Master of Commerce (Decision, Risk and Financial Sciences) (MC-COMDRFS)

You’re currently viewing the 2024 version of this course

Overview

Award title	Master of Commerce (Decision, Risk and Financial Sciences)
Year & campus	2024 — Parkville
CRICOS code	092761G
Fees information	Subject EFTSL, level, discipline and census date
Study level & type	Graduate Coursework
AQF level	9
Credit points	200 credit points
Duration	24 months full-time

The Master of Commerce (Decision, Risk and Financial Sciences) represents years 1 and 2 of the 5-year doctoral program in Decision, Risk and Financial Sciences and is only available to students pursuing the doctoral program.

The course is a two-year interdisciplinary program in advanced studies in decision, risk and financial sciences. It provides training in the conceptual principles and research techniques in fields across the social, biological and mathematical sciences that analyse human decision-making and problem solving in the context of risk and complexity at the level of individuals and markets.

Entry requirements

1. To be considered for entry, applicants must have completed:

A four-year undergraduate degree in finance, economics, mathematics, psychology, biology, computer science, physics, or engineering, or equivalent, a University of Melbourne equivalent weighted average mark of least 75% (H2A) or equivalent; or
a qualification and/or professional experience considered to be equivalent;

and submit:

a personal statement outlining why they wish to be considered for the course (maximum of 1,000 words); and
a Graduate Management Admission Test (GMAT) or Graduate Record Examination (GRE) test, unless the applicant has met one of the Faculty’s doctoral-level conditions for GMAT/GRE exemption; and
academic referee reports (except for applicants who have graduated from the University of Melbourne within the last 5 years).
Meeting these requirements does not guarantee selection.

2. In ranking applicants, the selection committee will consider:

prior academic performance; and
the results of a Graduate Management Admission Test (GMAT) or Graduate Record Examinations (GRE) test completed within the last 5 years. No minimum GMAT or GRE score is required. The average score of successful applicants is around 680-700 (GMAT) and 324 (GRE).**The following applicants for this course are exempt from submitting a GMAT or GRE test:
◦Those who have completed an undergraduate degree in Australia or New Zealand within the 18 months prior to the date of application; or
◦Those who face significant humanitarian issues;
performance in an interview during which the applicant’s level of understanding, motivation and time commitment will be assessed; and
relevant prior research and/or professional experience; and
referee reports; and
the personal statement.

3. The Selection Committee may seek further information to clarify any aspect of an application in accordance with the Academic Board rules on the use of selection instruments.

4. Applicants are required to satisfy the university’s English language requirements for graduate courses. For those applicants seeking to meet these requirements by one of the standard tests approved by the Academic Board, performance band 7 is required.

Inherent requirements (core participation requirements)

Inherent requirements are the abilities, knowledge and skills needed to complete this course that must be met by all students. For information on the inherent requirements specific to this course contact the course/program coordinator. In some circumstances reasonable adjustments may be available to enable students to meet these requirements while still preserving the academic integrity of the university's learning, assessment and accreditation processes. For more information on how to seek these adjustments refer to the Student Equity and Disability Support website: https://services.unimelb.edu.au/student-equity/home

Intended learning outcomes

Graduates of this degree will undergo rigorous training in and gain a thorough knowledge of human decision-making in the face of uncertainty and complexity, as well as related disciplines, and be able to carry out high quality research in these area.

Demonstrate an advanced understanding of the major current theories and models of decision making under uncertainty at the level of individuals, small groups and markets;
Knowledgably describe and critically evaluate the primary financial theories including foundations of finance, investments, and derivatives;
Knowledgably describe the results of the research devoted to testing the major models and theories of decision-making under uncertainty;
Critically comment on the results of the research in the field; and
Develop cognitive, technical and creative skills to generate and evaluate advanced questions in the area of decision-making under uncertainty.

Graduates of this degree have a solid understanding of methods required to conduct state-of-the-art research on decision-making under uncertainty and in the presence of complexity, at the level of individuals, small groups and markets.

Knowledgably describe research designs and protocols, relevant computational modelling approaches, relevant statistical methods used in this area of research, which includes modelling at the neurobiological, behavioural and market-level;
Determine an appropriate research design and protocol for a research problem on decision- making under uncertainty;
Determine an appropriate statistical method for a research problem on decision-making under uncertainty;
Statistically analyse neurobiological, behavioural and market‐level data to determine the answer to a research problem on decision‐making under uncertainty.

Graduates of this degree will have demonstrable skills sufficient to carry out independent and sustained research on human decision-making under uncertainty and complexity.

Apply the necessary analytical skills and techniques to critically assess a range of issues in decision-making, including: A) Develop the research questions necessary to test a model or theory of decision-making under uncertainty or in the presence of complexity; B) Determine appropriate methods for answering the research questions, including an experimental protocol; C) Determine the data needed to conduct the research and manage this information effectively; and D) Determine the feasibility of a research project;
Manage any research compliance issues arising as part of the research such as human research ethics approval;
Be familiar and able to use the technological infrastructure required for the research, such as brain-imaging systems or systems for markets experiments;
Conduct the research using the methods and data they have assessed as being appropriate, including: A) Managing information effectively; and B) Applying quantitative rigor in the assessment and analysis of research issues; and
Communicate the results of their research in scholarly fashion.

Generic skills

On successful completion of this degree students should have enhanced their skills in:

Applying theory and methods to analyse significant phenomena related to decision‐making in the presence of uncertainty and complexity at the level of individuals, small groups and large groups such as markets, and to discern open research questions addressing key issues arising in relation to those phenomena;
Designing and implementing experiments to address research questions related to decision‐making in the presence of uncertainty and complexity through the application of the necessary analytical skills and techniques;
Assessing the importance and relevance of theoretical or empirical research on decision- making in the presence of uncertainty and complexity; and
Communicating ideas and research in a clear and concise manner.

Graduate attributes

Graduates of this degree will be:

Familiar with state-of-the-art research methods required to conduct research within the scope of current financial knowledge of decision-making in the presence of uncertainty and complexity;
Able to demonstrate research skills sufficient to carry out independent and sustained research in finance;
Able to continue their careers as PhD candidates at research institutes specialising in experimental finance, behavioural economics, decisions sciences and decision neuroscience and will as well be able to use their acquired expertise as consultants and advisors in decision making;
Competent in assessing the importance and relevance of theoretical or empirical research on decision-making in the presence of uncertainty and complexity; and
Proficient at communicating ideas and research in a clear and concise manner.

Course structure

The Master of Commerce (Decision, Risk and Financial Sciences) consists of 16 subjects:

6 core subjects (75 points)
3 additional subjects from a related discipline (37.5 points)
3 elective subjects (37.5 points)
2 lab rotations (25 points)
2-part research report (25 points)

Year 1

During the first year of the course students complete 6 core subjects and 2 additional subjects from a related discipline (one of the disciplines covered by the core subjects or other discipline relevant to decision‐making research). The two additional subjects must be approved by the program director.

Year 2

In the final year of the course students complete 1 additional subject from a related discipline (one of the disciplines covered by the core subjects in Year 1 or other discipline relevant to decision‐making research, 3 electives, 2 lab rotations subjects and the research report, that must be completed over two consecutive semesters of study. The additional subject and electives must be approved by the program director.

Progression from Year 2 of the Master of Commerce (Decision, Risk and Financial Sciences) to the Doctor of Philosophy (Business and Economics) requires:

An average of no less than 75% overall for the course overall; and
an average of no less than 80% in FNCE90071 DRFS Research Report Part 1 and FNCE90072 DRFS Research Report Part 2.

Subject options

Core Subjects

Code	Name	Study period	Credit Points
FNCE90070	Experimental Methods in Decision Studies	Semester 2 (On Campus - Parkville)	12.5
COMP90049	Introduction to Machine Learning	Semester 1 (On Campus - Parkville) Semester 2 (On Campus - Parkville)	12.5
ECON90002	Microeconomics	Semester 1 (On Campus - Parkville)	12.5

Code	Name	Study period	Credit Points
PSYC90097	Mind, Brain & Behaviour 1	Summer Term (On Campus - Parkville)	12.5
COMP90051	Statistical Machine Learning	Semester 1 (On Campus - Parkville) Semester 2 (On Campus - Parkville)	12.5
ECOM90002	Econometrics 2	Semester 1 (On Campus - Parkville) Semester 2 (On Campus - Parkville)	12.5

and
Three additional subjects from a related discipline such as Mathematics, Statistics, Neuroscience, etc. that must be approved by the Program Director.

Elective Subjects
Three elective subjects that must be approved by the Program Director.

Lab Rotation Subjects
Students must complete both subjects:

Code	Name	Study period	Credit Points
FNCE90073	Laboratory Rotation 1	Semester 1 (On Campus - Parkville) Semester 2 (On Campus - Parkville)	12.5
FNCE90074	Laboratory Rotation 2	Semester 1 (On Campus - Parkville) Semester 2 (On Campus - Parkville)	12.5

Research Report
Students must enrol in the Research Report over two consecutive semesters of study.

Code	Name	Study period	Credit Points
FNCE90071	DRFS Research Report Part 1	Semester 1 (Extended) (On Campus - Parkville) Semester 2 (Extended) (On Campus - Parkville)	12.5
FNCE90072	DRFS Research Report Part 2	Semester 1 (Early-Start) (On Campus - Parkville) Semester 2 (Early-Start) (On Campus - Parkville)	12.5