Page 108 - 2024.2025 - 澳門理工大學研究生課程手冊 (電子書) (PDF)

ENGLISH

STUDY PLAN & MODULE DESCRIPTIONS
Code Module Credits Duration Prerequisite(s)

Table I: Compulsory Modules
FIDA6121 Financial Statement Analysis and 3 45 hrs ---
Business Ethical Standards
This module is designed to equip students with the insights and analytic techniques to
critically analyze and interpret corporate financial reports and associated information
from user’s perspective in order to assess the “economic reality” of firms’ financial
status, operational results, risks and equity value. This module will also provide students
with an overview of business ethics and ethical management practices, with emphasis
on the ethical responsibilities required of CFA Institute members. It is intended to
demonstrate to the students how ethics can be integrated into business decisions and
can be applied to their own careers.
FIDA6122 Corporate Finance 3 45 hrs ---
This module will systematically examine the fundamental theories of finance, techniques
of asset valuation and its applications at the corporate level. Topics covered include the
concept of present value, the opportunity cost of capital, valuation of cash-flow streams,
bonds, and stocks, relationships between risk and return, capital asset pricing model,
capital budgeting, corporate capital structure and dividend policy, etc.

FIDA6123 Investment Analysis and Portfolio 3 45 hrs ---
Management
This module introduces the fundamental principles of investment analysis and the
theories and techniques of portfolio management and covers the major issues currently
of interest to investors. The first part covers investment environment, risk and return
trade-off, portfolio diversification, modern portfolio theory, and market efficiency. The
second part covers basic analytical tools used in analyzing fixed income securities
including interest rates and yield curve mathematics, duration and convexity. Portfolio
performance evaluation is also covered.

FIDA6124 Data Analysis and Visualization 3 45 hrs ---
Big data analytics is the process of examining large and complex data to uncover
information that can inform better business decisions. Analysing big data requires a
variety of approaches, including techniques such as predictive analytics, machine
learning, and statistical algorithms. The primary purpose of this module is to provide
students with an understanding of the data analytics approach in finance. The first part
of this module introduces the basics of a popular programming language in data analytics
such as Python and its important packages for data analytics. Another more popular
programming language instead of Python may be used. The second part will concentrate
on the data analytics and data visualization techniques for financial applications. Topics
covered may include financial time series analysis, Stochastic modelling, and derivatives
analytics.

102