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:

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.