Real Estate Investment Analysis: Focus on Sydney and Surrounding Areas Assignment

Assignment Task

Background

You are working for a financial advisory company that specialises in real estate in Sydney and surrounding areas. A typical client of your company is an everyday person looking for professional investment advice identifying an investment property, and seeks to hold the property for an extended period of time (say at least 5 years).

There is regular debate among senior managers about the best places to recommend to clients. As an analyst for several managers occasionally you are asked to gather evidence to suit different agendas. Note that for simplicity, we will ignore the specific size of a dwelling (including factors such as number of bedrooms and bathrooms), and you are only required to work with the median data (see Resources).

For the purposes of this assignment, we will also ignore data on rent and only look at housing prices (in more technical language, we will only look at "capital gain").

Your Task

You will each be allocated one Local Government Area (LGA).

As mentined above, the data sets will require you to clean them before you begin your analysis.

The dollar amounts in the first 2 data sets are not adjusted for inflation. You will first need to use the CPI values in the third data set to adjust the dollar amounts in the first 2 spreadsheets. If you are unsure about how to adjust for inflation using CPI, there are many resources available online.

Please choose the CPI value of the second quarter (indicated by Jun-12, Jun-13, ...) of each year in the Consumer Price Index table as the CPI of that year. And put them into the formula in the video for calculating price adjustment.

Once you have cleaned the data for your assigned LGA and adjusted for inflation, you will need to run analysis to answer the following questions:

1. Without using the second data set (i.e. using only data from 2017 or earlier), what evidence is there to suggest your LGA a good place to invest?

2. Without using the second data set (i.e. using only data from 2017 or earlier), what evidence is there to suggest your LGA a bad place to invest?

3. Based on your findings using only the data from 2017 or earlier, would you recommend this LGA to a prospective client?

4. Imagine that a client has followed your recommendation from Q3. Using the 2021 data (i.e. the second data set), reflect on your response to Q3. This may include whether the patterns you noticed using the pre-2018 data continued into 2021, comments on whether you believe you made the right decision given the 2021 outcome, and the impact of your recommendation on the client.

As part of your analysis, you may wish to consider strata and non-strata dwellings separately, as well as overall dwellings (i.e. the combined performance of strata and non-strata dwellings).

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