25624 Financial Metrics for Decision Making
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Credit points: 6 cp
Subject level:
Undergraduate
Result type: Grade and marksRequisite(s): 25300 Fundamentals of Business Finance OR 25400 Financial Literacy
These requisites may not apply to students in certain courses.
There are course requisites for this subject. See access conditions.
Anti-requisite(s): 25622 Quantitative Business Analysis
Description
This subject serves as an introduction to financial decision-making and the role of (big) data in financial decisions. It will enable students to make smart decisions, such as management finance decisions, personal savings decisions and investment decisions. The starting point is the traditional paradigm, which assumes that individuals have rational beliefs (with Bayesian updating when new information arrives) and the objective of maximising their expected utilities. This view is enriched, using models of decision-making based on research in psychology, which allow for beliefs that are not fully rational, as well as for alternative preferences and limits to cognition. Using real data, students will calculate the metrics used to make financial decisions, they will learn how to apply decision-making rules to those metrics, and they will discover the systematic pitfalls and biases that plague decision-making, as well as techniques for overcoming them.
Subject learning objectives (SLOs)
| 1. | describe various decision-making techniques and explain the roles of financial metrics, utility theory, prospect theory and systematic biases in financial decision-making |
|---|---|
| 2. | recommend a financial decision based on data, using appropriate financial and statistical concepts and techniques |
| 3. | identify cognitive biases and analyse their impact on corporate behaviour and asset prices |
Contribution to the development of graduate attributes
This subject contributes to the development of the following graduate attributes:
- Intellectual rigour and innovative problem solving
- Communication and collaboration
- Professional and technical competence
This subject also contributes specifically to develop the following Program Learning Objectives:
- Apply evidence, creativity and critical reasoning to solve business problems (1.1)
- Communicate information clearly in a form appropriate for its audience (2.1)
- Make judgements and business decisions consistent with the principles of social responsibility, inclusion and knowledge of Indigenous peoples (3.1)
Teaching and learning strategies
The following strategies are used to facilitate student learning.
Preparation before class
Students will be required to watch online videos and read prescribed articles before coming to class. This will facilitate in-class interaction and productive discussion of case studies.
In-class activities
The lectures focus on practical examples. Following the discussion of an example, students will be required to answer questions about it, giving them immediate feedback on their understanding.
In-class data analysis
Students will be required to use data and financial metrics to solve decision-making problems in class. Their solutions will then be discussed in-class.
Case studies
Collaborative group case studies will enable students to prepare professional responses to realistic questions and to develop their critical thinking skills in a group context.
Online discussions
Students will be directed to the online discussion board, where they can lodge questions and suggest solutions to other students’ questions. This forum will stimulate debate and provide peer feedback.
Feedback
Feedback will be provided for all in-class presentations. Students will be given recommendations on how to improve their problem-solving techniques and their presentations.
An aim of this subject is to help you develop academic and professional language and communication skills to succeed at university and in the workplace. During the course of this subject, you will complete a milestone assessment task that will, in addition to assessing your subject-specific learning objectives, assess your English language proficiency.
Content (topics)
- Utility theory and prospect theory
- Financial decision-making
- Financial metrics
- Heuristics and systematic biases
- Managerial decision-making
Assessment
Assessment task 1: Quizzes (Individual)*
| Objective(s): | This addresses subject learning objective(s): 1 and 3 |
|---|---|
| Weight: | 30% |
| Criteria: | *Note: Late submission of the assessment task will not be marked and awarded a mark of zero. |
Assessment task 2: Business case (Individual)
| Objective(s): | This addresses subject learning objective(s): 2 |
|---|---|
| Weight: | 40% |
Assessment task 3: Final Exam (Individual)
| Objective(s): | This addresses subject learning objective(s): 1, 2 and 3 |
|---|---|
| Weight: | 30% |
Minimum requirements
Students must achieve at least 50% of the subject’s total marks.
Other resources
- Camm, J. D., Cochran, J. J., Fry, M. J., & Ohlmann, J. W. (2020). Business analytics. Cengage AU
- Guerrero, H. (2019). Excel data analysis. Springer Berlin Heidelberg
- Alexander, M., Kusleika, R., & Walkenbach, J. (2018). Excel 2019 Bible. John Wiley & Sons