Master of Commerce (Decision, Risk and Financial Sciences) (MC-COMDRFS)
Masters (Coursework)Year: 2018 Delivered: On Campus (Parkville)
About this course
Contact
Melbourne Business School
Level 4, 198 Berkeley Street
Telephone: +61 3 8344 1670
Email: buseco-gradresearch@unimelb.edu.au
Coordinator
Professor Peter Bossaerts and Dr Carsten Murawski
Overview
Award title | Master of Commerce (Decision, Risk and Financial Sciences) |
---|---|
Year & campus | 2018 — 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) 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. Admission to this course is available only to students selected into the doctoral program in Decision, Risk and Financial Sciences.
Entry requirements
1. The Selection Committee will evaluate the applicant's ability to pursue the course successfully using the following criteria:
- A four-year undergraduate degree in finance, economics, mathematics, psychology, biology, computer science, physics, or engineering, or equivalent, with at least H2A (75%) average;
- Successful completion of university level subjects in Calculus and Linear Algebra;
- The applicant’s submitted statement of intent in seeking entry; and
- The Graduate Record Examination (GRE) or GMAT (Graduate Management Admission Test) unless the applicant has completed an undergraduate degree with Honours in Australia or New Zealand or met one of the approved conditions for GRE exemption
2. 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.
3. Applicants are required to satisfy the university’s English language requirements for postgraduate 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)
The Faculty of Business and Economics welcomes applications from students with disabilities. It is University and Faculty 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 Faculty’s programs.
The BCom and Masters degrees of the Faculty of Business and Economics equip graduates with the knowledge and technical skills necessary to understand and participate in the modern business world. The degrees include the following academic requirements for study:
(1) The ability to explain and evaluate concepts, theories, institutional arrangements and operations of modern mixed economies;
(2) The ability to critically evaluate the economy, commerce and business in the broader social and political context;
(3) The ability to explain and apply concepts across a range of commerce and business disciplines in solving business and policy problems; and
(4) The ability to contribute positively to the development of organisations and society in relation to business, government and the commercial professions.
All students of the Faculty’s courses must possess intellectual, ethical, and emotional capabilities required to participate in the full curriculum and to achieve the levels of competence required by the Faculty. Candidates for the BCom degree and for FBE Masters degrees must have abilities and skills in communication; in conceptual, integrative, and quantitative dimensions; and in behavioural and social dimensions.
- Communication: The student must be able to communicate effectively and efficiently in oral and/or written form. A student must have the ability to clearly and independently communicate knowledge and application of a discipline, principles or practices during assessment tasks, and in some discipline streams.
- Intellectual‐Conceptual, Integrative and Quantitative Abilities: The student is expected to have the ability to develop problem‐solving skills and demonstrate the ability to establish study plans and priorities. These abilities include measurement, calculation, reasoning, analysis, and synthesis. Problem solving requires all of these intellectual abilities. Students should also have the ability to comprehend complex disciplinary and cross-disciplinary information related to the BCom and Masters degrees.
- Behavioural and Social Attributes: A student must possess behavioural and social attributes that enable them to participate in a complex learning environment and the emotional health required for full utilisation of his/her intellectual abilities. Students are required to take responsibility for their own participation and learning. They also contribute to the learning of other students in collaborative learning environments, demonstrating interpersonal skills and an understanding of the needs of other students. Assessment may include the outcomes of tasks completed in collaboration with other students. Integrity, concern for others, interpersonal skills, interest, and motivation are all personal qualities that are deemed necessary for students enrolled in FBE cours
Students who feel their disability will prevent them from participating in tasks involving the inherent academic requirements of the BCom and FBE Masters courses are encouraged to contact Student Equity and Disability Support. Adjustments can be provided to minimise the impact of a disability, but students should participate in the course in an independent manner.
Intended learning outcomes
1. Learning Goal
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.
Learning objectives to achieve this goal
On successful completion of this degree students will be able to:
- 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.
2. Learning Goal
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.
Learning objectives to achieve this goal
On successful completion of this degree students will be able to:
- Knowledgably describe research designs and protocols, relevant computational modelling approaches, relevant statistical methods used in this area of research, which includes modelling of behavioural data, neuro-imaging data, and market-level data;
- 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 individual behavioural, neuro-imaging and market-level data to determine the answer to a research problem on decision-making under uncertainty.
3. Learning Goal
Graduates of this degree will have demonstrable skills sufficient to carry out independent and sustained research on human decision-making under uncertainty and complexity.
Learning objectives to achieve this goal
On successful completion of this degree students will be able to:
- 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 knowledgably discuss the importance of a wide range of issues related to decision-making in the presence of uncertainty and complexity at the level of individuals, small groups and large groups such as markets;
- Solving problems 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, comprising 10 core subjects (125 points), 2 elective subjects (25 points) 2 lab rotations (25 points) and a research report (25 points).
Year 1
During the first year of the course students complete 8 core subjects.
Year 2
In the final year of the course students complete 2 core, 2 elective, 2 lab roations subjects and the research report.
Subject options
Core Subjects
Code | Name | Study period | Credit Points |
---|---|---|---|
FNCE90070 | Experimental Methods in Decision Studies | Not available in 2018 | 12.5 |
FNCE90002 | Foundations of Finance | Semester 2 (On Campus - Parkville) |
12.5 |
ELEN90026 | Introduction to Optimisation | Semester 2 (On Campus - Parkville) |
12.5 |
COMP90049 | Knowledge Technologies |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
ECOM90001 | Basic Econometrics | Semester 1 (On Campus - Parkville) |
12.5 |
ECON90002 | Microeconomics | Semester 1 (On Campus - Parkville) |
12.5 |
NEUR90011 | Molecular and Cellular Neuroscience A | April (On Campus - Parkville) |
12.5 |
PSYC90097 | Mind, Brain & Behaviour 1 | Summer Term (On Campus - Parkville) |
12.5 |
COMP90051 | Statistical Machine Learning | Semester 2 (On Campus - Parkville) |
12.5 |
ECOM90002 | Econometrics |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
Elective Subjects
In consultation with a Program Director students choose 2 subjects from the elective list.
Code | Name | Study period | Credit Points |
---|---|---|---|
FNCE90041 | Finance Theory - Investments | Semester 2 (On Campus - Parkville) |
12.5 |
BMEN90002 | Neural Information Processing | Semester 2 (On Campus - Parkville) |
12.5 |
ECON90022 | Game Theory | Semester 2 (On Campus - Parkville) |
12.5 |
NEUR90009 | Brain Imaging and Neural Networks A | March (On Campus - Parkville) |
12.5 |
COMP90038 | Algorithms and Complexity |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
Lab Rotation Subjects
Students must complete both subjects.
Code | Name | Study period | Credit Points |
---|---|---|---|
FNCE90073 | Laboratory Rotation 1 | Semester 2 (On Campus - Parkville) |
12.5 |
FNCE90074 | Laboratory Rotation 2 | Semester 1 (On Campus - Parkville) |
12.5 |
Capstone Subject
Students must complete both subjects.
Code | Name | Study period | Credit Points |
---|---|---|---|
FNCE90071 | DRFS Research Report Part 1 |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
FNCE90072 | DRFS Research Report Part 2 |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
Last updated: 18 December 2020