成人大片

CORPFIN 7023 - Financial Modelling Techniques (M)

North Terrace Campus - Semester 2 - 2024

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.

  • 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
    15 hours
    Learning Activities Summary

    Week

    Content

    1

    Basic tools and functions for Excel

    2

    Financial statement modelling 1, Pro Forma

    3

    Financial statement modelling 2, Cost of Capital

    4

    Corporate valuation, using financial statement models

    5

    Bond valuation models 1, Duration

    6

    Bond valuation models 2, Term Structure

    7

    Option valuation models 1, Binomial Model

    8

    Option valuation models 2, Black-Scholes Model

    9

    Monte Carlo Methods 1, Introduction

    10

    Monte Carlo Methods 2, Simulations for investments

    11

    Monte Carlo Methods 3, Value at risk

    12

    Revision

  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task

    Weighting

    Learning Outcome

    Assignment (individual) 20% all
    Online quiz 1 10% all
    Online quiz 2 15% all
    Exam 55% all
    Assessment Related Requirements
    An aggregate score of at least 50% is required to pass the course.
    Assessment Detail
    Assessment Task

    Distributed

    Due Date

    Weighting

    Assignment 1
    Online quiz 1
    Online quiz 2
    Exam
    Week 6
    Week 4
    Week 6
    Exam period

    Week 10
    Week 4
    Week 6


    20%
    10%
    15%
    55%
    Submission
    Assignments are to be submitted online via MyUni. Late assignments will not be accepted.
    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through .

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student鈥檚 disciplinary procedures.

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