This course will cover an overview of financial technology and its various applications. The specific topics include fintech and financial service, cryptocurrencies, high-frequency trading, peer-to-peer lending, etc. The course will help students learn fintech industry through case studies. It also provides students with a unique opportunity to delve deep into one aspect of financial technology and write an extensive paper/report on this topic. Topics include (but are not limited to): Data-driven credit models, Cryptocurrencies, Digital wallets, Blockchain and its applications, Financial cloud services, Robo advising, Crowd-funding, Peer-to-Peer lending, High-frequency trading, Payments, Artificial Intelligence, Digital banking, Defi (Decentralized Finance), NFT, etc.

This course will cover an overview of financial technology and its various applications. The specific topics include fintech and financial service, cryptocurrencies, high-frequency trading, peer-to-peer lending, etc. The course will help students learn fintech industry through case studies. It also provides students with a unique opportunity to delve deep into one aspect of financial technology and write an extensive paper/report on this topic. Topics include (but are not limited to): Data-driven credit models, Cryptocurrencies, Digital wallets, Blockchain and its applications, Financial cloud services, Robo advising, Crowd-funding, Peer-to-Peer lending, High-frequency trading, Payments, Artificial Intelligence, Digital banking, Defi (Decentralized Finance), NFT, etc.

This course provides an overview of statistical analysis and inference. The language and methods of statistics are used throughout the MBA curriculum, both in the classroom and in assigned readings. In addition, the language and methods of statistical analysis have permeated much of academic and professional writing as well as media reporting, both inside and beyond the business community. The goal is to present a broad introduction to statistical thinking, concepts, methods, and vocabulary. The course has an emphasis on business applications.

This course provides an overview of statistical analysis and inference. The language and methods of statistics are used throughout the MBA curriculum, both in the classroom and in assigned readings. In addition, the language and methods of statistical analysis have permeated much of academic and professional writing as well as media reporting, both inside and beyond the business community. The goal is to present a broad introduction to statistical thinking, concepts, methods, and vocabulary. The course has an emphasis on business applications.

This course provides an overview of statistical analysis and inference. The language and methods of statistics are used throughout the MBA curriculum, both in the classroom and in assigned readings. In addition, the language and methods of statistical analysis have permeated much of academic and professional writing as well as media reporting, both inside and beyond the business community. The goal is to present a broad introduction to statistical thinking, concepts, methods, and vocabulary. The course has an emphasis on business applications.

This course provides an overview of statistical analysis and inference. The language and methods of statistics are used throughout the MBA curriculum, both in the classroom and in assigned readings. In addition, the language and methods of statistical analysis have permeated much of academic and professional writing as well as media reporting, both inside and beyond the business community. The goal is to present a broad introduction to statistical thinking, concepts, methods, and vocabulary. The course has an emphasis on business applications.

The focus of this course is on the financial theory and empirical evidence that are relevant to management of investment portfolios. The topics covered include the relation between risk and return, diversification, asset allocation, portfolio optimization, factor models, market efficiency, and other related topics. The course will focus on the tools, applications, and concepts that go into investments. It relies heavily on quantitative methods and provides students with the ability to build valuation models to suit various investment strategies. Students will also gain an understanding of how investment theory relates to investment and management practices in the real world.

This course reviews the foundations of modern economics with an emphasis on its applications in business. Course coverage includes a range of both microeconomic and macroeconomic subjects. Topics include demand and supply analysis, consumer theory, theory of the firm, unemployment, inflation, monetary and fiscal policy, economic growth, the causes and consequences of recessions, and issues in global economics.

This course examines the principles and practice of valuing firms, projects, and assets, blending rigorous financial modeling with the art of storytelling. Students will learn to develop and defend valuations using discounted cash flow (DCF) methods, relative valuation (multiples), real options, and specialized approaches for startups, private firms, and financial institutions. The course emphasizes the interplay between narrative and numbers, encouraging students to frame valuation as both a quantitative model and a qualitative story about a company?s future. Throughout the semester, each student will select a company and build a full valuation across multiple methods, culminating in a professional-quality report and presentation. Weekly modules integrate real-world data, current events, and mini-cases, ensuring that students not only master the mechanics of valuation but also develop the judgment to apply valuation techniques responsibly in practice.

Basic concepts, principles, and practices involved in financial budgeting, planning for the cost of capital, and managing financial aspects of organizational sustainability and growth. Both theory and techniques applicable to financial problem solving.