Investment

In this course, we start with a brief review of elementary tools in finance and wide range of financial instruments available in major asset classes, their specific features and cash flows. The course later covers financial market theory, the basic theoretical underpinnings of behavioral, quantitative, and macroeconomic approaches to portfolio management, strategic and tactical asset allocation, and methods used in the development of investment strategies.

The course provides a comprehensive overview of the financial system, including major financial markets, institutions and instruments. Students will learn the fundamentals of the global money, capital and foreign exchange markets, the determinants of financial prices and yields and the basic quantitative tools and perspectives used to evaluate financial prices and risks.

The topic of focus this semester will be on text generation and recent developments in pretraining. We will study recent advances in text generation with neural networks and the potential of machine learning methods to develop a clear and accurate natural text. The course will concentrate on developing applied mastery of the central models and algorithms of machine learning, such as multinomial models, multi-class logistic regression, and, particularly this year, a focus on deep learning/neural network models such as convolutional networks (CNN) and recurrent neural networks (RNN).

Python is a language with a simple syntax and a powerful set of libraries. It is an interpreted language, with a rich programming environment, including a robust debugger and profiler. While it is easy for beginners to learn, it is widely used in many scientific areas for data exploration. This course is an introduction to the Python programming language for students without prior programming experience. We cover data types, control flow, object-oriented programming, and graphical user interface-driven applications.

This course investigates methods implemented in multiple quantitative trading strategies with an emphasis on automated trading and quantitative finance-based approaches to enhance the trade decision-making mechanism. The course provides a comprehensive view of the algorithmic trading paradigm and some of the key quantitative finance foundations of these trading strategies. Topics explore markets, financial modeling and its pitfalls, factor model-based strategies, portfolio optimization strategies, and order execution strategies.

This course "FinTech Security and Regulation (RegTech)" help you to understand RegTech and to become more confident and persuasive in your ability to analyze and make recommendations to executives within the finance industry regarding how to react to these changes, e.g., Regulations to cryptocurrencies like BitCoin & Initial Coin Offering (ICO). It presents the views of several professors from the top business school in Asia as well as perspectives from industry professionals.

Strategic Management is one of the most cross-functional management course, which emphasizes the comprehensive application of basic knowledge in core courses of the discipline. The basic question to be answered in this course is how an enterprise could gain its sustainable competitive advantage in a dynamic environment. This course will spotlight some of the important issues in strategic management by concentrating on modern analytical tools and successful strategic practices, particularly those tools and practices that focus on the evolving nature of global business competition.