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ECONS507-19T (HAM)
Quantitative Skills for Finance and Economics
15 Points
Staff
Convenor(s)
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Susan Olivia
4112
MSB.2.11
Thursdays 3-5pm or by appointment
susan.olivia@waikato.ac.nz
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Lecturer(s)
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Susan Olivia
4112
MSB.2.11
Thursdays 3-5pm or by appointment
susan.olivia@waikato.ac.nz
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Administrator(s)
Librarian(s)
You can contact staff by:
- Calling +64 7 838 4466 select option 1, then enter the extension.
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Extensions starting with 4, 5, 9 or 3 can also be direct dialled:
- For extensions starting with 4: dial +64 7 838 extension.
- For extensions starting with 5: dial +64 7 858 extension.
- For extensions starting with 9: dial +64 7 837 extension.
- For extensions starting with 3: dial +64 7 2620 + the last 3 digits of the extension e.g. 3123 = +64 7 262 0123.
Paper Description
The exponential growth in the availability of data requires that students are able to make informed decisions using data, and effectively communicate their data analyses.This course covers the analytical and statistical techniques that business and management students are most likely to use in their future courses and professional careers. Students will learn different types of data analytics methods and their applications to problems in accounting, economics, finance, marketing, and business in general.
This course uses a combination of lectures, case discussions, lab sessions and student presentations. Students will have hands-on work with data and Microsoft Excel. Weekly computer-based workshops aim to enhance understanding of how the techniques introduced in lectures apply in a business context. Topics to be covered include presenting data using visual and descriptive statistics, measuring and understanding the relationship between variables, predictive analytics and prescriptive analytics tools. Empirical examples from economics, finance, accounting, and marketing will illustrate the material covered. Emphasis will be placed on understanding concepts and analysis of data. The paper will also provide opportunities for students to enhance their teamwork and communication skills with an empirical group research project and poster presentation.
Paper Structure
Two 3-hour in-class lectures and one 3-hour computer labs per week. Attendance at lectures and computer labs is strongly encouraged.
Lectures
The lectures will be focused on teaching quantitative methods to students who want to apply data and regression analysis techniques sensibly in the context of real-world empirical problems. They will also feature some discussion based on applied econometric theory, these will draw on practical examples that demonstrate the interpretation of results provided by various techniques.
Computer Labs
The main purpose of the computer classes will be to provide students with practical experience of using the econometric techniques covered in the lectures. In labs, you will be given a set of questions and exercises to complete using Microsoft Excel. The computer classes will also be a forum for students to discuss the lecture material and attempt various problem-solving exercises that might be set over the weeks.
In order to promote class participation and to provide immediate in-class feedback about specific concepts, we will use the Xorro-Q student response system. To participate, students will need an internet capable device (e.g. laptop, smartphone, tablet). The lecture theatres are all Wi-Fi enabled and there are no data charges for accessing the Xorro-Q website on campus. Instructions on how to use Xorro-Q will be provided on Moodle.
Learning Outcomes
Students who successfully complete the course should be able to:
Assessment
Assessment Components
The internal assessment/exam ratio (as stated in the University Calendar) is 100:0. There is no final exam.
Required and Recommended Readings
Required Readings
Camm, J., Cochran, J., Fry, M., Ohlmann, J., Anderson, D., Sweeney, D., and T. Williams (2019) Business Analytics, 3rd edition, Cengage Learning.
Recommended Readings
Duignan, J. (2014) Quantitative Methods for Business Research Using Microsot Excel, Cengage Learning (On Course Reserve)
Koop, G (2013) Analysis of Economic Data, Wiley (on Course Reserve)
Hyndman, R. and Athanasopoulos, G. (2018) Forecasting: Principles and Practice, 2nd ed., OTexts: Melbourne, Australia (freely available online at https://otexts.com/fpp2)
Other Resources
In addition to the required textbook, students are encouraged to read widely including the business section of newspaper, the Economist magazine, and other similar sources. Additional paper resources will be made available on Moodle.
The following websites are examples of Data Analytics being used in practice:
Waikato University also has several databases available for students with interests in Finance, which include:
- NZX Company Research(formerly NZX Deep Archive), which provides historical information on New Zealand Companies
- Datastreamwhich provides key data sets from both developed and emerging markets. Current and historical data is available variables such as - equities, market indices, company accounts, economic indicators, bonds, foreign exchange, interest rates, commodities and derivatives.
Online Support
Workload
According to the university points system, students are expected to spend 150 hours in total on a 15-point paper.
Since you are taking a paper in Economics, we know that you will make rational and optimal (to you) decisions about the work you will put into the paper. Thus, the workload the paper places on you will depend on your preferences, what you want to achieve and the constraints you face.