Due to COVID-19 restrictions, a selection of on-campus papers will be made available via distance and online learning for eligible students.
Find out which papers are available and how to apply on our COVID-19 website
Examines financial analytical methods for the analysis of cross-sectional 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 | Financial Analytics |
|---|---|
| Paper code | FINC412 |
| Subject | Finance |
| EFTS | 0.1667 |
| Points | 20 points |
| Teaching period | Semester 2 (On campus) |
| Domestic Tuition Fees (NZD) | $1,113.72 |
| International Tuition Fees (NZD) | $5,177.04 |
- Recommended Preparation
- FINC 302 and FINC 308
- Notes
- May not be credited with FINC499 taken in 2019 or 2020
- Contact
- 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
Global perspective, Interdisciplinary perspective, Lifelong learning, Scholarship, Communication, Critical Thinking, Information Literacy, Research, Self-motivation
View more information about Otago's graduate attributes.- Learning Outcomes
Students who successfully complete the paper will be able to:
- Understand financial data (in particular, CRSP via WRDS and Bloomberg)
- 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
Timetable
Examines financial analytical methods for the analysis of cross-sectional and time-series data on stock returns.
| Paper title | Financial Analytics |
|---|---|
| Paper code | FINC412 |
| Subject | Finance |
| EFTS | 0.1667 |
| Points | 20 points |
| Teaching period | Semester 2 (On campus) |
| Domestic Tuition Fees | Tuition Fees for 2022 have not yet been set |
| International Tuition Fees | Tuition Fees for international students are elsewhere on this website. |
- Recommended Preparation
- FINC 302 and FINC 308
- Notes
- May not be credited with FINC499 taken in 2019 or 2020
- Contact
- Teaching staff
To be confirmed
- Textbooks
To be confirmed
- Graduate Attributes Emphasised
- Critical thinking.
View more information about Otago's graduate attributes. - Learning Outcomes
To be confirmed
