CFA Examination Preparatory Course
Prepares you for the CFA® Examinations
Aiming to provide the academic knowledge and practical skill to candidates to sit for three levels of the Chartered Financial Analyst (CFA) examinations.
HKU SPACE is glad to offer the CFA® Level I, II and III Examination Preparatory Programmes to help CFA® candidates prepare for the forthcoming examinations.
Based on the curriculum of the CFA Program, three programmes provide candidates with the Candidate Body Of Knowledge (CBOK), which includes the core knowledge, skills and abilities generally accepted and applied by global investment professionals.
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The programme aims to prepare students to sit for the Chartered Financial Analyst (CFA) Level I examination. It will provide students with knowledge of quantitative methods, economic and financial analysis, and portfolio management. It also covers the ethical and professional standards requirement for an asset manager.
The programme aims to prepare students to sit for the Chartered Financial Analyst (CFA) Level II examination. It will provide students with the knowledge in economic and corporate financial analysis, the valuation techniques of investment assets and issues of portfolio management.
The programme aims to prepare students to sit for the Chartered Financial Analyst (CFA) Level III examination. It will provide students with the advanced knowledge to evaluate various asset classes in investment portfolios and perform asset allocation in synthesized cases. It also enables students to perform wealth planning and portfolio management holistically.
Students will learn how to build three-statement financial models as it is done on Wall Street. Students will explore best practices, discover optimal model flow and design, strengthen Excel practical skills and tackle more complex modeling cases in practice.
Students will learn the skills required for success as buy-side and sell-side equity research analysts. Students will also explore how to conduct thorough industry research, research companies strategically, forecast accurately, identify mispricings, and make recommendations based on their work.
Students will follow the data science workflow from financial data ingestion to training artificial neural networks. Also, students will have the opportunity to pull financial data and use the standard tools and techniques to prepare it to deliver insights, work through an example of forecasting percentage change in EPS, and explore a common natural language processing task of sentiment analysis.
Students will explore the basics of Python and how to use Jupyter Notebooks to develop, present, and share data science projects related to finance. Also, the workshop assists students to quickly build up their coding skills and apply them to dozens of industry-specific examples.
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