SIT718 Real World Analytics

Learning Outcomes

This assessment assesses the following Unit Learning Outcomes (ULO) and related Graduate Learning Outcomes (GLO):

The aim of this assignment is to analyse the behaviour and performance of financial share prices of one company from the listed five Telecom & Utilities companies below:
• Australia and New Zealand Banking Group (ASX: ANZ)
• Downer EDI Limited (ASX: DOW)
• SEEK Limited (ASX: SEK)
• BHP Billiton Limited (ASX: BHP)
• Rio Tinto Limited (ASX: RIO)

You can use Yahoo Finance to download the historical data of the company you have chosen at

By completing this assignment, you are required to write a case study report of no more than 7 pages, which should include the following information:

1. Your company’s name and the “principal activities” of this company. Choose one company from the list.

2. Collect share price data (daily closing price) for 3 consecutive months from 1 March 2019 to 31 May 2019 inclusive for the company of your choice. Visualise company’s share price data (daily closing price) for this period.

Describe the general trend of the share price for this period. Produce your own graph.

3. Research the information about modelling of share prices, particularly the stochastic modelling (based on Geometric Brownian motion), to describe the behaviour of the company’s share price. A simplified version of the model is given

Assume that drift and volatility in this model are constants.
You are encouraged to research further the literature about and . Find and describe the meaning of the drift and volatility. Find appropriate formulas to compute their values – daily and annualised - from the historic data.

Assessment Task 2: Problem Solving

4. State the condition that share prices have to satisfy in order to be represented by

a Geometric Brownian motion. Do your data satisfy this condition? Produce appropriate evidence to support your

5. Calculate the parameter values and (daily and annualised values) for the selected periods of three months (March-May) and for the last third month (May).

What is the effect of time on and Are the parameters constants (with time)? How this could affect the model performance?

6. Estimate the expected values of the share price on 4 days between 28 May and 31 May 2019 using the formula given above. Use the parameters and values, computed from the three months of historical data. Compare with the published real data. Comment on the results.

7. Find information publicly available for your company, e.g. reports and news releases, and discuss their effect on the values of and , and the values of the share price. Comment on the model’s performance and state the restrictions of the model.