Teaching
The University of Texas at San Antonio
Computer Modeling of Financial Applications FIN3063 (previously FIN4873) - Example syllabus
This course provides the opportunity to develop computer modeling skills and techniques for analyzing financial situations encountered in business, including the analysis of financial statements, forecasting, capital budgeting, and principles of investment analysis of securities. Financial issues involving uncertainty are examined.
Financial Derivatives FIN6213 / FIN3453 - Example Syllabus - Example Lecture
This course presents and analyzes derivatives, such as forwards, futures, and options. These instruments have become extremely popular investment tools over the past several decades, as they allow one to tailor the amount and kind of risk one takes, be it risk associated with changes in interest rates, exchange rates, stock prices, commodity prices, inflation, weather, etc. They are used by institutions as well as investors, sometimes to hedge (reduce) unwanted risks. Other times investors use the same investment to take on additional risk motivated by views regarding future market movements. The course defines the main kind of derivatives, shows how they are used to achieve various hedging and speculating objectives, introduces a framework for pricing derivatives, and studies several applications of derivative-pricing techniques outside derivative markets.
Financial Technology Lab (FIN6323)
Many aspects of finance require an intermediary (middleman) to allow the exchange of assets and information. Financial intermediation has evolved from early systems of banking to our current web of interconnected firms that facilitate payment/transactions, capital fundraising, provide financial advice, and financial management services. Technology is changing the way financial intermediaries deliver all of these services. This course consists of two alternating components. In the first segment, we will lay an informational foundation in five finance content areas: Payments/Currency, Equity Capital Markets, Debt Capital markets, Financial Consumption/Advice, Financial Investments/Advice. We will learn about the current financial systems that serve these areas and the technology that is disrupting current business models. In the second portion of the course, students will learn machine learning techniques which are often the source of technology revolutionizing financial intermediation. Using the information from the content areas and machine learning segment, students will propose and produce a final project demonstrating their mastery of both.
University at Buffalo - SUNY
FinTech Lab (MGF687/MGF620)
Welcome to FinTech Lab at the University at Buffalo! Many aspects of finance require an intermediary (middleman) to allow the exchange of assets and information. Financial intermediation has evolved from early systems of banking to our current system of financial intermediaries, where firms facilitate payment/transactions, capital fundraising, provide advice and financial management services. Technology is changing the way financial intermediaries deliver all of these services. Because of the hybrid nature of this area (Finance and Information Systems), it is increasingly important that finance students understand information system issues/limitations and vice versa. This course is a hybrid elective that will combine students from both subjects to learn about different areas influenced by recent advances in financial technology. By design, we will work in teams of finance and IS students to accomplish our learning objectives.
This course is broken into two segments. In the first segment, we will lay an informational foundation in five different content areas: Payments, Primary Capital Markets (Debt, Equity, Hybrid ICO), and Financial Advice (Investment, Personal Finance). We will learn about the current financial systems that serve these areas and the technology that is disrupting current business models. You will be individually tested over this informational content. However, as a team you will be responsible for pitching a project in each of these areas. The second segment of the course will be our laboratory for each team to implement one of their pitched projects. We will spend 5 weeks designing and implementing a project around one of the seven content areas. Our goal will be to present each project in an external competition or case review for students to receive feedback from broader stakeholders like industry participants.
Security Trading and Market Making (F439) & (F639)
Welcome to Security Trading and Market Making at the University at Buffalo! For simplicity, most finance courses assume that securities trade in an idealized costless, frictionless world. In reality there are many frictions: bid-ask spreads, trade impact on price, brokerage commissions, quantity limitations, time delays, etc. This field of study is known as “market microstructure.” Microstructure has grown rapidly into one of the largest subdisciplines of finance and has had a profound impact on the real world. For example, one research study uncovered evidence of implicit collusion by NASDAQ dealers. This led to a class action lawsuit that was eventually settled when 30 brokerage firms paid a total of $1 billion in damages!
This course is broken into three segments. In the first segment we’ll learn about the trading process and how it works. Students will gain a solid understanding of order types, exchange designs, and the different types of participants in our markets. In the second portion of the course we’ll focus on the basics of algorithmic trading strategies. Students will examine how traders design trading strategies and order types to trade electronically. Students will have the opportunity to demonstrate this learning through an in-class competition. The last segment of the course covers current topics in microstructure. The U.S. markets have undergone tremendous change in the past 10 years and as a result there are numerous policy questions that are open for debate. We will cover topics such as the impact of High Frequency Trading, why the increased usage of Dark Pools, and how behavioral bias made influence trading.
Indiana University
Equity and Fixed Income Investments (F420)
F420 is a rigorous treatment of portfolio valuation and management. We build on the discussion of equity and fixed income securities from F303 and develop an understanding of how finance theory suggests we ought to value portfolios of these assets. Knowing that deviations from these models exist, we include some discussion on the limits to portfolio valuation theory and introduce topics such as behavioral finance and limits to arbitrage. Often in practice, an outside agent manages a portfolio. We will discuss the differences between these different fund managers. Finally, we will spend a few sessions focused on bond portfolios and discuss how securitization has changed the landscape of fixed income investments. From a skill standpoint the course emphasizes communication and analysis. Activities will be designed to build both written and oral communication skills as well as analytical techniques.
Security Trading and Market Making (F335)
Welcome to Security Trading and Market Making at Indiana University! For simplicity, most finance courses assume that securities trade in an idealized costless, frictionless world. In reality there are many frictions: bid-ask spreads, trade impact on price, brokerage commissions, quantity limitations, time delays, etc. This field of study is known as “market microstructure.” Microstructure is an important subdiscipline of finance and has had a profound impact on the real world. For example, one research study uncovered evidence of implicit collusion by NASDAQ dealers. This led to a class action lawsuit that was eventually settled when 30 brokerage firms paid a total of $1 billion in damages!
Statistics for Business Majors (S301)
This course is about statistics, applied to the business world. Specifically, we will focus on certain statistical competencies that help managers make better decisions. We will start from scratch: I expect you to have only the basic understanding of math. Everything else we will learn in this class. As you will see, we will use a lot of business applications, and I am concerned more with your understanding on how statistic works as opposed to memorizing the formulas. This class will be unique in a sense that I will bring a lot of non-statistical material to help you understand the world of decision sciences.