Advanced Investments

This subject has the following teaching availabilities in 2016:

Admission into BH-COM and

Please refer to Prerequisites and Corequisites.

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability

At a theoretical level, the subject teaches principles of strategic and tactical asset allocation, and their potential impact on market-wide phenomena such as asset prices and trading volume (“asset pricing theory”). At the practical level, the subject provides students with opportunities to attempt implementing investment choices in purposely controlled online markets. Students will experience the effect of their actions on commonly used performance evaluation statistics. Mistakes will be put into perspective against recent advances in behavioural finance. Special attention will be paid to market-wide effects of such mistakes, if they exist, and whether these are easily recognisable in real-world financial markets. Lastly, students will investigate to what extent and how trading can be automated (algorithmic trading). Students with programming background (Python) have the option to test their algorithms live in controlled online markets.

On successful completion of this subject students should be able to:

• Put into practice commonly used techniques in tactical and strategic asset allocation;
• Understand to what extent common actions and mistakes impact market-wide phenomena such as prices and volume;
• Recognise and avoid (for oneself and others) common behavioural biases in the context of investments;
• Learn what forces behind prices and volume that one cannot see in historical data, by confronting theory with data from controlled experiments;
• Evaluate to what extent (and for those with programming skills, how) investment can be automated;
• Form an informed opinion about major issues in investments, such as portfolio performance evaluation, the efficient markets hypothesis, dark markets, and algorithmic trading.

• Two assignments not more than 500 words each, first due by end of week 6 and second due end of week 12, (15% each for total of 30%)
• Three on-line trading laboratory tasks, with reports of no more than 500 words each, during 3rd, 5th and 7th week (10% each for total of 30%)
• Three self-paced online decision tasks, with reports of no more than 250 words each, during 2nd (2 tasks) and 9th (1 task) week (5% each for total of 15%)
• 90 minute end-of-semester exam of no more than 750 words, end of semester (25%)

You will be advised of prescribed texts by your lecturer.

This subject is not available as a breadth subject.

• High level of development: written communication; interpretation and analysis; critical thinking.

• Moderate level of development: collaborative learning; problem solving; team work; application of theory to practice; accessing data and other information from a range of sources.

• Some level of development: oral communication; statistical reasoning; synthesis of data and other information; evaluation of data and other information; use of computer software.