MATHS 3012 - Financial Modelling: Tools & Techniques III

North Terrace Campus - Semester 2 - 2022

The growth of the range of financial products that are traded on financial markets or are available at other financial institutions, is a notable feature of the finance industry. A major factor contributing to this growth has been the development of sophisticated methods to price these products. The significance to the finance industry of developing a method for pricing options (financial derivatives) was recognized by the awarding of the Nobel Prize in Economics to Myron Scholes and Robert Merton in 1997. The mathematics upon which their method is built is stochastic calculus in continuous time. Binomial lattice type models provide another approach for pricing options. These models are formulated in discrete time and the examination of their structure and application in various financial settings takes place in a mathematical context that is less technically demanding than when time is continuous. This course discusses the binomial framework, shows how discrete-time models currently used in the financial industry are formulated within this framework and uses the models to compute prices and construct hedges to manage financial risk. Spreadsheets are used to facilitate computations where appropriate. Topics covered are: The no-arbitrage assumption for financial markets; no-arbitrage inequalities; formulation of the one-step binomial model; basic pricing formula; the Cox-Ross-Rubinstein (CRR) model; application to European style options, exchange rates and interest rates; formulation of the n-step binomial model; backward induction formula; forward induction formula; n-step CRR model; relationship to Black-Scholes; forward and future contracts; exotic options; path dependent options; implied volatility trees; implied binomial trees; interest rate models; hedging; real options; implementing the models using EXCEL spreadsheets.

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Course Details

Course Code	MATHS 3012
Course	Financial Modelling: Tools & Techniques III
Coordinating Unit	Mathematical Sciences
Term	Semester 2
Level	Undergraduate
Location/s	North Terrace Campus
Units	3
Contact	Up to 3 hours per week
Available for Study Abroad and Exchange	Y
Prerequisites	MATHS 1010 or MATHS 1011 or ECON 1010
Assumed Knowledge	Familiarity with Excel spreadsheets
Assessment	Ongoing Assessment, Exam

Course Staff

Course Coordinator: Dr Judith Bunder

Course Timetable

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

Course Learning Outcomes

On successful completion of this course students will be able to:
1. demonstrate an understanding of basic financial market concepts
2. construct binomial tree models
3. price a wide variety of contingent claims using principles of non-arbitrage

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
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
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

1. Binomial Models in Finance by J Van Der Hoek and R Elliot, Cambridge
2. Elementary Calculus of Financial Mathematics by Roberts, Cambridge
3. Options, Futures, and Other Derivatives 7th ed. by Hull, Pearson

Online Learning

This course uses MyUni exclusively for providing electronic resources, such as notes, videos, quizzes, assignments and solutions et cetera.

Learning & Teaching Modes

Comprehensive course notes are provided. Each week, videos will be made available. Videos will consist of the lecturer explaining key material and examples from the lecture notes. Weekly face-to-face lectures and tutorials supplement this, providing exercises to enhance learning and confirm understanding including interaction with the lecturer and/or tutor. Three written assignments, three online tests and weekly quizzes 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 tests Online quizzes Assignments	12 weeks 12 tutorials 3 tests 12 quizzes 3 assignments	90 hours 24 hours 3 hours 3 hours 30 hours
Total		150 hours

Learning Activities Summary

Topics

1. Call options - European and American
2. Trading options
3. Put options
4. Arbitrage
5. Binomial assett pricing model
6. Price derivatives using risk neutral probabilities
7. Cox-Ross-Rubinstein (CRR) model
8 Arrow-Debreu securities and state prices
9. Black Scholes model
10. Volatility
11. Variable interest rates
12. Valuing American options
13. Barrier options
14. Forward contracts
15. Interest rate derivatives
16. Bonds
17. Ho-Lee model
18. Futures markets
19. Managing risk
20. Hedging
21. Sensitivity of options

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

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

Assessment Summary

Component	Weighting	Objective Assessed
Assignments	15%	all
Online quizzes	10%	all
Online tests	15%	all
Examination	60%	all

Assessment Related Requirements

An aggregate score of at least 50% is required to pass the course.

Assessment Detail

Assessment Item	Distributed	Due Date	Weighting
Assignment 1 Assignment 2 Assignment 3 Online test 1 Online test 2 Online test 3 Quizzes Exam	Week 4 Week 6 Week 8 Week 4 Week 6 Week 8 Weekly exam period	Week 6 Week 8 Week 10 Week 4 Week 6 Week 8 Weekly	5% 5% 5% 5% 5% 5% 10% in total 60%

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
This section contains links to relevant assessment-related policies and guidelines - all university policies.
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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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Authorised by:	Deputy Vice-Chancellor and Vice-President (Academic)
Maintained by:	Course Outlines Administrator

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