ÐÂÀ˲ÊƱ

Course Outlines

CORPFIN 7023 - Financial Modelling Techniques (M)

North Terrace Campus - Semester 2 - 2025

This course provides an in-depth understanding of financial models used in assessing investment opportunities. Topics covered include corporate valuation, Monte Carlo simulations, option and bond pricing, and value at risk. Through hands-on exercises using Excel and VBA, students will learn to build these models. By the end of the course, students will be able to apply these models to make informed investment decisions. This course is essential for professionals in investment banking, asset management, and financial advisory roles. The course provides students with the skills and knowledge needed to excel in the dynamic world of financial modelling and investment evaluation.

Open All
  • General Course Information
    Course Details
    Course Code CORPFIN 7023
    Course Financial Modelling Techniques (M)
    Coordinating Unit Finance and Banking
    Term Semester 2
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Up to 3 hours per week
    Available for Study Abroad and Exchange Y
    Prerequisites CORPFIN 7005 and (CORPFIN 7033 or CORPFIN 7033MELB) or (CORPFIN 7033AUACM and CORPFIN 7033BUACM)
    Assessment Exam/assignments/tests/tutorial work as prescribed at first lecture
    Course Staff

    Course Coordinator: Yulin Li

    Dr Yulin Li
    Course Timetable

    The full timetable of all activities for this course can be accessed from .

  • Learning Outcomes
    Course Learning Outcomes
    On successful completion of this course students will be able to:
    1. Prepare pro forma financial statements with the estimated cost of capital.
    2. Estimate the value of firm based on financial statement modelling.
    3. Construct binomial tree and Black-Scholes Models to evaluate bonds and options.
    4. Conduct Monte Carlo Simulation analysis for investments.
    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)

    Attribute 1: Deep discipline knowledge and intellectual breadth

    Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.

    		 1,2,3,4

    Attribute 2: Creative and critical thinking, and problem solving

    Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.

    		 1,2,3,4

    Attribute 3: Teamwork and communication skills

    Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.

    		 2,3

    Attribute 4: Professionalism and leadership readiness

    Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.

    		 1,2,3
  • Learning Resources
    Required Resources
    None
    Recommended Resources

    Financial Modeling, The MIT press, Cambridge, Massachusetts, 2021, 5th Ed.

    Online Learning
    This course uses MyUni exclusively for providing electronic resources, such as notes, videos, quizzes, assignments and solutions et cetera.
  • Learning & Teaching Activities
    Learning & Teaching Modes

    Comprehensive course notes are provided. Each week, a two-hour face-to-face lecturer will explain key material and examples from the lecture notes. Weekly tutorials are providing exercises to enhance learning and confirm understanding including interaction with the lecturer and/or tutor. Two online quizzes along with one written assignment provide the assessment opportunities for students to gauge and demonstrate their progress and understanding. Regular consulting sessions can be used to interact with the lecturer and/or tutor.

    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.


    Activity

    		 Quantity

    		 Workload Hours
    Lecture material
    Tutorials
    Online quizzes
    Assignments    		 12 weeks
    12 tutorials
    2 quizzes
    1 assignment (individual)    		 90 hours
    24 hours
    3 hours
    1