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FINC203 Financial Data Analysis

A second course in business statistics with an emphasis on data analysis in finance problems.

The main aim of the paper is to provide students with a course in financial and economic data analysis using statistical techniques based on the Microsoft Excel spreadsheet. This paper is designed to prepare students to develop the skills of the students such as critical thinking, information literacy, research and self-motivation of analysing the information by using regression and time series models. This paper focuses on solving a variety of practical problems using computer spreadsheets.

Paper title Financial Data Analysis
Paper code FINC203
Subject Finance
EFTS 0.1500
Points 18 points
Teaching period First Semester
Domestic Tuition Fees (NZD) $863.25
International Tuition Fees (NZD) $4,276.80

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Prerequisite
BSNS 102 or BSNS 112 (passed with a grade of at least C+)
Pre or Corequisite
FINC 102 or FINQ 102
Restriction
ECON 210, STAT 210, STAT 241
Schedule C
Commerce
Notes
MATH 170 will be accepted as an alternative to FINC 102 or FINQ 102 when that paper has already been passed or where a student is enrolled for both a BCom and another degree for which MATH 170 is required.
Contact
accountancyfinance@otago.ac.nz
Teaching staff

Dr Duminda Kuruppuarachchi

Teaching Arrangements

Lectures and computer labs

Textbooks

Analysis of Financial Data by Gary Koop, John Wiley & Sons, (2006) ISBN: 9780470013212.

Course outline
View the course outline for FINC 203
Graduate Attributes Emphasised
Critical thinking, Information literacy, Research and Self-motivation.
View more information about Otago's graduate attributes
Learning Outcomes

Students who successfully complete the paper will be able to:

  1. Understand of the properties of variables from financial markets
  2. Understand the pragmatic use of statistics in Commerce
  3. Understand and apply the concept of simple and multiple linear regression in the analysis of cross-sectional datasets collected under various contexts.
  4. Understand and apply the concept of basic time series regression models.
  5. Develop fundamental research skills (such as data collection, data processing, and model estimation and interpretation) in applied financial analysis.
  6. Emphasize techniques used by Financial and Economic Analysts

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Further information about teaching staff, tutorial times, assessment details, reading lists and learning objectives is available in the PDF below.

Download Course Outline for FINC203 2018 Semester 1

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Timetable

First Semester

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Blackboard

Computer Lab

Stream Days Times Weeks
Attend one stream from
Z1 Monday 09:00-09:50 11-13, 19-21
Z2 Monday 10:00-10:50 11-13, 19-21
Z3 Monday 12:00-12:50 11-13, 19-21
Z4 Monday 13:00-13:50 11-13, 19-21
Z5 Monday 11:00-11:50 11-13, 19-21

Lecture

Stream Days Times Weeks
Attend
M1 Monday 14:00-15:50 9-13, 19-22
Tuesday 16:00-16:50 9-12, 18-22
Wednesday 16:00-16:50 9-12, 18-22

A second course in business statistics with an emphasis on data analysis in finance problems.

The main aim of the paper is to provide students with a course in financial and economic data analysis using statistical techniques based on the Microsoft Excel spreadsheet. This paper is designed to prepare students to develop skills such as critical thinking, information literacy, research and self-motivation for analysing the information by using regression and time series models. This paper focuses on solving a variety of practical problems using computer spreadsheets.

Paper title Financial Data Analysis
Paper code FINC203
Subject Finance
EFTS 0.15
Points 18 points
Teaching period First Semester
Domestic Tuition Fees Tuition Fees for 2021 have not yet been set
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

^ Top of page

Prerequisite
BSNS 102 or BSNS 112 (passed with a grade of at least C+)
Pre or Corequisite
FINC 102 or FINQ 102
Restriction
ECON 210, STAT 210, STAT 241
Schedule C
Commerce
Notes
MATH 170 will be accepted as an alternative to FINC 102 or FINQ 102 when that paper has already been passed or where a student is enrolled for both a BCom and another degree for which MATH 170 is required.
Contact
accountancyfinance@otago.ac.nz
Teaching staff

Dr Duminda Kuruppuarachchi

Teaching Arrangements

This paper is taught via lectures and computer labs.

Textbooks

Analysis of Financial Data by Gary Koop, John Wiley & Sons, (2006) ISBN: 9780470013212.

Course outline
View the course outline for FINC 203
Graduate Attributes Emphasised
Critical thinking, Information literacy, Research and Self-motivation.
View more information about Otago's graduate attributes
Learning Outcomes

Students who successfully complete the paper will be able to

  1. Understand of the properties of variables from financial markets
  2. Understand the pragmatic use of statistics in Commerce
  3. Understand and apply the concept of simple and multiple linear regression in the analysis of cross-sectional datasets collected under various contexts
  4. Understand and apply the concept of basic time series regression models
  5. Develop fundamental research skills (such as data collection, data processing, and model estimation and interpretation) in applied financial analysis
  6. Emphasize techniques used by Financial and Economic Analysts

^ Top of page

Further information about teaching staff, tutorial times, assessment details, reading lists and learning objectives is available in the PDF below.

Download Course Outline for FINC203 2018 Semester 1

^ Top of page

Timetable

First Semester

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Blackboard

Computer Lab

Stream Days Times Weeks
Attend one stream from
Z1 Monday 09:00-09:50 11-13, 15-16, 18-21
Z2 Monday 10:00-10:50 11-13, 15-16, 18-21
Z3 Monday 11:00-11:50 11-13, 15-16, 18-21
Z4 Monday 12:00-12:50 11-13, 15-16, 18-21
Z5 Monday 13:00-13:50 11-13, 15-16, 18-21

Lecture

Stream Days Times Weeks
Attend
M1 Monday 14:00-15:50 9-13, 16, 18-22
Tuesday 16:00-16:50 9-13, 15-22
Wednesday 16:00-16:50 9-13, 15-22