STATISTICS FOR BUSINESS AND FINANCE

BUS5SBF

2016

Credit points: 15

Subject outline

This subject develops basic quantitative skills to analyse real life problems in accounting, business and finance. It focuses on volatility measure of portfolio risk return distributions, basic concepts of probability and statistics, methods of statistical inference, measure of linear relationship between various business and finance variables including regression analysis. There is a strong emphasis on the application of these techniques to real world problems in business and finance using MS-Excel. This subject lays a solid foundation to the further study of quantitative analysis in business and finance. The contents of the subject are in line with 'Chartered Financial Analyst -CFA' quantitative analysis curriculum and hence follows CFA textbook.

SchoolLa Trobe Business School

Credit points15

Subject Co-ordinatorIshaq Bhatti

Available to Study Abroad StudentsYes

Subject year levelYear Level 5 - Masters

Exchange StudentsYes

Subject particulars

Subject rules

PrerequisitesN/A

Co-requisitesN/A

Incompatible subjects FIN5SBF

Equivalent subjects FIN5SBF

Special conditionsN/A

Learning resources

Readings

Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsQuantitive investment analysisPrescribedDeFusco, R, McLeavy,D., Pinto, J., Runkle,D.3rd . EDN. JOHN WILEY, 2015
ReadingsQuantitative investment analysis workbookPreliminaryDeFusco, R, McLeavy,D., Pinto, J., Runkle,D.3rd EDN, JOHN WILEY, 2015

Graduate capabilities & intended learning outcomes

01. Apply and interpret concepts of descriptive statistics to real life data and interpretation of results.

Activities:
Lecturing on cash flow topics with linkage to Statistical methodology
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)

02. Apply probability theory in business and financial decision making

Activities:
Based on lecture material, weekly computer labs are conducted to impliment statistical computations using SPSS software or Excel
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)

03. Develop competency in estimating linear regression models and testing hypothesis

Activities:
Assignment 2, computational work, interpretation of statistical results and report writing related to regression and hypothesis testing
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Quantitative Literacy)
Literacies and Communication Skills (Writing,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Discipline -Specific Knowledge and Skills (Discipline-Specific Knowledge and Skills)

04. Develop competency in running linear regressions based on CAPM model and testing hypotheses

Activities:
Assignment 2, computational work, interpretation of statistical results and report writing related to regression and hypothesiis testing
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Discipline -Specific Knowledge and Skills (Discipline-Specific Knowledge and Skills)

05. Develop ability to present work in a professional manner

Activities:
Presentation and interpretation of statistical results and report writing related to Multiple regression models related to return and CAPM Models
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Quantitative Literacy)
Literacies and Communication Skills (Writing,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Discipline -Specific Knowledge and Skills (Discipline-Specific Knowledge and Skills)

Subject options

Select to view your study options…

Start date between: and    Key dates

City Campus, 2016, Semester 2, Day

Overview

Online enrolmentYes

Maximum enrolment size60

Enrolment information Room size limitations at City Campus Limiting of numbers

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Seminar Week: 31 - 43
One 3.0 hours seminar per week from week 31 to week 43 and delivered via face-to-face.

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted AssignmentEquivalent to 750 words15 01, 02, 03
Assignment 2: Computer Assisted Assignment using Regression modelsEquivalent to 750 words15 03, 04, 05
Quiz 1During 5 week - 500 word10 01, 02
Quiz 2During 11 week - 500 words10 03, 04, 05
Final Exam3000 word equivalent50 03, 04, 05

City Campus, 2016, Semester 1, Day

Overview

Online enrolmentYes

Maximum enrolment size60

Enrolment information Room size Limiting of numbers

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Seminar Week: 10 - 22
One 3.0 hours seminar per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted AssignmentEquivalent to 750 words15 01, 02, 03
Assignment 2: Computer Assisted Assignment using Regression modelsEquivalent to 750 words15 03, 04, 05
Quiz 1During 5 week - 500 word10 01, 02
Quiz 2During 11 week - 500 words10 03, 04, 05
Final Exam3000 word equivalent50 03, 04, 05

City Campus, 2016, Summer, Day

Overview

Online enrolmentYes

Maximum enrolment size60

Enrolment information Room size limitations at City Campus Limiting of numbers

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Computer Laboratory Week: 45
One 1.0 hours computer laboratory per week on weekdays during the day in week 45 and delivered via face-to-face.
"Students need to obtain laptops from reception at Collins Street Campus or can provide own"

Lecture Week: 45
One 2.0 hours lecture per week on weekdays during the day in week 45 and delivered via face-to-face.

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted AssignmentEquivalent to 750 words15 01, 02, 03
Assignment 2: Computer Assisted Assignment using Regression modelsEquivalent to 750 words15 03, 04, 05
Quiz 1During 5 week - 500 word10 01, 02
Quiz 2During 11 week - 500 words10 03, 04, 05
Final Exam3000 word equivalent50 03, 04, 05

Melbourne, 2016, Semester 1, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorJae Kim

Class requirements

Laboratory Class Week: 11 - 22
One 1.0 hours laboratory class per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.
"this class is recommended but optional"

Lecture Week: 10 - 22
One 2.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted AssignmentEquivalent to 750 words15 01, 02, 03
Assignment 2: Computer Assisted Assignment using Regression modelsEquivalent to 750 words15 03, 04, 05
Quiz 1During 5 week - 500 word10 01, 02
Quiz 2During 11 week - 500 words10 03, 04, 05
Final Exam3000 word equivalent50 03, 04, 05

Melbourne, 2016, Semester 2, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Laboratory Class Week: 31 - 43
One 1.0 hours laboratory class other recurrence on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
"this class is recommended, but optional"

Lecture Week: 31 - 43
One 2.0 hours lecture other recurrence on weekdays during the day from week 31 to week 43 and delivered via face-to-face.

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted AssignmentEquivalent to 750 words15 01, 02, 03
Assignment 2: Computer Assisted Assignment using Regression modelsEquivalent to 750 words15 03, 04, 05
Quiz 1During 5 week - 500 word10 01, 02
Quiz 2During 11 week - 500 words10 03, 04, 05
Final Exam3000 word equivalent50 03, 04, 05

Melbourne, 2016, Summer, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Computer Laboratory
One 1.0 hours computer laboratory per week on weekdays during the day and delivered via face-to-face.
"this class is recommended, but optional"

Lecture
One 2.0 hours lecture per week on weekdays during the day and delivered via face-to-face.

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted AssignmentEquivalent to 750 words15 01, 02, 03
Assignment 2: Computer Assisted Assignment using Regression modelsEquivalent to 750 words15 03, 04, 05
Quiz 1During 5 week - 500 word10 01, 02
Quiz 2During 11 week - 500 words10 03, 04, 05
Final Exam3000 word equivalent50 03, 04, 05

Sydney, 2016, Study Period 1, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Laboratory Class Week: 10 - 22
One 1.0 hours laboratory class per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Lecture Week: 10 - 22
One 2.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted AssignmentEquivalent to 750 words15 01, 02, 03
Assignment 2: Computer Assisted Assignment using Regression modelsEquivalent to 750 words15 03, 04, 05
Quiz 1During 5 week - 500 word10 01, 02
Quiz 2During 11 week - 500 words10 03, 04, 05
Final Exam3000 word equivalent50 03, 04, 05

Sydney, 2016, Study Period 2, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Laboratory Class Week: 31 - 42
One 1.0 hours laboratory class per week on weekdays during the day from week 31 to week 42 and delivered via face-to-face.

Lecture Week: 31 - 42
One 2.0 hours lecture per week on weekdays during the day from week 31 to week 42 and delivered via face-to-face.

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted AssignmentEquivalent to 750 words15 01, 02, 03
Assignment 2: Computer Assisted Assignment using Regression modelsEquivalent to 750 words15 03, 04, 05
Quiz 1During 5 week - 500 word10 01, 02
Quiz 2During 11 week - 500 words10 03, 04, 05
Final Exam3000 word equivalent50 03, 04, 05

Sydney, 2016, Study Period 3, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Laboratory Class Week: 46
One 1.0 hours laboratory class per week on weekdays during the day in week 46 and delivered via face-to-face.

Lecture Week: 46
One 2.0 hours lecture per week on weekdays during the day in week 46 and delivered via face-to-face.

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted AssignmentEquivalent to 750 words15 01, 02, 03
Assignment 2: Computer Assisted Assignment using Regression modelsEquivalent to 750 words15 03, 04, 05
Quiz 1During 5 week - 500 word10 01, 02
Quiz 2During 11 week - 500 words10 03, 04, 05
Final Exam3000 word equivalent50 03, 04, 05