Financial Forecasting Report: BHP Billiton Company Performance

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Running Head: FINANCIAL FORECASTING REPORT 1
BHP Billiton Company Forecasting Report
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Financial Forecasting Report 2
Balance sheet ratio
The balance sheet presented in the excel files exhibits the financial progress of the BHP
company. It includes various ratios for example the current ratio, total asset ratios that utilizes
cash at hand in evaluating the performance of the BHP Billiton Company. BHP assets have
shown significant reduction in value from the year 2016 to 2018 with a margin of about $6
billion. On the other hand the overall liability of the company in the 2018 has totaled to about
$51.32 billion. Therefore it’s upon the firm to improve its business thus gaining future benefits
for the firm (Rey, T., Kordon, A., & Wells, C., 2012). .
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Financial Forecasting Report 3
Total income statement ratio
While analysis BHP Billiton Company forecast it is important in viewing the income
statements. The income statement comprises of the revenue. The chart shown above implies that
there is an increase in the firm’s sales values. Therefore, investors should diagnose a company’s
stocks in order to know if it’s declining. At the bottom section contains te profit and loss
statements which explain the level of profit or loss of a certain period. As exhibited in the chart
above the current profit or loss of the BHP Company is $3.7 billion.
Return of Equity Ratios
Therefore the overall figure in the upcoming 5 years cash flows and terminal value that
has been discounted today is called the equity value. Always the value of equity is always
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Financial Forecasting Report 4
achieved through the division of the net income together with the overall capital of the firm. A
high increase in the equity value results to a higher chance for more investor increasing the
investment processes. The BHP’s return on equity was 9% in 2016, 7% in 2017, and 8% in 2018.
This should be considered since there is a declining state of the company’s return of equity.
Therefore, it is projected that the return on equity of the company in the next three years will
increase by 2%. Thus the return of equity is thus seen to increase in the years to come according
to prior research acquired (Pivnyak, G., Bondarenko, V., Kovalevs'ka, I., & Illiashov, M., 2013).
Mean reversion and choice of reliance of BHP Company
For the BHP Billiton Company mean reversion value is estimated to $120 which shows a
considerate margin. Additionally its manufacturing levels of the company are within $40-$50
tones in total. Although, based on prior results of 2014 to 2018 the company’s mean reversion is
projected to increase from $120 to $190 in the upcoming years. Therefore the company’s
reliance will be on the regional aquifers which will help them meet the company’s environmental
commitments.
Terminal value
The essential components which should be aligned within the cash flow rate include the
actual cash flows and the discounted rates. It is not compulsory in abiding by my values,
although I suggest that verifying my computation will be important. Since BHP Billiton
Company is viewed as a potential investor always the discounted rate is used for the cost of
equity but not the cost of capital which in turn is takes into considerations the debts (Donnelly,
2011). In this computational analysis 10.7% is used based on a 1.084 bottom up beta value and
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Financial Forecasting Report 5
also had restrictions which lied between 0.8 and 2 which provides clear rationale for a steady
business. The performance outcome of the BHP Company is evaluated exactly through analyzing
at the approximate growth of the company and the extent of profit value it is supposed to
produce (Woodward, Wesseloo & Potvin, 2018). In one to three years BHP company’s revenues
is expected to decline which is lower than the UK and market levels of Northern Ireland. In
respect to shareholder’s funds, BHP Company is not expected to use the funds in future.
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Financial Forecasting Report 6
Reference
Donnelly, J. (2011). BHP Billiton Forges Ahead With Large, Complex Projects. Journal Of
Petroleum Technology, 63(03), 38-45. doi: 10.2118/0311-0038-jpt
Pivnyak, G., Bondarenko, V., Kovalevs'ka, I., & Illiashov, M. (2013). Mining of mineral
deposits, (5th ed.), pp 455-633, venezuela.
Rey, T., Kordon, A., & Wells, C. (2012). Applied data mining for forecasting using SAS®. Cary,
N.C.: SAS Institute.
Woodward, K., Wesseloo, J., & Potvin, Y. (2018). A spatially focused clustering methodology
for mining seismicity. Engineering Geology, 232(4), 104-113. doi:
10.1016/j.enggeo.2017.11.015
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