Courses

Prerequisites: STAT GU4204 and STAT GU4205 A fast-paced introduction to statistical methods used in quantitative finance. Financial applications and statistical methodologies are intertwined in all lectures. Topics include regression analysis and applications to the Capital Asset Pricing Model and multifactor pricing models, principal components and multivariate analysis, smoothing techniques and estimation of yield curves statistical methods for financial time series, value at risk, term structure models and fixed income research, and estimation and modeling of volatilities. Hands-on experience with financial data.

Prerequisites: At least one semester of calculus. A calculus-based introduction to probability theory. Topics covered include random variables, conditional probability, expectation, independence, Bayes rule, important distributions, joint distributions, moment generating functions, central limit theorem, laws of large numbers and Markovs inequality.

Prerequisites: STAT GR5203 and GR5204 or the equivalent. Theory and practice of regression analysis, Simple and multiple regression, including testing, estimation, and confidence procedures, modeling, regression diagnostics and plots, polynomial regression, colinearity and confounding, model selection, geometry of least squares. Extensive use of the computer to analyse data.

Prerequisites: STAT GU5204 and STAT GU5205 Open to MA students in Statistics only Introduction to programming in the R statistical package: functions, objects, data structures, flow control, input and output, debugging, logical design, and abstraction. Writing code for numerical and graphical statistical analyses. Writing maintainable code and testing, stochastic simulations, paralleizing data analyses, and working with large data sets. Examples from data science will be used for demonstration.

Open to MA students in Statistics only Prerequisites: STAT GU4205 or the equivalent. Least squares smoothing and prediction, linear systems, Fourier analysis, and spectral estimation. Impulse response and transfer function. Fourier series, the fast Fourier transform, autocorrelation function, and spectral density. Univariate Box-Jenkins modeling and forecasting. Emphasis on applications. Examples from the physical sciences, social sciences, and business. Computing is an integral part of the course.

Prerequisites: STAT GR5206 or the equivalent. Open to MA students in Statistics only The course will provide an introduction to Machine Learning and its core models and algorithms. The aim of the course is to provide students of statistics with detailed knowledge of how Machine Learning methods work and how statistical models can be brought to bear in computer systems - not only to analyze large data sets, but to let computers perform tasks that traditional methods of computer science are unable to address. Examples range from speech recognition and text analysis through bioinformatics and medical diagnosis. This course provides a first introduction to the statistical methods and mathematical concepts which make such technologies possible.

Prerequisites: STAT GR5204 or the equivalent. STAT GR5205 is recommended. Open to MA students in Statistics only A fast-paced introduction to statistical methods used in quantitative finance. Financial applications and statistical methodologies are intertwined in all lectures. Topics include regression analysis and applications to the Capital Asset Pricing Model and multifactor pricing models, principal components and multivariate analysis, smoothing techniques and estimation of yield curves statistical methods for financial time series, value at risk, term structure models and fixed income research, and estimation and modeling of volatilities. Hands-on experience with financial data.

This course is about cost-benefit analysis and the economic evaluations of policies and projects. Cost benefit analysis (CBA) consists of a comprehensive set of techniques used to evaluate government programs. It is now routinely applied in such program areas as transportation, water projects, health, training and education, criminal justice, environmental protection, urban policy and even in the international arena such as foreign direct investment. Many of the techniques of CBA can also be applied to private sector decision-making. The objective of CBA is to determine whether the benefits of a particular program, policy or decision outweigh its costs. The techniques used to determine this are sometimes quite simple, but on other, increasingly frequent occasions are highly sophisticated. Sophisticated cost benefit studies are based on a framework that utilizes the basic concepts of economic theory. In addition, statistical and econometric analyses are often needed to estimate program effects from diverse available data. The course has two parts: methodology and practice. The goal is for students to be practically adept to undertake an independent cost-benefit analysis.

The purpose of this course is to provide an overview of trends and best practices in corporate communications relating to sustainability, with a particular focus on global sustainability reporting frameworks and green marketing communications. It is designed for those who hold/will hold positions in organizations with responsibilities for communicating the sustainability goals, challenges and achievements, as well as accurately and honestly communicating the environmental aspects of an organization's products and services. Increasingly, large corporations are creating c-suite roles or dedicated departments to oversee this function. More typically, multiple functions contribute information such as: Corporate Communications, Marketing, Community Affairs, Public Policy, Environmental Health & Safety, R&D, Facilities, Operations and Legal. Benefits of reporting range from building trust with stakeholders, and uncovering risks and opportunities; to contributing to stronger long-term business strategy, and creating new products and services.

In an era of growing environmental and social awareness, supply chains have emerged as a powerful lever for driving
sustainability in operations. Supply chain emissions are, on average, 11.4 times higher than operational emissions (1)
making them a critical focal point for impactful change in operations. This course explores the essential role of supply
chains in achieving sustainable outcomes and equips students with the tools and insights needed to transform
conventional practices into innovative, responsible, and efficient systems. This course is part of a broader curriculum
aimed at cultivating leaders who can integrate sustainability into the heart of business strategy. It is designed for
students from diverse professional and academic backgrounds, no prior experience in operations or supply chain
management is required to excel in this course.

Through this interdisciplinary journey, students will gain a robust foundation in supply chain management, learning
to integrate sustainability principles across operations. The course balances analytical skills with creative problem-
solving, preparing students to address real-world challenges. Upon completing this course, students will gain a
comprehensive skillset to analyze, design, and implement sustainable operations solutions in their future careers.
Students will gain a comprehensive understanding of the strategic role of supply chains in modern economies,
including their critical impact in decarbonization efforts. Students will also learn to apply key analytical tools such as
demand forecasting and risk assessment, while mastering strategies for sourcing, supplier management, and logistics
optimization.

Since the rollback of the Inflation Reduction Act (IRA), federal subsidies targeting energy conservation and renewables have decreased. These legislative changes are hindering progress within the New York City affordable housing sector in meeting climate goals. However, energy opportunities in affordable housing can still be realized with funding provided by government subsidies used in housing, incentives offered by investor-owned utilities, and private capital from mission-driven financial institutions.

This course will assist students in understanding the complexities of mixing private and public funding to bridge the housing gap while achieving climate goals at the same time. Through a structured hierarchy of debt and equity, called a capital stack, students will explore the ways in which expanding energy investments in affordable housing reduce tenant energy burden and improve building performance.

Students will learn fundamental concepts of real estate finance like project feasibility, the sources and use of capital, and the project development process.

 

Fundamentals of visual vocabulary. Students work from observation using still-life objects and the human figure. Emphasizes the relationship of lines and forms to each other and to the picture format. Materials used: vine charcoal, compressed charcoal, pencil, pen, ink, and brushes. Class assignments, discussions, and critiques.