Students

AFIN2070 – Stochastic Methods in Applied Finance

2022 – Session 1, In person/Online-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Unit Convenor
Kai Li
kai.li@mq.edu.au
Yin Liao
yin.liao@mq.edu.au
Credit points Credit points
10
Prerequisites Prerequisites
50cp at 1000 level or above including (AFIN100 or AFIN102 or AFIN1002 or ACST152 or ACST1052) and (STAT150 or STAT1250 or STAT170 or STAT1170 or STAT171 or STAT1171)
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

Quantitative modelling and analysis are significant components in the discipline of applied finance. The models employed by practitioners and researchers are based on assumptions about the stochastic properties of financial variables and time series. This unit covers a variety of stochastic models for use in applied finance and includes extensive use of Excel spreadsheets. The topics include discrete and continuous probability distributions, extreme events, joint probability distributions, copulas, bayesian analysis, regression models, time series models, and risk-neutral pricing.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: Use a range of probability distributions to model different financial variables.
  • ULO2: Assess the dependence between financial variables with suitable statistical tools.
  • ULO3: Apply regression models and time series models to various financial time series.
  • ULO4: Examine the concepts of no-arbitrage principle and risk-neutral pricing.
  • ULO5: Perform mathematical computations on Excel spreadsheets for practical problems.

General Assessment Information

Late submissions of assessments

Unless a Special Consideration request has been submitted and approved, no extensions will be granted. There will be a deduction of 10% of the total available assessment-task marks made from the total awarded mark for each 24-hour period or part thereof that the submission is late. Late submissions will only be accepted up to 96 hours after the due date and time.

No late submissions will be accepted for timed assessments – e.g., quizzes, online tests.

Table 1: Penalty calculation based on submission time

Submission time after the due date (including weekends)

Penalty (% of available assessment task mark)

Example: for a non-timed assessment task marked out of 30

<  24 hours

10%

10% x 30 marks = 3-mark deduction

24-48 hours

20%

20% x 30 marks = 6-mark deduction

48-72 hours

30%

30% x 30 marks = 9-mark deduction

72-96 hours

40%

40%  x 30 marks = 12-mark deduction

> 96 hours

100%

Assignment won't be accepted

Other assessment criteria for assessment tasks will be provided on the unit iLearn site.

Assessment Tasks

Name Weighting Hurdle Due
Online Quiz 5% No Week 3
Mid Session Test 20% No Week 8
Assignment 15% No Week 10
Final Examination 60% No Final exam period

Online Quiz

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 1 hours
Due: Week 3
Weighting: 5%

 

The online quiz will be conducted through iLearn and consist of multiple choice questions, and calculation based questions, where a numerical value will need to be entered.

 
On successful completion you will be able to:
  • Use a range of probability distributions to model different financial variables.

Mid Session Test

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 12 hours
Due: Week 8
Weighting: 20%

 

A practical test of 60 minutes will be held to give students practice on a summative task and to provide feedback on their progress midway through the session.

 
On successful completion you will be able to:
  • Use a range of probability distributions to model different financial variables.
  • Assess the dependence between financial variables with suitable statistical tools.
  • Apply regression models and time series models to various financial time series.

Assignment

Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 10 hours
Due: Week 10
Weighting: 15%

 

The assignment will cover quantitative analysis of the materials taught in the class.

 
On successful completion you will be able to:
  • Use a range of probability distributions to model different financial variables.
  • Assess the dependence between financial variables with suitable statistical tools.
  • Apply regression models and time series models to various financial time series.
  • Examine the concepts of no-arbitrage principle and risk-neutral pricing.

Final Examination

Assessment Type 1: Examination
Indicative Time on Task 2: 20 hours
Due: Final exam period
Weighting: 60%

 

A two hour exam will be held during the University Examination Period.

 
On successful completion you will be able to:
  • Use a range of probability distributions to model different financial variables.
  • Assess the dependence between financial variables with suitable statistical tools.
  • Apply regression models and time series models to various financial time series.
  • Examine the concepts of no-arbitrage principle and risk-neutral pricing.
  • Perform mathematical computations on Excel spreadsheets for practical problems.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

Recommended reading materials: Probability and statistics for finance, by ST Rachev, M Hoechstoetter, FJ Fabozzi, SM Focardi, 2010.

Regarding class delivery, please see iLearn for details.

Unit Schedule

Week

Topic

1

Measures of location and spread

2

Discrete probability distributions

3

Basic option pricing techniques

4

Continuous probability distributions

5

Modeling extreme events

6

Joint probability distributions

7

Copulas and dependence measures

8

Mid-term test

9

Regression models

10

Time series models

11

No-arbitrage pricing

12

Business ethics

13

Revision

 

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Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.

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Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

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Unit information based on version 2022.03 of the Handbook