Demonstrate knowledge of time value of money (TVM) concepts and techniques
Increasing housing prices has become a serious issue among Australians and this price related to house has remained comparatively high in both Melbourne and Sydney. Hence, it is essential to detect and justify the historical housing prices of any of these two cities with the help of which some assumptions can be made for future prices of houses in Australia. This report has selected the housing price of Melbourne for conducting forecast further. To recognize the entire historical growth of housing price in this city, sufficient calculations have been done. This is because the analysis on housing price growth of this city is required for adequate purposes related to analysis. Based on data, it can be seen that the housing price in this city has grown relatively from 2002 to 2017 and this in turn has helped to understand the future trend of housing prices of Melbourne (Bayer, Ferreira & Ross, 2017). As the housing price is at inflation in Melbourne, the average of Median Price of Established House Transfers (Unstratified) of this city is used. This measurement has helped to identify the relative price change for the next 20 years regarding housing property that is required to evaluate for understanding the implications that it has on the client, who are going to purchase houses. The data is collected from the ABS website for calculation and sufficient dada are given to evaluate and understand the price action regarding housing property (Abs.gov.au., 2018).
Prices in Next 20 Years |
||
Year |
Quarter |
Price |
Year 0 |
$ 713,000.0000 |
|
Year 1 |
Q1 |
$ 726,685.9519 |
Q2 |
$ 740,634.6041 |
|
Q3 |
$ 754,850.9991 |
|
Q4 |
$ 769,340.2760 |
|
Year 2 |
Q1 |
$ 784,107.6730 |
Q2 |
$ 799,158.5284 |
|
Q3 |
$ 814,498.2833 |
|
Q4 |
$ 830,132.4829 |
|
Year 3 |
Q1 |
$ 846,066.7792 |
Q2 |
$ 862,306.9325 |
|
Q3 |
$ 878,858.8136 |
|
Q4 |
$ 895,728.4061 |
|
Year 4 |
Q1 |
$ 912,921.8085 |
Q2 |
$ 930,445.2363 |
|
Q3 |
$ 948,305.0242 |
|
Q4 |
$ 966,507.6286 |
|
Year 5 |
Q1 |
$ 985,059.6300 |
Q2 |
$ 1,003,967.7348 |
|
Q3 |
$ 1,023,238.7785 |
|
Q4 |
$ 1,042,879.7276 |
|
Year 6 |
Q1 |
$ 1,062,897.6825 |
Q2 |
$ 1,083,299.8797 |
|
Q3 |
$ 1,104,093.6947 |
|
Q4 |
$ 1,125,286.6445 |
|
Year 7 |
Q1 |
$ 1,146,886.3905 |
Q2 |
$ 1,168,900.7412 |
|
Q3 |
$ 1,191,337.6547 |
|
Q4 |
$ 1,214,205.2422 |
|
Year 8 |
Q1 |
$ 1,237,511.7704 |
Q2 |
$ 1,261,265.6646 |
|
Q3 |
$ 1,285,475.5121 |
|
Q4 |
$ 1,310,150.0648 |
|
Year 9 |
Q1 |
$ 1,335,298.2427 |
Q2 |
$ 1,360,929.1369 |
|
Q3 |
$ 1,387,052.0131 |
|
Q4 |
$ 1,413,676.3149 |
|
Year 10 |
Q1 |
$ 1,440,811.6670 |
Q2 |
$ 1,468,467.8791 |
|
Q3 |
$ 1,496,654.9490 |
|
Q4 |
$ 1,525,383.0663 |
|
Year 11 |
Q1 |
$ 1,554,662.6166 |
Q2 |
$ 1,584,504.1844 |
|
Q3 |
$ 1,614,918.5576 |
|
Q4 |
$ 1,645,916.7312 |
|
Year 12 |
Q1 |
$ 1,677,509.9111 |
Q2 |
$ 1,709,709.5184 |
|
Q3 |
$ 1,742,527.1934 |
|
Q4 |
$ 1,775,974.7998 |
|
Year 13 |
Q1 |
$ 1,810,064.4292 |
Q2 |
$ 1,844,808.4050 |
|
Q3 |
$ 1,880,219.2874 |
|
Q4 |
$ 1,916,309.8776 |
|
Year 14 |
Q1 |
$ 1,953,093.2225 |
Q2 |
$ 1,990,582.6193 |
|
Q3 |
$ 2,028,791.6208 |
|
Q4 |
$ 2,067,734.0396 |
|
Year 15 |
Q1 |
$ 2,107,423.9536 |
Q2 |
$ 2,147,875.7108 |
|
Q3 |
$ 2,189,103.9348 |
|
Q4 |
$ 2,231,123.5298 |
|
Year 16 |
Q1 |
$ 2,273,949.6860 |
Q2 |
$ 2,317,597.8853 |
|
Q3 |
$ 2,362,083.9067 |
|
Q4 |
$ 2,407,423.8321 |
|
Year 17 |
Q1 |
$ 2,453,634.0521 |
Q2 |
$ 2,500,731.2719 |
|
Q3 |
$ 2,548,732.5173 |
|
Q4 |
$ 2,597,655.1410 |
|
Year 18 |
Q1 |
$ 2,647,516.8288 |
Q2 |
$ 2,698,335.6059 |
|
Q3 |
$ 2,750,129.8435 |
|
Q4 |
$ 2,802,918.2654 |
|
Year 19 |
Q1 |
$ 2,856,719.9549 |
Q2 |
$ 2,911,554.3616 |
|
Q3 |
$ 2,967,441.3084 |
|
Q4 |
$ 3,024,400.9986 |
|
Year 20 |
Q1 |
$ 3,082,454.0234 |
Q2 |
$ 3,141,621.3693 |
|
Q3 |
$ 3,201,924.4254 |
|
Q4 |
$ 3,263,384.9917 |
This part has tried to investigate the historical data related to income of clients of Melbourne for making forecast for the next 10 years. In this context, sine assumptions are formed for forecasting while justification of those assumptions is also made to provide supportive arguments.
The above table has represented a relative historical income growth calculated from 1994 to 2016 of the clients, who are coming from Melbourne. This overall data set has helped to protect the increase in income, which can allow clients to obtain their dream for purchasing a house in Australia. The average growth rate related to income has been measured for the last few years while adequate increment has been used to implement the inflation rate on an average growth rate. This measurement has helped to understand the growth level related to income for the next 10 years of clients in Melbourne. This measurement based on income is relatively a feasible approach that would ultimately support to understand the mortgage level exposure that the client could obtain in future. In addition to this, it can also help to understand the time duration when the client can become able to purchase a Australian Dream house. For this, growth rate of 3.5587% has been used based on yearly income that the client can understand during its growth over the period of 10 years that has been depicted efficiently in the following table.
Capital market theories, and methods of financing businesses
In the context, net income of the client has been calculated considering that the person is single and does not depend on any one. For determining this net income, ATO tax calculator has been used (Genworth.com.au., 2018). Moreover, some realistic calculations are also formed on the monthly expense of the specified client to determine the capacity of monthly repayment of that person.
Two tables are shown above to represent relatively the overall savings and maximum borrowing of money that can applied by the client. The client can in the end save almost $2104 per month that needs to be used for mortgage payments. However, calculation related to loan requirements has been represented where a relative property value of $ 374,857 can be allowed to the client regarding the low initial deposit of the bank (Bhutta, Dokko & Shan, 2017). Therefore, the client can purchase a small property worth $374857 and about this payment of $ 2104.
The two tables represented above have showed overall property value in a relative sense and client can provide this value when mortgage premium is used and also when mortgage premium is not used. Based on valuation, the property value can be obtained worth $370000 by the client while the overall savings has remained at the level of $ 75253. In addition to this, the total LVR can be found at the levels of 80% that has allowed the client to accumulate the property effectively with the value of $ 370000 (Gnanamanickam et al., 2018). Instead of this, the property value along with the mortgage premium has remained at the level of $ 600000 while the client has paid adequate insurance premium for receiving the loan regarding property. The bank has provided total LVR of 92% for the mortgage premium along with the property.
Calculation regarding tables has relatively represented the duration, where the client can measure adequate investments related to property with an upfront payment of 20%. In the fifth year, equation loan can be obtained, as during this year the difference between income and expenses has become positive. On the contrary, the given case with upfront payment with 5% has indicted relatively the use of insurance premium in 3rd year, as that can allow the client to get the property (Bankrate.com., 2018). This phenomenon further can help to improve the income level, which can be obtained through operation.
From the above table has been represented the entire mortgage payments that the client is going to conduct after purchasing of the property. However, the interest rate has changed from 4.50% to 7% during four years and this in turn has slightly influenced the overall mortgage payments of the concerned client (Kareem, 2017). Hence, during the initial investment period, the above-mentioned table has represented the overall income and savings of the client’s mortgage payments. This initial investment related to property can be conducted over 3 years where interest rate increment can be obtained from year 7 (Stampduty.calculatorsaustralia.com.au., 2014). On the other side, changing mortgage payments from $ 43601.80 to $ 57251.28 has remained unable to influence the overall income of the client negatively regarding its continuous savings and increasing income during the year.
Based on the above analysis, a report has been written with financial plan of the client for detaining about the assumptions underlying in the financial plan when the “Australian dream” can be true. Moreover, this section is going to discuss about the potential risks, which are entailed by the assumptions and the way it is managed in the financial plan.
To achieve the Australian dream, assumptions are made for client, as the person’s entire income is sufficient for supporting a mortgage regarding the new home. Hence, the changing income of the client during the period has been represented with the calculations of the financial planner (Clark, Lusardi & Mitchell, 2017). This calculation may support a new mortgage. However, it can be seen from the evaluation that clients may lose their jobs and consequently the entire aim for achieving the Australian dream may remain unfeasible. Hence, the chief focus on the financial plan has remained only on the income that the client can generate over the period. This financial plan can support the mortgage plan.
References:
Abs.gov.au. (2018). Ato.gov.au. Retrieved 24 May 2018, from https://www.ato.gov.au/calculators-and-tools/simple-tax-calculator/
Bankrate.com. (2018). Bankrate. Retrieved 24 May 2018, from https://www.bankrate.com/calculators/mortgages/mortgage-payment-calculator.aspx
Bayer, P., Ferreira, F., & Ross, S. L. (2017). What Drives Racial and Ethnic Differences in High-Cost Mortgages? The Role of High-Risk Lenders. The Review of Financial Studies, 31(1), 175-205.
Bhutta, N., Dokko, J., & Shan, H. (2017). Consumer ruthlessness and mortgage default during the 2007 to 2009 housing bust. The Journal of Finance, 72(6), 2433-2466.
Clark, R., Lusardi, A., & Mitchell, O. S. (2017). Employee financial literacy and retirement plan behavior: a case study. Economic Inquiry, 55(1), 248-259.
Genworth.com.au. (2018). Genworth.com.au. Retrieved 24 May 2018, from https://www.genworth.com.au/lenders/lmi-tools/lmi-premium-estimator/
Gnanamanickam, E. S., Dyer, S. M., Milte, R., Harrison, S. L., Liu, E., Easton, T., … & Whitehead, C. (2018). Direct health and residential care costs of people living with dementia in Australian residential aged care. International journal of geriatric psychiatry.
Kareem, M. K. (2017). On the meaning of Rib? [interest] and its effect on the Nigerian economy. HTS Theological Studies, 73(3), 1-14.
Stampduty.calculatorsaustralia.com.au. (2014). Stamp Duty Calculator. Retrieved 24 May 2018, from https://stampduty.calculatorsaustralia.com.au/