FINAN520-20G (HAM)

Financial Econometrics

15 Points

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Division of Management
School of Accounting, Finance and Economics

Staff

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Convenor(s)

Lecturer(s)

Administrator(s)

: denise.martin@waikato.ac.nz

Placement/WIL Coordinator(s)

Tutor(s)

Student Representative(s)

Lab Technician(s)

Librarian(s)

: clive.wilkinson@waikato.ac.nz

You can contact staff by:

  • Calling +64 7 838 4466 select option 1, then enter the extension.
  • Extensions starting with 4, 5, 9 or 3 can also be direct dialled:
    • For extensions starting with 4: dial +64 7 838 extension.
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    • For extensions starting with 3: dial +64 7 2620 + the last 3 digits of the extension e.g. 3123 = +64 7 262 0123.
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Paper Description

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The goal of this paper is to familiarize students with the R statistical and programming language. R is a widely used open source tool for data analytics. Lecture notes and slides integrate the discussion of the methods and their application with the implementation in R in a learning-by-doing manner.

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Paper Structure

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  • Assignment
  • Presentation
  • Class participation
  • Tutorial & Lecture
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Learning Outcomes

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Students who successfully complete the paper should be able to:

  • know with the basic setting of R software
    Linked to the following assessments:
  • perform basic analysis using R
    Linked to the following assessments:
  • create graphs in R
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  • Apply, interpret and communicate the results of the models using R.
    Linked to the following assessments:
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Assessment

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The application for special consideration can be found under Files. Further information is available at
http://www.waikato.ac.nz/sasd/examinations/exams3.shtml
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Assessment Components

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The internal assessment/exam ratio (as stated in the University Calendar) is 100:0. There is no final exam. The final exam makes up 0% of the overall mark.

The internal assessment/exam ratio (as stated in the University Calendar) is 100:0 or 0:0, whichever is more favourable for the student. The final exam makes up either 0% or 0% of the overall mark.

Component DescriptionDue Date TimePercentage of overall markSubmission MethodCompulsory
1. Class participation
11 Dec 2020
No set time
10
2. Assignment 1
22 Nov 2020
5:00 PM
30
  • Online: Submit through Moodle
3. Assignment 2
6 Dec 2020
5:00 PM
30
  • Online: Submit through Moodle
4. Presentation
17 Dec 2020
5:00 PM
30
  • Presentation: In Class
Assessment Total:     100    
Failing to complete a compulsory assessment component of a paper will result in an IC grade
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Required and Recommended Readings

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Recommended Readings

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Singh, A. K., & Allen, D. E. (2016). R in finance and economics: A beginner's guide. World Scientific Publishing Company.

Carmona, R. (2014). Statistical analysis of financial data in R (Vol. 2). New York: Springer.

Tsay, R. S. (2014). An introduction to analysis of financial data with R. John Wiley & Sons.

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Online Support

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All the teaching resources will be available in Moodle. Updates will be made as necessary.
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Workload

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There are 150 learning hours for this paper. The time is devoted to the following activities:

  • Watch lecture recordings;
  • Attend tutorials;
  • Read teaching materials;
  • Prepare for presentation;
  • Complete individual assignments.
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Linkages to Other Papers

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Prerequisite(s)

Acceptance into the Master of Applied Finance programme.

Corequisite(s)

Equivalent(s)

Restriction(s)

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