11 courses with the subject FNAN, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
FNAN 600Corporate Finance3
This course builds on the foundational principles of corporate finance, delving into more advanced topics that are essential for understanding the financial decision-making processes within a corporation. Students will explore concepts such as capital budgeting, capital structure, dividend policy, and working capital management. The course also covers the analysis of financial statements, valuation techniques, and the role of financial markets in corporate strategy.
This course focuses on portfolio analysis, construction, and equity valuation using modern financial techniques. Students will explore risk-return trade-offs, apply valuation models, and assess portfolio performance. The course emphasizes the use of financial analytics to construct optimized portfolios and perform company analysis. Prerequisite: FNAN 600.
This course offers an introduction to econometric techniques that are essential for conducting empirical analysis. It aims to equip students with the ability to master key concepts and independently and critically complete empirical projects.
This graduate-level course offers an in-depth study of options, exploring their structure, pricing, and strategic applications in financial markets. The course focuses on key concepts such as option valuation models, volatility, the Greeks, and using options for hedging and speculative purposes. Through theoretical frameworks and real case studies from Bloomberg Terminals, students will gain practical insights into the dynamic role of options in risk management and portfolio optimization. Prerequisites: FNAN 600, FNAN 602, FNAN 604.
This course delves into the use of machine learning techniques in the field of investment management. Students will explore how machine learning models can be applied to financial data to enhance investment strategies, optimize portfolios, and manage risks. The course will cover supervised and unsupervised learning, deep learning, and reinforcement learning, with a focus on their practical applications in asset pricing, algorithmic trading, and risk management. Hands-on projects will allow students to apply machine learning techniques to real-world financial datasets. Prerequisites: FNAN 600, FNAN 602, FNAN 604.
Behavioral Finance examines the ways in which human behavior influences financial decisions, markets, and the broader economy. The course explores how cognitive biases, emotions, and social factors lead to deviations from the predictions of traditional financial theories. Through case studies, discussions, and critical analysis, students will learn how to apply behavioral finance concepts to better understand market dynamics and improve investment decision-making. Prerequisites: FNAN 600, FNAN 602, FNAN 604.
FNAN 630Applied Artificial Intelligence in Finance3
This course introduces students to the practical use of artificial intelligence tools in modern financial decision-making, with an emphasis on application rather than heavy programming. Students learn how AI can be used to analyze financial statements, evaluate firm performance, construct and rebalance investment portfolios, and identify, measure, and manage financial risks using intuitive, no-code or low-code platforms.
This course explores the valuation and pricing of real estate securities, focusing on both theoretical and practical aspects of real estate capital markets to enable students to make informed investment decisions in a dynamic and complex environment. The course covers a range of topics, such as residential and commercial securities, mortgage prepayment and credit risk, debt securities, and regulations. The primary goal is to familiarize students with the structured finance market and the diverse array of assets that are actively securitized. The course will provide an understanding of: The foundational elements of CMBS (Commercial Mortgage-Backed Securities) and RMBS (Residential Mortgage-Backed Securities) structures, including credit enhancement and payment priority, as well as the approach of rating agencies to assess securitizations. Prerequisites: FNAN 600, FNAN 602, FNAN 604.
The capstone project is a mandatory component of the MS in Financial Analytics program, designed to serve as an integrative, comprehensive, and practical application of the knowledge and skills acquired throughout the curriculum. The capstone offers students an opportunity to deeply engage with real-world financial analytics challenges, demonstrating their ability to independently develop, implement, and communicate sophisticated financial analytics solutions. Under the guidance of experienced faculty mentors, students will enhance their proficiency in research methodologies, advanced analytical techniques, data-driven decision-making processes, and professional communication and presentation skills. This experience will prepare them for impactful and successful careers in the rapidly evolving and dynamic field of financial analytics. Prerequisites: FNAN 600, FNAN 602, FNAN 604.
Application of Statistical and Econometric Techniques to Financial Data Analysis: Students will learn to apply various statistical and econometric methods to analyze financial data, focusing on three key areas: Linear Regression Models: Understanding the determinants of stock returns and evaluating their risk using linear regression techniques, Time Series Models: Utilizing historical data to predict future values, such as forecasting a company’s quarterly revenue, Volatility Models: Applying time series methods to forecast the variance or standard deviation of financial variables, with practical applications in financial risk management. Prerequisite: FNAN 604.
This graduate-level course offers a comprehensive exploration of fixed income securities, focusing on their significance in financial markets. The course delves into advanced topics such as risk-return dynamics, sophisticated valuation techniques, credit analysis, and the term structure of interest rates. It is tailored to equip students with the skills necessary for high-level analysis and decision-making in finance, with particular relevance for those preparing for the fixed income segment of the CFA® Level II Exam. Prerequisites: FNAN 600 and FINAN 602.
