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You are a real estate investor trending the general direction of real estate prices for your client, a real estate developer.You have obtained data on housing prices, inflation, and total historical sales from the Case-Shiller Housing Prices 2000 through 2014, and inflation and related data from the U.S. Department of Labor Statistics, the U.S. Census, and the U.S. Department of Commerce.You have built a subsequent table below:

Year

Sold (Thousands)

Inflation

Nominal Price $USD

Real Price $ USD

Household Income $USD

2000

877

3.4%

138,914

188,925

41,990

2001

908

2.8%

148,197

197,958

42,228

2002

973

1.6%

162,358

212,504

42,409

2003

1,086

2.3%

178,294

228,409

43,318

2004

1,203

2.7%

202,619

251,203

44,344

2005

1,283

3.4%

229,996

275,321

46,326

2006

1,051

3.2%

233,992

274,665

48,201

2007

776

2.9%

221,389

249,636

50,233

2008

485

3.9%

194,855

216,999

50,303

2009

375

-0.3%

187,347

204,846

49,777

2010

323

1.6%

179,956

193,867

49,276

2011

306

3.2%

172,647

180,163

50,054

2012

368

2.1%

183,836

188,325

51,097

2013

429

1.5%

203,615

206,060

51,939

2014

438

0.8%

212,400

212,400

51,850

2015

 

 


 

 

2016

 

 


 

 

2017

 

 


 

 

2018

 

 


 

 

2019

 

 


 

 

Based on the information, you wish to determine the best time for your investor to begin investing again in new housing developments. Use Monte Carlo simulation to generate a series of scenarios for your client including the following:

1. Using a flat inflation of 3%, with the probability of 85% that incomes will not grow more than 3%, find the year that is best for the investor to begin new home construction.

2. If incomes remain flat (within 3% of 2014 figure), and inflation grows at 2.5% annually, what year should the investor be pulling out of the market in the 5 years noted?

3. Based on the data shown, what would be the expected number of housing units sold for the 5-year period with a uniform inflation rate of 3%?You can use either Monte Carlo or Crystal Ball for this portion of the response.

4. Using your simulation, graphically show the answers to the three questions above.Please show scenarios to compare for your investor, and briefly describe why you used the choice of simulation (Monte Carlo or Crystal Ball).

5. For the 5-year period that the simulation is intended to model, is investing in real estate a good idea, or should the investor seek other opportunities?Assume you are seeking a 5% return annually on the investment.Support your answer strictly based on your responses to questions 1-4 above.

6. Name the next likely sensitivity quantity that would provide you with a better result for your client, and explain why.

This examination takes into account all chapters covered in this course.You are free to use any tools necessary to achieve the model simulation to achieve responses to the six questions above.

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