This course provides basic economic concepts and theories. It discusses both decision making of individual agents' behavior (microeconomics) and aggregate level economic issues (macroeconomics). The first part of the course covers principles of economics, how to think as an economist, supply-demand-market mechanism, and elasticity. Then, the second part of the course discusses consumers' and producers' behaviors as well as externalities and public goods. The third part of the course covers various types of market. The last part of this course discusses macroeconomics issues including national income, production, growth, saving, investments and unemployment. Fundamentals of monetary system, aggregate demand and aggregate supply are also covered.

This course examines the determination of the macroeconomic variables such as national income, unemployment, inflation, investment and interest rates. After a brief introduction to macroeconomic data, the course is divided into three sections. The first studies the long-run behavior of aggregate measures of the economy. The second section focuses on the determinants of economic growth. In the third section, a model is developed to characterize short-run economic fluctuations. Throughout the course, we consider macroeconomic policies and particular economic issues of current interest.

This course introduces students to some of the fundamental ideas and tools of standard microeconomic theory and their applications to various business and policy issues. The topics include: demand and supply, consumer behavior, theory of the firm, markets and welfare, general equilibrium, strategic behavior, information economics, and market failures. Upon completion, students should be able to apply the concepts and models of microeconomics to real world problems.

This course is an undergraduate major course which is highly recommended for students pursuing a specialization in IT Business, in particular to develop a strong background and understanding of Digital Banking and FinTech. The course starts with Digital Banking and covers all important aspects of it, including cars, ATMs, mobile and internet banking, branchless banking, POS terminals, payment systems, etc. The course continues with FinTech and this part starts with how the data is giving rise to a new Economy. It covers the roles of AI and Deep Learning in FinTech. It also covers CRM in FinTech, and Blockchain technologies. I shall also present my experiences as the IT Department Manager of a Japanese Company (Has-Nihon Trading Co. Ltd.) where I developed smart business application systems and payment mechanisms for international trade.

The course provides a review of e-business and payment systems. The technology, market models and correspondent strategies of e-business will be discussed individually. In frame of payment systems students will study such topics as banking systems, credit cards, digital payment, security and others.　

This course provides the accounting fundamentals governing preparation of financial statements. It discusses the accrual accounting concepts, transactions analysis and the recording process. The first part of specific topics includes cash, receivables, inventories and long-term assets. The second part covers liabilities and equities. The statement of cash flow and financial statement analysis topics are also covered in the third part. Overall, the whole accounting cycle is discussed so that students will acquire knowledge of the preparation, proper reporting and analysis of financial statements.

This course provides students the fundamentals principles of corporate finance. Students will learn major financial issues commonly faced by corporate decision-makers. The first part of the course will discuss the financial statements fundamentals, time value of money, valuation and capital budgeting decision. The second part of the course will cover the capital market, risk and return analysis, theories of capital structure and dividend policy as well as the short term financial management implementation.

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This course covers strategies for empirical research in a data rich environment. That is, we discuss the analysis of high dimensional data sets. Specifically, the course provides a working introduction to big data, both large n and large p, a new generation of prediction methods (a.k.a. machine learning), as well as the use of these methods for causal inference (causal machine learning). We go through examples of the initial off the shelf applications of machine learning to economics and finance. We also present highlights and empirical studies from the emerging econometric literature combining machine learning and causal inference. Mastery of techniques taught in a class demonstrated through the completion of a capstone project. Students will finish the course equipped with a familiarity with the (causal) machine learning techniques, facility with data handling, and programming.

This is an undergraduate course in Money and Banking that aims to provide a framework for understanding how financial institutions and markets work. This is an upper level course. The aim of the course is to provide an overview of the international financial system, discuss central banking and monetary policies, and how the stock markets, the bond markets and the mortgage markets operate. I will follow the topics in the main textbook by Frederic S. Mishkin. The main objective of the course is to provide a fresh perspective to the contemporary issues in financial policies. The students are expected to gain a deeper understanding of how the financial markets work through discussions of case studies in the class lectures.

This course is a first course in applied statistics. It will familiarize you with the basics of statistical thinking, language, and techniques, thus providing you with the needed skills to address questions that have real life consequences and effects. By the end of the course, you will able to organize and summarize empirical data. This course will also teach you how to compute probabilities, making you skillful in the uses of theoretical probability distributions.

This course begins with the development of elementary functions, including their properties and applications. Then, we will cover finite mathematics, which includes mathematics of finance, linear algebra (matrices, linear systems, and linear programming), probability (starting with foundation for probability with a treatment of logic, sets, and counting techniques), application of linear algebra and probability.