This paper provides students enrolled in the Master of Applied Finance (MAppFin) with a thorough grounding in the applied quantitative techniques required for professional practice in business, finance, and economics. The main emphasis is to attain some particular skills that are appropriate and needed for solving business problems that require quantitative solutions and interpreting the results.

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 learn to apply skills in data analysis and applied regression methods to a broad range of topics including business applications, corporate and international finance, international economics and macroeconomics using time series and panel data at household, firm and country levels. The topics covered include data analysis; correlation vs.causation; simple regression analysis; multiple regression analysis; regression diagnostics; regression with dummy variables; transformation of variables and econometric issues with time series and panel data. The skills acquired from the course can be applied to problems in accounting, economics, finance, marketing, and business in general. This course uses a combination of lectures and lab sessions. Students will have hands­on work with data. Weekly computer­based 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, and predictive 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 is taught via a combined two hours lecture plus computer lab each week.

Lecture: Each lecturer is combined with theoretical discussions and practical demonstrations. Therefore, lectures are held in the lab to demonstrate the theoretical calculations. Attendance at lectures 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 real­world 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 the software package STATA and EVIEWS, both are available in the lab computers. You may also obtain students versions of the software which cost less than the full version. The computer classes will also be a forum for students to discuss the lecture material and attempt various problem­solving exercises that might be set over the weeks.

Below are some suggested useful reference texts to supplement lecture notes.

• Introductory Econometrics: A Modern Approach by Jeffrey Wooldridge 6th Ed (Cengage)
• Forecasting: Principles and Practice by R.J. Hyndman; G. Athanasopoulos 2018
• Mostly harmless econometrics: An empiricist's companion by J.D. Angrist; J­S. Pischke 2009
• Econometrics for dummies by R. Pedace 2013

OTHER RESOURCES
The following two texts are useful for quantitative approaches to finance/economics:

• Duignan, J. (2014) Quantitative Methods for Business Research Using Microsot Excel, Cengage Learning (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 (https://otexts.com/fpp2/))

In addition to the lecture notes, recommended textbooks and those in the reading lists, 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:

http://fivethirtyeight.com/ (http://fivethirtyeight.com/)
https://www.gapminder.org/ (https://www.gapminder.org/)
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
Datastream which 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.

Resources on STATA:
http://www.ats.ucla.edu/stat/stata/
https://www.youtube.com/user/statacorp/featured (https://www.youtube.com/channel/UCVk4G4nEtBS4tLOyHqustDA)

ONLINE SUPPORT
All course materials, plus other information of importance to students, are available via Moodle

WORKLOAD
According to the university points system, students are expected to spend 150 hours in total on a 15­point 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.

PREREQUISITE(S)
Prerequisite papers: Acceptance into the MPAcct or MAppFin programme.