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APPENDIX - Details of Elective Courses
COURSE TITLE Applied Econometrics
COURSE CODE CQC7054
At the end of the course, students are able to:
1. Estimate using statistical analysis, including the classical regression
model, to estimate relevant economic parameters, predict economic
outcomes, and test economic hypotheses using quantitative data.
2. Formulate the basic assumptions of the classical linear regression
LEARNING
OUTCOMES model and correct any violations of these assumptions, such as
autocorrelation, multicollinearity, heteroscedasticity and other biasness.
3. Formulate time series data analysis and find quantitative solutions via
applying latest software in social science research.
4. Formulate panel data analysis and find quantitative solutions via
applying latest software in social science research.
Throughout these course students will be exposed to econometrics methods
SYNOPSIS being used in cross sectional data, time series data and panel data by using
statistical software.
COURSE TITLE Digital Finance
COURSE CODE CQC7061
At the end of the course, students are able to:
1. Examine the nature and developments of digital finance related to
money, lending and payment systems.
2. Demonstrate the applications of digital finance innovations in financial
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OUTCOMES markets.
3. Evaluate the risk and challenges of digital finance applications among
consumers and businesses and their implications to regulations.
4. Describe the role and future of digital finance in designing business
solutions.
In this course, students are introduced to the nature and evolutions of digital
finance. The applications of digital finances in relation to money, lending,
payment systems and financial market are examined. This course also
SYNOPSIS discusses the risk and challenges brought about by the usage of digital
finance among consumers and business and how these issues impact
regulations. Finally, students will be able to describe the role and future of
digital finance in business decision making.
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