Finance
- ECO 525/FIN 525: Asset PricingIntroduction to asset pricing covering theory in both continuous and discrete time to study dynamic portfolio choice; derivative pricing; the term structure of interest rates; and intertemporal asset-pricing and consumption-based models. Pre-requisites: All required courses in micro, macro and econometrics at the first-year PhD level.
- FIN 501/ORF 514: Asset Pricing I: Pricing Models and DerivativesAn introduction to the modern theory of asset pricing. Topics include: No arbitrage, Arrow-Debreu prices and equivalent martingale measure; security structure and market completeness; mean-variance analysis, Beta-Pricing, CAPM; and introduction to derivative pricing.
- FIN 516: Topics in Finance: FINTECHThis course studies the impact of recent technological innovations in the financial sector. We first study the microeconomic principles of using big data to design credit rating systems, financial platforms, digital tokens, and smart contracts. We then study a range of applications such as peer-to-peer lending, cryptocurrency valuation, crowdsourcing, micro-credit, green contracting and central bank digital tokens. Finally, we study the macroeconomic impact of fintech on the broader economy.
- FIN 521: Fixed Income: Models and ApplicationsA study of models for the term structure of interest rates, bond prices and other contracts such as forwards and futures, swaps and options. The course develops the theory of arbitrage-free pricing of financial assets in continuous time, as well as special models that can be used to price and hedge fixed income securities
- FIN 560: Master's Project IUnder the direction of a Bendheim affiliated faculty member, students carry out a master's project, write a report, and present the results in the form of a poster or an oral presentation in front of an examining committee.
- FIN 567: Institutional Finance,Trading and MarketsFinancial institutions play an increasingly dominant role in modern finance. This course studies the financial system and its protagonists, with a focus on efficiency and stability. It covers important theoretical concepts and recent developments in asset pricing under asymmetric information, market microstructure, and financial intermediation. Topics include market efficiency, liquidity crises, asset price bubbles, herding, risk management, market design and financial regulation. The course examines these concepts theoretically as well as empirically by using financial data.
- FIN 591: Cases in Financial Risk ManagementRisk management systems are a fundamental tool in investment banks and hedge funds. The objective of this quantitative course is to give students a comprehensive view of such a system. The course covers topics related to market, credit and operational risks (time allowing). We learn about risk factors and how they are used to mark assets to market, build portfolio conditional loss distributions and back-test them to learn if our models are adequate. We also study in detail portfolio and derivatives credit risk. Theoretical classes are complemented with hands-on computational homework and a take home computational midterm exam.
- FIN 594: Chinese Financial and Monetary SystemsWith its rapid economic growth in the past three decades, China already has the world's second largest economy. Meanwhile its financial markets are also being quickly liberalized and integrated with the rest of the world. As the current trend continues, there are growing interests to learn and understand the workings of China's financial and monetary systems. This course aims to serve this objective with a particular emphasis on understanding the role provided by the financial system in facilitating China's economic development, in addition to the investment opportunities and risk presented by the system to the outside world.
- ORF 505/FIN 505: Statistical Analysis of Financial DataThe course is divided into three parts of approximately the same lengths. Density estimation (heavy tail distributions) and dependence (correlation and copulas). Regression analysis (linear and robust alternatives, nonlinear, nonparametric,classification.) Machine learning (TensorFlow, neural networks, convolution networks and deep learning). The statistical analyzes, computations and numerical simulations are done in R or Python.
- ORF 531/FIN 531: Computational Finance in C++The intent of this course is to introduce the student to the technical and algorithmic aspects of a wide spectrum of computer applications currently used in the financial industry, and to prepare the student for the development of new applications. The student is introduced to C++, the weekly homework involves writing C++ code, and the final project also involves programming in the same environment.
- ORF 535/FIN 535: Financial Risk and Wealth ManagementThis course covers the basic concepts of measuring, modeling and managing risks within a financial optimization framework. Topics include single and multi-stage financial planning systems. Implementation from several domains within asset management and goal based investing. Machine learning algorithms are introduced and linked to the stochastic planning models. Python and optimization exercises required.