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FINC499 Special Topic: Empirical Methods in Finance

Provides an understanding of the methods used in empirical asset pricing and financial econometrics, preparing students for independent research and finance industry careers.

The aim of this course is to deliver the knowledge on two major areas in Empirical Finance namely, Empirical Asset Pricing (Part 1) and Advanced Financial Econometrics (Part 2). Empirical asset pricing consists of a wide range of applications in investments and corporate finance, which will be essential to those students who are willing to enter the investment banking and corporate finance professions. Financial Econometrics helps students to empirically test theories; understand relationships between variables that can be used in research and are of interest for businesses and financial institutions.

Paper title Special Topic: Empirical Methods in Finance
Paper code FINC499
Subject Finance
EFTS 0.1667
Points 20 points
Teaching period Second Semester
Domestic Tuition Fees (NZD) $1,079.88
International Tuition Fees (NZD) $4,786.79

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Restriction
FINC 406
Notes

May not be credited with FINC 499 taken in 2018.

Recommended preparation: (FINC 308 or ECON 375) and two further 300 level FINC papers.

Contact

accountancyfinance@otago.ac.nz

Teaching staff

Dr Duminda Kuruppuarachchi
Dr Edwin Ruan

Paper Structure

The paper covers two key themes:

  1. Empirical Asset Pricing
  2. Advanced Financial Econometrics

Teaching Arrangements

STATA software will be available for the students via Student Desktop platform to use during the lectures.

Textbooks

Recommended:
Bali, T. G., Engle, R. F., and Murray, S. (2016). Empirical Asset Pricing: The Cross Section of Stock Returns. John Wiley & Sons.
Carter Hill, R., Griffiths, William E., and Lim, G. C. (2018). Principles of econometrics, 5th ed. Wiley: Hoboken, NJ.

Course outline

View the course outline here

Graduate Attributes Emphasised

  • Information Literacy
  • Independent Learning
  • Critical Thinking
  • Specialist Business Knowledge
  • Written Communication
  • Oral Communication
  • Teamwork


View more information about Otago's graduate attributes.

Learning Outcomes

Students who successfully complete the paper will:

  • Identify the sources of financial data (in particular, CRSP and Compustat) and know how to use them to construct corresponding investment factors (market beta, firm value, book-to-market ratio, etc.).
  • Demonstrate the knowledge on investment analysis such as one-way and two-way portfolio sorting and Fama-Macbeth regression analysis
  • Apply appropriate portfolio sorting and Fama-Macbeth regression analysis in solving financial investment problems in academic research and in practice (e.g. investment banks) by using STATA software.
  • Understand the types and forms of data and identify the relevant sources (Bloomberg, DataStream, Yahoo Finance, etc.) to be used to perform an econometric analysis.
  • Demonstrate the knowledge on econometric techniques such as generalized linear models, univariate and multivariate time series analysis, and panel data analysis.
  • Apply appropriate econometric techniques in solving financial problems that arise in financial industry and real life and research using the STATA software.
  • Demonstrate the ability to report, interpret and present the results obtained from an investment and/or econometric analysis.

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Timetable

Second Semester

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
None

Lecture

Stream Days Times Weeks
Attend
A1 Monday 10:00-11:50 28-34, 36-41
Wednesday 10:00-11:50 28-33, 36-41

Examines financial analytical methods for the analysis of cross-section and time-series data on stock returns.

Financial analytics is the in-depth analysis of large financial datasets using statistical methods and programming. It has a wide range of applications in investments and corporate finance, including assisting with the construction and evaluation of investment opportunities. Financial analytics is essential for students who wish to enter the investment banking and corporate finance professions. It also provides a strong base for research in finance.

Paper title Special Topic: Financial Analytics
Paper code FINC499
Subject Finance
EFTS 0.1667
Points 20 points
Teaching period Second Semester
Domestic Tuition Fees Tuition Fees for 2020 have not yet been set
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

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Notes
May not be credited with FINC 499 taken in 2019.
Contact

accountancyfinance@otago.ac.nz

Teaching staff

Lecturer: Edwin Ruan

Paper Structure

The paper covers two key themes:

  • Cross-sectional analysis
  • Time-series analysis
Teaching Arrangements

Stata software will be available for the students via Student Desktop platform to use during the lectures.

Textbooks

Empirical Asset Pricing: The Cross Section of Stock Returns by T. G. Bali, R. F. Engle, S. Murray, John Wiley & Sons, 2016.

E-book is available in library at
https://ebookcentral-proquest-com.ezproxy.otago.ac.nz/lib/otago/detail.action?docID=4451896.

Graduate Attributes Emphasised

Information Literacy, Independent Learning, Critical Thinking, Research, Written Communication, Oral Communication
View more information about Otago's graduate attributes.

Learning Outcomes

Students who successfully complete the paper will be able to:

  • Identify the sources of financial data (in particular, CRSP and Compustat via WRDS)
  • Acquire the programming skills in a particular statistical software (e.g., Stata)
  • Demonstrate the knowledge on cross-sectional analysis, such as portfolio analysis and Fama-Macbeth regression analysis
  • Apply the knowledge on time-series analysis, such as in-sample analysis, out-of-sample analysis and asset allocation analysis
  • Demonstrate appropriate financial analytics in solving financial investment problems in academic research and in practice (e.g. investment banks) by using a statistical software
  • Acquire the ability to report, interpret and present the results

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Timetable

Second Semester

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
None

Lecture

Stream Days Times Weeks
Attend
A1 Monday 10:00-11:50 28-34, 36-41
Wednesday 10:00-11:50 28-34, 36-41