FIT3051 Decision support systems for finance - Semester 1, 2013

This unit is designed to introduce students to the practical application of decision support systems for finance using modern computer tools. It covers issues associated with the implementation, theory and risk of decision support systems for finance. The aims of this course are to provide a study of the concepts behind decision making; the tools and techniques to support various stages of the decision making process and to explore key factors of successful decision support systems for finance problems and their development methodology. On completion of the unit, students should be able to:

1. understand the needs of decision makers and apply techniques and tools to support various phases of the decision making process
2. formulate requirements for simulation and modelling and apply techniques of sensitivity analysis
3. analyse and design effective decision support systems for finance problems.

Mode of Delivery

Contact Hours

2 hrs lectures/wk, 1 hr laboratory/wk

Workload requirements

Students will be expected to spend a total of 12 hours per week during semester on this unit as follows:

• two hour lecture and
• one hour tutorial (or laboratory) (requiring advance preparation)
• a minimum of 3 hours of personal study per one hour of contact time in order to satisfy the reading and assignment expectations.

• You will need to allocate up to 5 hours per week in some weeks, for use of a computer, including time for newsgroups/discussion groups.

Unit Relationships

Prohibitions

BUS3030, AFF2051, AFW2051

Prerequisites

Completion of 24 points of FIT units at level 1

Chief Examiner

Campus Lecturer

Tutors

Academic Overview

Learning Outcomes

• familiarity with, and ability to apply, relevant decision support systems to the solution of financial problems;
• the ability to formulate, frame and solve financial problems in the context of appropriate decision support systems;
• an understanding of relevant finance concepts and understand how to apply those concepts in a practical setting.

• basic concepts of decision support systems;
• basic concepts of operational (investing and financing) finance;
• basic concepts and principles of decision support criteria as applied to operational finance;
• how decision support are applied to operational finance in organisations;
• opportunities, risks and liabilities arising from the usage and application of decision support in the context of operational finance in organisations;
• processes of acquiring, developing and managing decision support in the context of operational finance in organisations;
• techniques and tools (Excel spreadsheet modelling and Expert Choice for describing and analysing problems in operational finance in organisations under multicriteria decision making framework.

• recognise the importance of decision support systems in the context of operational finance to organisational processes and functions;
• recognise the opportunities and limitations of the role that decision support systems play in managing operational finance in organisations.

• assess the potential scope for using decision support systems as part of the solution to an organisational operational finance problem;
• understand how to apply decision support systems to help solve the operational finance problems of an organisation;
• appreciate the limitations of decision support systems and appreciate the role that human judgement plays in determining solutions for operational finance problems.

• Recognise the team skills necessary for successful development and implementation of decision support systems to operational finance problems in organisations;
• Appreciate the importance of the inter-relationships between IT professionals and the stakeholders in decision support systems in organisations.

Unit Schedule

*Unit Schedule details will be maintained and communicated to you via your learning system.

Assessment Summary

Examination (2 hours): 60%; In-semester assessment: 40%

Teaching Approach

• Lecture and tutorials or problem classes
  This teaching and learning approach provides facilitated learning, practical exploration and peer learning.
• Laboratory-based classes
  This teaching approach is practical learning.

Assessment Requirements

Assessment Policy

Faculty Policy - Unit Assessment Hurdles (http://www.infotech.monash.edu.au/resources/staff/edgov/policies/assessment-examinations/unit-assessment-hurdles.html)

Academic Integrity - Please see the Demystifying Citing and Referencing tutorial at http://lib.monash.edu/tutorials/citing/

Assessment Tasks

Participation

• Assessment task 1

  Title:

  Finance knowledge fundamental and analysis for DSS

  Description:

  A set of computational and discussion questions based on topics 1 to 4.

  Weighting:

  10%

  Criteria for assessment:

  This individual assignment will be based on computational questions using financial ratios and associated company specific factors.
  Criteria to be used are:

  1. Correctness and understanding - there may be more than one "right" answer in many cases. We will look for answers that reflect understanding of the underlying principles and theories.
  2. Completeness - that you have answered all parts of each question.
  3. Presentation - that you have presented your answers in a suitably formatted report style.
  4. Use of evidence and argument - you are able to explain your position by using logical argument drawing on the theory presented in the unit.

  Due date:

  Monday 15 April 2013, 4pm

• Assessment task 2

  Title:

  Analytic Hierarchical / Analytic Network Process/ Value at risk

  Description:

  A specific case on decision support systems for financial investment and risk management decision setup, using behavioural psychology and economic fundamentals criteria, and implemented on AHP / ANP with the help of Expert Choice software tool.
  
  Students are to work in groups of 2 to 4. A final group report of a minimum of 3000 words (excluding graphs and tables) is to be submitted by the set deadline. Each student must contribute at least 1000 words in the report write-up.

  Weighting:

  25%

  Criteria for assessment:

  1) Investment portfolio formulation methods. (30 / 100)

  2) Solution to investment portfolio to obtain optimum asset class allocation. (30 / 100)

  3) Discussion with interpretation of results and their implications. (30 / 100)

  4) Conclusion and recommendation of issues for further investigations. (10 / 100)

  The report will be graded according to the following criteria:

  1. All programs codes used to implement AHP must compile and run correctly to meet the problem specification.
  2. Correctness in the interpretation of results must be reported concisely.
  3. Recommendations made for investment decision taking must be theoretically justified and intuitively correct.

  The tutor will monitor individual contributions when allocating marks to members of the group.

  Due date:

  Monday 27 May 2013, 4pm

• Assessment task 3

  Title:

  Continuous assessment of tutorial participation

  Description:

  In order to meet unit group assessment objectives students are expected to attend all tutorial / practical classes, where they will engage in active group participation.

  Weighting:

  5%

  Criteria for assessment:

  The tutor in charge will monitor individual's participation of activities i.e. continuous assessment of tutorial tasks inclusive of quizzes when allocating marks to each student.

  Due date:

  At the end of each tutorial / lab class

Examinations

• Examination 1

  Weighting:

  60 %

  Length:

  2 hours

  Type (open/closed book):

  Closed book

  Electronic devices allowed in the exam:

  Students may use a financial calculator or programmable scientific calculator.

  Remarks:

  Multiple choice and discussion type questions.
  
  All formulae except definition of terms and ratios will be given.

Learning resources

Reading list

Brigham, E. F. and Houston, J. F. (2012), Fundamentals of Financial Management (Concise 7th Edition), South-western

Slaughter, S.J. and Delwiche, L. D. (2011), The Little SAS Book for Enterprise Guide 4.2, SAS

Charnes, J (2007), Financial Modelling with Crystal Ball and Excel + companion web site, ISBN 13: 978-0-471-77972-8, John Wiley

Feedback to you

• Informal feedback on progress in labs/tutes
• Graded assignments with comments
• Test results and feedback
• Other: Discussion of solution to tutes, labs (where applicable) and assignments

Extensions and penalties

Returning assignments

Resubmission of assignments

Resubmission or an extension of the submission dateline (up to 5 working days) may be granted if a medical certificate is produced.

Referencing requirements

Basic reading / reference materials for Assignment 2 will be issued. Students aiming for a HD grade are expected to explore / discuss and add innovations to methodology used in the assignment.

Assignment submission

Online submission

If Electronic Submission has been approved for your unit, please submit your work via the learning system for this unit, which you can access via links in the my.monash portal.

Required Resources

Excel Spreadsheet and Crystal Ball software. Expert Choice, or Matlab toolbox, or JAVA (JADE).

These will either be freely downloadable or available for use in University computer labs.  Further details to be advised.

Other Information

Policies

Graduate Attributes Policy

Student services

Monash University Library

Disability Liaison Unit

Your feedback to Us

Previous Student Evaluations of this Unit

Some modifications on assessment criteria. There are two assignments - one individual assignment and one group assignment, and no class test.