University of Technology Sydney

20511 Financial Metrics for Decision Making

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Subject handbook information prior to 2025 is available in the Archives.

UTS: Business: Finance
Credit points: 6 cp

Subject level:

Undergraduate

Result type: Grade and marks

There are course requisites for this subject. See access conditions.

Description

This subject serves as an introduction to financial decision-making and the role of (big) data in financial decisions. It enables 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 calculate the metrics used to make financial decisions, they learn how to apply decision-making rules to those metrics, and they discover the systematic pitfalls and biases that plague decision-making, as well as techniques for overcoming them.

Subject learning objectives (SLOs)

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

The subject contributes to the development of graduate attributes involving intellectual rigour, innovative problem-solving, and professional and technical competence by developing practical hands-on skills in data analysis, data interpretation and decision-making. These skills are enhanced through numerous practical in-class data analysis activities. The case study assessment gives students an opportunity to apply their data analysis and decision-making skills to a real-world problem. It also allows them to showcase their written communication skills, which contributes to the graduate attribute related to communication and collaboration.

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 Objective(s):
  • 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 different cultures (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.

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: 20%
Length:

60 minutes per quiz

Criteria:
  • Correctness and accuracy of answers

*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: 30%
Length:

3,000-word report plus documented Excel workbook

Criteria:
  • Quality of explanations in written report
  • Quality quantitative analysis in Excel workbook

Assessment task 3: Final Exam (Individual)

Objective(s):

This addresses subject learning objective(s):

1, 2 and 3

Weight: 50%
Length:

2 hours

Criteria:
  • Correctness and accuracy of answers
  • Interpretation of the results of Excel analysis
  • Application of Excel results to solve business problems

Minimum requirements

Students must achieve at least 50% of the subject’s total marks.