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FINC12-201: Financial Applications and Quantitative Analysis January 2020 [Standard]

General information

An introduction to statistical techniques used in financial analysis and decision-making. Specific applications include capital budgeting, capital asset pricing model, arbitrage-pricing, portfolio modelling and the study of co-movements of different financial assets. The use of spreadsheets and related software tools is central to the learning experience of this subject to provide extensive opportunities to develop practical skills in financial analysis and modelling.


Academic unit:Bond Business School
Subject code:FINC12-201
Subject title:Financial Applications and Quantitative Analysis
Subject level:Undergraduate
Semester/Year:January 2020
Credit points:10

Delivery & attendance

Delivery mode:


Workload items:
  • Computer Lab: x12 (Total hours: 24) - Computer Lab 1
  • Computer Lab: x12 (Total hours: 24) - Computer Lab 2
  • Personal Study Hours: x12 (Total hours: 72) - Recommended study time & reviewing materials
Attendance and learning activities: Attendance at all class sessions is expected. Students are expected to notify the instructor of any absences with as much advance notice as possible.


Prescribed resources:
  • Simon Benninga Principles of Finance with Excel. 2nd, Oxford University Press
  • Moyer, McGuigan, Rao and Kretlow Contemporary Financial Management. The textbook prescribed for FINC12-200: Thomson / South-Western
After enrolment, students can check the Books and Tools area in iLearn for the full Resource List.
[email protected] & Email:[email protected] is the online learning environment at Bond University and is used to provide access to subject materials, lecture recordings and detailed subject information regarding the subject curriculum, assessment and timing. Both iLearn and the Student Email facility are used to provide important subject notifications. Additionally, official correspondence from the University will be forwarded to students’ Bond email account and must be monitored by the student.

To access these services, log on to the Student Portal from the Bond University website as

Enrolment requirements

Requisites: ?


Restrictions: ?


Assurance of learning

Assurance of Learning means that universities take responsibility for creating, monitoring and updating curriculum, teaching and assessment so that students graduate with the knowledge, skills and attributes they need for employability and/or further study.

At Bond University, we carefully develop subject and program outcomes to ensure that student learning in each subject contributes to the whole student experience. Students are encouraged to carefully read and consider subject and program outcomes as combined elements.

Program Learning Outcomes (PLOs)

Program Learning Outcomes provide a broad and measurable set of standards that incorporate a range of knowledge and skills that will be achieved on completion of the program. If you are undertaking this subject as part of a degree program, you should refer to the relevant degree program outcomes and graduate attributes as they relate to this subject.

Find your program

Subject Learning Outcomes (SLOs)

On successful completion of this subject the learner will be able to:
  1. Demonstrate the role and objective of financial management and compute key valuation metrics.
  2. Apply the concept of time value of money to complex problems using advanced techniques.
  3. Apply valuation models for sophisticated financial instruments.
  4. Create advanced models for cash flow analysis, evaluation techniques and capital budgeting.


Assessment details

TypeTask%Timing*Outcomes assessed
Computer-aided Test (Closed) Spreadsheet-based test on spreadsheet basics, TVM, bonds and stocks. 10% Week 4 1, 2, 3, 4.
Project Data analysis and simulation modelling project. 20% Week 12 2, 3, 4.
Computer-Aided Examination (Closed) Comprehensive spreadsheet-based exam on spreadsheet basics, TVM (including bonds, stocks etc.), capital budgeting, simulations and portfolio analysis. 40% Final Examination Period 1, 2, 3, 4.
Computer-Aided Examination (Closed) Spreadsheet-based exam on Excel basics, TVM, bonds, stocks, loans, and capital budgeting. 30% Week 7 (Mid-Semester Examination Period) 1, 2, 3, 4.
  • * Assessment timing is indicative of the week that the assessment is due or begins (where conducted over multiple weeks), and is based on the standard University academic calendar
  • C = Students must reach a level of competency to successfully complete this assessment.

Assessment criteria

High Distinction 85-100 Outstanding or exemplary performance in the following areas: interpretative ability; intellectual initiative in response to questions; mastery of the skills required by the subject, general levels of knowledge and analytic ability or clear thinking.
Distinction 75-84 Usually awarded to students whose performance goes well beyond the minimum requirements set for tasks required in assessment, and who perform well in most of the above areas.
Credit 65-74 Usually awarded to students whose performance is considered to go beyond the minimum requirements for work set for assessment. Assessable work is typically characterised by a strong performance in some of the capacities listed above.
Pass 50-64 Usually awarded to students whose performance meets the requirements set for work provided for assessment.
Fail 0-49 Usually awarded to students whose performance is not considered to meet the minimum requirements set for particular tasks. The fail grade may be a result of insufficient preparation, of inattention to assignment guidelines or lack of academic ability. A frequent cause of failure is lack of attention to subject or assignment guidelines.

Quality assurance

For the purposes of quality assurance, Bond University conducts an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.

Study information

Submission procedures

Students must check the [email protected] subject site for detailed assessment information and submission procedures.

Policy on late submission and extensions

A late penalty will be applied to all overdue assessment tasks unless an extension is granted by the subject coordinator. The standard penalty will be 10% of marks awarded to that assessment per day late with no assessment to be accepted seven days after the due date. Where a student is granted an extension, the penalty of 10% per day late starts from the new due date.

Policy on plagiarism

University’s Academic Integrity Policy defines plagiarism as the act of misrepresenting as one’s own original work: another’s ideas, interpretations, words, or creative works; and/or one’s own previous ideas, interpretations, words, or creative work without acknowledging that it was used previously (i.e., self-plagiarism). The University considers the act of plagiarising to be a breach of the Student Conduct Code and, therefore, subject to the Discipline Regulations which provide for a range of penalties including the reduction of marks or grades, fines and suspension from the University.

Bond University utilises Originality Reporting software to inform academic integrity.

Feedback on assessment

Feedback on assessment will be provided to students within two weeks of the assessment submission due date, as per the Assessment Policy.

Accessibility and Inclusion Support

If you have a disability, illness, injury or health condition that impacts your capacity to complete studies, exams or assessment tasks, it is important you let us know your special requirements, early in the semester. Students will need to make an application for support and submit it with recent, comprehensive documentation at an appointment with a Disability Officer. Students with a disability are encouraged to contact the Disability Office at the earliest possible time, to meet staff and learn about the services available to meet your specific needs. Please note that late notification or failure to disclose your disability can be to your disadvantage as the University cannot guarantee support under such circumstances.

Additional subject information

Key Software/Platforms: Microsoft Excel, Bloomberg. As part of the requirements for Business School quality accreditation, the Bond Business School employs an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.

Subject curriculum

Introduction to basic spreadsheets techniques including, but not limited to, formatting, navigation, absolute and relative referencing, formulas, and functions. Spreadsheet design will focus around the concepts of standardisation, versatility, and reusability in order to familiarise students with common spreadsheet design practices.

Valuation of various cash flows including single payments, annuities, and perpetuities through the use of formulas, functions, and long-form spreadsheets. These techniques are then extended to the valuation of real world assets (e.g. stocks and bonds) with various cash flow patterns and assess overall investment performance.

Conditional statements and more advanced Excel functions (e.g VLOOKUP, Goal Seek) are used to introduce students to the concept of adaptive spreadsheets. Changes in parameters will not only require adjustments to values but techniques as well. With a focus on bonds and loans, students will be taught how to design spreadsheets that can react to the information provided by the user and adjust the process taken to achieve a set goal.

Construction of detailed cash flow series given a project description and its exposure to sunk and opportunity costs, taxes, inflation, growth rates and other factors. Assessment of project performance is extended through break even and sensitivity analyses, which also aids in the identification of key performance parameters.

Introduction to multiple financial performance techniques including, but not limited to, net present value (NPV) and internal rate of return (IRR) used to assess individual project cash flows. Advanced interest rate adjustment concepts are also introduced.

Use of new modelling techniques to identify ideal subsets of projects in order to maximise shareholder wealth. Apply various restrictions to the selection process including capital constraints and project relationships.

Introduction of random variables, both discrete and continuous and their use in simulations. Simulation of simple events such as coin flips and die rolls.

Simulation of more complex financial and portfolio models. Concepts such as capital budgeting and portfolio construction and forecasting are revisited to simulate results given a series of non-constant and unknown parameters (e.g. demand, returns, inflation etc.). Students are presented with various functions in Excel to handle non-uniform distributions.

Calculation and understanding of various statistical metrics with a focus on interpretation and the relationships/patterns found among the results. Multiple return and risk measures are presented allowing us to explore the circumstances under which each measure can be used. These metrics are then considered in the context of modern portfolio theory and the portfolio construction process.

Application of CAPM concepts to the portfolio construction process through the introduction of additional parameters (e.g. borrowing/lending rates). Performance assessment techniques (graphical and statistical) are introduced to allow for the comparison of portfolios/assets and identification of arbitrage opportunities. Diversification is further explored through the concepts of systematic and unsystematic risk.

An introduction to portfolio modelling. This topic will include the use of advanced problem-solving tools (e.g. Solver) applied to publicly available data to construct efficient portfolios given various investor requirements/restrictions.

Approved on: Nov 26, 2019. Edition: 3.6