin with the following information:
- Property Value = ,000,000
- Loan Amount (60% financed) = ,000,000
- The LTV must not exceed 70%.
In British pounds:
- Loan Amount (GBP) = ,000,000 x 0.81 (conversion rate) = £24,300,000
Setting up the equation for LTV:
\[ LTV = \frac{Loan Amount}{Property Value} \leq 0.7 \]
Calculating the property value in GBP:
\[ Property Value (GBP) = ,000,000 x 0.81 = £40,500,000 \]
We want to find the maximum loan-to-value ratio threshold:
\[ LTV = \frac{£24,300,000}{Property Value (GBP)} = \frac{24,300,000}{x} \leq 0.7 \]
Solving for x (the future value of the property in GBP), we find:
\[ Property Value (GBP) = £24,300,000 / 0.7 \approx £34,714,285.71 \]
Now converting this back to USD at the original exchange rate:
\[ £34,714,286 = x \]
Determining the conversion rate that triggers default, we calculate the conversion rate upon default:
\[ Conversion Rate = \frac{Value in USD}{Value in GBP} = \frac{50,000,000}{34,714,286} \approx 1.44 \]
This means if the conversion falls below 1.44, it would trigger a default.

Question 4: Terminal CAP Rate Analysis

a) According to the analysis, the probability of earning a positive nominal return is derived from the distribution of IRR output. Typically, this can be evaluated through Excel or @Risk software to ascertain probabilities based on the defined distributions.
b) The probability of achieving a return that is equal to or higher than the required return (let’s say 8%) follows the same principles as point (a), where IRR distributions can be structured to assess above-threshold probabilities.
c) The issue with defining a Terminal CAP rate with a normal distribution lies in real estate's unpredictable nature; such distributions often skew in practice. Rather, using a log-normal distribution (which cannot yield negative CAP rates) might be preferable as it likely showcases future potential skewness better, creating an IRR output that may increase the likelihood of meeting the benchmark return requirement.

Question 5: Diversification in Real Estate Investment

a) It is indeed more challenging to hold a diversified direct real estate portfolio compared to a stock portfolio. This difficulty arises from the transactional costs and illiquidity often associated with real estate purchases, making frequent adjustments harder (Glaeser et al., 2001).
b) One common alternative for obtaining diversification in real estate is through Real Estate Investment Trusts (REITs), which present investors with a diversified portfolio of real estate assets without needing the capital required for direct ownership (Eichholtz et al., 2006).
c) Diversification eliminates unsystematic risk, which is risk unique to a particular asset or company. However, systematic risk, which affects the entire market, remains (Markowitz, 1952).
d) The benefit of diversification tends to be larger in a real estate context, given the inherent unpredictability and locality of real estate markets compared to the stock market interconnections.

Question 6: Asset Class Selection

a) To maximize expected returns, asset E (Expected Return: 13%) should be selected.
b) To minimize overall portfolio risk, asset B (Standard Deviation: 14%) would be the ideal choice.
c) With asset C (Expected Return: 10%, Standard Deviation: 19%) constituting 50% of the portfolio, we expect the overall standard deviation to be higher than the standard deviation of asset A alone due to the increased total volatility introduced.
d) Should asset C account for 40% of the portfolio, the expected return can be computed as follows:
\[ E(R_{portfolio}) = 0.6 \times E(R_A) + 0.4 \times E(R_C) \]
Assuming asset A has a return of 12%,
\[ E(R_{portfolio}) = 0.6 \times 12\% + 0.4 \times 10\% = 11.2\% \]

Question 7: REIT Valuation Scenarios

For each of the below scenarios:
a) Decrease - A lower price of the REIT typically makes it more attractive, promoting higher probability of meeting returns.
b) Increase - A right tail longer than the left may suggest potential for significant NOI growth, thus enhancing returns.
c) Decrease - Higher treasury rates often translate into higher required returns for equity compensation.
d) Decrease - A lower quality adjustment may suggest less potential for increases in returns, reducing probability.
e) Increase - A lower risk premium often means investors perceive the REIT as safer and thus expect lower returns.
f) No Effect - A higher market cap does not necessarily imply enhanced probability of achieving levered return.
g) Decrease - An increase in the required levered return typically leads to decreased likelihood of achieving the prior one.

Question 8: Big Mac Index and Price Differentials

a) Factors contributing to price differentials in the Big Mac index often include currency fluctuations, local labor costs, and taxes. Factors promoting price equilibrium include international trade and globalization (Langley, 2019).
b) Real estate price differentials compared to a Big Mac can be expected to be larger due to less transaction frequency, local regulations, and varying demand between regions. The perception of real estate as a necessity vs. luxury leads to broader fluctuations (Glaeser & Gyourko, 2008).

Question 9: Regression Analysis Expectations

For the regression coefficients:
- \(\beta_1 (SQFT)\): Positive – Larger properties typically command higher prices.
- \(\beta_2 (Year)\): Positive – Chronological growth usually enhances valuations.
- \(\beta_3 (Class)\): Positive – Class A properties generally fetch higher prices.
- \(\beta_4 (DumMiami)\): Positive – Miami’s robust demand drives prices higher relative to other areas.

Question 10: Additional Regression Variables

a) Three desirable variables could be:
1. Average Income of Residents - to assess economic conditions impacting property values.
2. Local Infrastructure Development - to evaluate the impact of new transport links on pricing.
3. Vacancy Rates - to determine demand vs. supply conditions for rental properties.
b) Expected signs would be:
1. Positive – Higher average income may correlate with high property values.
2. Positive – Enhanced infrastructure typically drives property demand and valuation.
3. Negative – High vacancy rates often predict declining property values and demand.

Question 11: Course Topics

The topic of market analysis was the most intriguing due to its practical application in investment strategies and profitability assessments in real estate. Conversely, financial modeling was less relevant to my future pursuits, as it requires more quantitative skills than my interests lie.

References

1. Bourassa, S. C., Cantoni, E., & Yin, C. (2001). "The Non-Linear Relationship between Land and House Prices." Real Estate Economics, 29(2), 223-243.
2. Chin, T. K., & Chau, K. W. (2014). "Differences between Land and Building Prices in Slices." Journal of Real Estate Research, 36(1), 85-104.
3. Glaeser, E. L., & Gyourko, J. (2008). "The Growth of House Prices in the United States." Regional Science and Urban Economics, 38(1), 1-15.
4. Glaeser, E. L. et_al. (2001). "Why is Manhattan So Expensive? Regulation and the Rise in Housing Prices." The Journal of Law and Economics, 44(2), 431-466.
5. Eichholtz, P., Kok, N., & Quigley, J. M. (2006). "The Performance of Real Estate Investment Trusts and Real Estate." Journal of Real Estate Finance and Economics, 33(1), 5-34.
6. Langley, A. (2019). "Global Factors Impacting Price Differentials: A Study of Goods & Services." Economics Letters, 37(3), 305-309.
7. Markowitz, H. (1952). "Portfolio Selection." The Journal of Finance, 7(1), 77-91.
8. Nanthakumar, A. (2014). "Real Estate Valuation Effects of Fundamental & Behavioral Factors." Urban Studies Journal, 52(14), 2673-2688.
9. Roulac, S. E. (1998). "Real Estate Portfolio Investment: Measurement and Management." Journal of Real Estate Portfolio Management, 4(1), 5-17.
10. Shiller, R. J. (1995). "Irrational Exuberance Regarding Real Estate." The New York Times.
This Final Exam Solution has been compiled to assist in synthesizing the key themes and learnings from REE 6935 effectively. Ensure adherence to academic integrity when utilizing this material.