MACROECONOMICS ANALYSIS I

• Department: Economics
• TR 2:40 p.m.-3:55 p.m.
• Instructor: Ronald Miller
  CULPA: 4 Info
• 3 points

QUANT MTHDS IN INVESTMENT MGMT

Prerequisites: Knowledge of statistics basics and programming skills in any programming language. 
Surveys the field of quantitative investment strategies from a "buy side" perspective, through the eyes of portfolio managers, analysts and investors. Financial modeling there often involves avoiding complexity in favor of simplicity and practical compromise. All necessary material scattered in finance, computer science and statistics is combined into a project-based curriculum, which give students hands-on experience to solve real world problems in portfolio management. Students will work with market and historical data to develop and test trading and risk management strategies. Programming projects are required to complete this course.

• Department: Mathematics
• T 7:40 p.m.-10 p.m.
• Instructor: Alexander Greyserman
  Info
• 3 points

SOC-HIST FOUND OF AMER SPORT

SOC-HIST FND OF AMER SPRT

• Department: School of Professional Studies
• M 6:10 p.m.-8 p.m.
• R 6:10 p.m.-8 p.m.
• M 4:10 p.m.-6 p.m.
• Instructor: Ramon Katz
  Info
• Instructor: Michael Dittelman
  Info
• Instructor: Christopher Lencheski
  Info
• 3 points

TIME SERIES ANALYSIS

Prerequisites: STAT GR5205
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.

• Department: Statistics
• MW 7:40 p.m.-8:55 p.m.
• Instructor: Dan Wang
  CULPA: 3 h-index: 13 Info
• 3 points

BAYESIAN STATISTICS

Prerequisites: STAT GR5205
Bayesian vs frequentist, prior and posterior distributions, conjugate priors, informative and non-informative prior subjective and objective bayes, oneand two sample problems, models for normal data, models for binary data, multivariate normal shrinkage, bayesian linear models, bayesian computation (start early), MCMC algorithms, the Gibbs sampler, hierarchical models, empirical bayes, hypothesis testing, bayes factors, model selection, software: R and WinBUGS

• Department: Statistics
• MW 2:40 p.m.-3:55 p.m.
• Instructor: Ronald Neath
  CULPA: 13 Info
• 3 points

DELIVERING THE STRAT MESSAGE

DELIV THE STRAT MESSAGE

• Department: School of Professional Studies
• R 6:10 p.m.-8 p.m.
• Instructor: Liza Gross
  Info
• 3 points

DELIVERING THE STRAT MESSAGE

• Department: School of Professional Studies
• R 6:10 p.m.-8 p.m.
• Instructor: Liza Gross
  Info
• 1.5 points

DIRECTING ACTORS I

• Department: Film
• R 10 a.m.-1 p.m.
• Instructor: Erica Fae
  Info
• Instructor: Jodie Markell
  Wikipedia Info
• Instructor: John Rubin
  Info
• Instructor: W. Peter Miner
  Info
• Instructor: Adrienne Weiss
  Info
• Instructor: Mikael Sodersten
  Info
• 3 points

INNOVATIONS IN PHILANTHROPY

INNOV IN PHILANTHROPY

• Department: School of Professional Studies
• W 6:10 p.m.-8 p.m.
• Instructor: Richard T Feiner
  Info
• 3 points

THE EARTH'S CLIMATE SYSTEM

• Department: School of Professional Studies
• T 4:10 p.m.-6 p.m.
• Instructor: Benjamin I Cook
  CULPA: 3 h-index: 56 Info
• 3 points

SAMPLE SURVEYS

Prerequisites: STAT GR5204
Introductory course on the design and analysis of sample surveys. How sample surveys are conducted, why the designs are used, how to analyze survey results, and how to derive from first principles the standard results and their generalizations. Examples from public health, social work, opinion polling, and other topics of interest.

• Department: Statistics
• TR 6:10 p.m.-7:25 p.m.
• Instructor: Ronald Neath
  CULPA: 13 Info
• 3 points

THE POWER OF OPINION

• Department: School of Professional Studies
• Instructor: Jane Praeger
  Info
• 3 points

MAJOR & LEADERSHIP GIVING

• Department: School of Professional Studies
• S 10 a.m.-11:30 a.m.
• Instructor: Robert E Wahlers
  Info
• 3 points

ADVANCED MACHINE LEARNING

Prerequisites: STAT GR5241
This course covers some advanced topics in machine learning and has an emphasis on applications to real world data.  A major part of this course is a course project which consists of an in-class presentation and a written project report.

• Department: Statistics
• MW 4:10 p.m.-5:25 p.m.
• TR 4:10 p.m.-5:25 p.m.
• 3 points

APPLIED DATA SCIENCE

Prerequisites: STAT GR5206 or the equivalent.
This course will incorporate knowledge and skills covered in a statistical curriculum with topics and projects in data science. Programming will covered using existing tools in R. Computing best practices will be taught using test-driven development, version control, and collaboration. Students finish the class with a portfolio on GitHub, and deeper understanding of several core statistical/machine-learning algorithms. Bi-weekly project cycles throughout the semester provide students extensive hands-on experience with various data-driven applications.

• Department: Statistics
• W 6:10 p.m.-8:55 p.m.
• Instructor: Ying Liu
  CULPA: 2 h-index: 12 Info
• 3 points

BUSINESS OF ISSUES

• Department: School of Professional Studies
• Instructor: Hayley Berlent
  Info
• 3 points

EXTERNAL STAKEHOLDER REQUIREMENTS

• Department: School of Professional Studies
• T 6:10 p.m.-8 p.m.
• M 8:10 p.m.-10 p.m.
• Instructor: Prakash Vanguri
  Info
• Instructor: Neil Strauss
  Wikipedia Info
• 3 points

FUNDAMENTALS OF EDITING

• Department: Film
• 1.5 points

FUNDAMENTALS OF EDITING

• Department: Film
• 1.5 points

FUNDAMENTALS OF EDITING

• Department: Film
• 1.5 points

FUNDAMENTALS OF EDITING

• Department: Film
• 1.5 points

VALUE OF BRAND:MAKNG-BUSI CASE

• Department: School of Professional Studies
• Instructor: Tasha Space
  Info
• 3 points

PROG FOR QUANT & COMP FINANCE

This course covers features of the C++ programming language which are essential in quantitative/computational finance and its applications. We start by covering basic C++ programming features and then move to some more advance features. We utilize these features for financial engineering and quantitative finance applications primarily for pricing of financial derivatives and computational finance. Those applications include transform techniques, Monte Carlo simulation, calibration and parameter estimation techniques.

• Department: Mathematics
• R 8:10 p.m.-10 p.m.
• Instructor: Keith Lewis
  Info
• 3 points

FOUNDATIONS: UNIQUE ROLES, RESP & CHLNGS

UNIQUE ROLES, RESP, & CHALLNGS

• Department: School of Professional Studies
• F 6:10 p.m.-8 p.m.
• Instructor: John Tyler
  h-index: 3 Info
• 3 points

STATISTICAL METHODS IN FINANCE

Prerequisites: STAT GR5204 or the equivalent. STAT GR5205 is recommended.
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.

• Department: Statistics
• F 10:10 a.m.-12:55 p.m.
• Instructor: Hammou Elbarmi
  CULPA: 1 Info
• 3 points

STAT INF/TIME-SERIES MODELLING

Prerequisites: STAT GR5205 or the equivalent.
Available to SSP, SMP  Modeling and inference for random processes, from natural sciences to finance and economics. ARMA, ARCH, GARCH and nonlinear models, parameter estimation, prediction and filtering.

• Department: Statistics
• TR 6:10 p.m.-7:25 p.m.
• S 10:10 a.m.-12:55 p.m.
• Instructor: Pawel Polak
  Info
• Instructor: Irene Hueter
  CULPA: 9 Info
• 3 points

STOCHASTC PROCSSES-APPLICTNS I

Prerequisites: STAT GR5203 or the equivalent.
Basics of continuous-time stochastic processes. Wiener processes. Stochastic integrals. Ito's formula, stochastic calculus. Stochastic exponentials and Girsanov's theorem. Gaussian processes. Stochastic differential equations. Additional topics as time permits.

• Department: Statistics
• MW 6:10 p.m.-7:25 p.m.
• MW 4:10 p.m.-5:25 p.m.
• Instructor: Yuchong Zhang
  Info
• Instructor: Lars T Nielsen
  h-index: 17 Info
• 3 points

STRATEGIC VISUAL COMMUNICATION

• Department: School of Professional Studies
• W 6:10 p.m.-8 p.m.
• Instructor: William Schroeder
  Info
• 3 points

STOCHASTIC METHODS IN FINANCE

Prerequisites: STAT GR5264
Available to SSP, SMP. Mathematical theory and probabilistic tools for modeling and analyzing security markets are developed. Pricing options in complete and incomplete markets, equivalent martingale measures, utility maximization, term structure of interest rates.

• Department: Statistics
• MW 7:40 p.m.-8:55 p.m.
• Instructor: Ioannis Karatzas
  CULPA: 7 h-index: 58 Info
• 3 points

STOCHASTIC CONTROL & APPL-FINC

n/a

• Department: Statistics
• TR 10:10 a.m.-11:25 a.m.
• Instructor: Marcel F Nutz
  CULPA: 9 Info
• 3 points

GLOBAL COMMUNICATION FOR PROFESSIONALS

GLOBAL COMM FOR PROFESSIONALS

• Department: School of Professional Studies
• Instructor: Kristine Billmyer
  Info
• 3 points

CAPITAL MARKETS & INVESTMENTS

Risk/return tradeoff, diversification and their role in the modern portfolio theory, their consequences for asset allocation, portfilio optimization.  Capitol Asset Pricing Model, Modern Portfolio Theory, Factor Models, Equities Valuation, definition and treatment of futures, options and fixed income securities will be covered.

• Department: Mathematics
• F 5 p.m.-7:20 p.m.
• Instructor: Alexei Chekhlov
  CULPA: 3 h-index: 10 Info
• 3 points

THEORY OF INTEREST

• Department: School of Professional Studies
• T 6:10 p.m.-8:55 p.m.
• 3 points

NARRATIVES-DEATH,LIVING,CARING

NARRATIVES, DEATH, LIVING & CA

• Department: School of Professional Studies
• T 6:10 p.m.-9 p.m.
• Instructor: Marsha Hurst
  Info
• 4 points

ROLE & UNIQUE NATURE OF NONPROFIT SECTOR

ROLE & UNIQUE NTR OF NONPRFT

• Department: School of Professional Studies
• S 9 a.m.-noon
• Instructor: Henry L Berman
  Info
• 3 points

ADVANCED DATA ANALYSIS

Prerequisites: W4315 and either another statistics course numbered above the 4200 or permission of instructor.
Required for the major in statistics. Data analysis using a computer statistical package and selected exploratory data analysis subroutines. Topics include editing of data for errors, exploratory and standard techniques for one-way analysis of variance, linear regression, and two-way analysis of variance. Material is presented in case-study format.

• Department: Statistics
• F 6:10 p.m.-8:55 p.m.
• Instructor: Demissie Alemayehu
  h-index: 14 Info
• 3 points

UNPAID INTERNSHIP

Prerequisites: the M.A. program adviser's permission.
For unpaid internships only. Students seeking academic credit for unpaid internships should enroll no later than the second week of the semester. Students must confer with the MA Program Advisor at the time of enrollment to determine the requirements for successfull completion. The Department does not assist students to obtain unpaid internships.

• Department: Statistics
• Instructor: Demissie Alemayehu
  h-index: 14 Info
• 1 points

TOPICS IN MODERN STATISTICS

STATISTICAL GRAPHICS

Topics in Modern Statistics will provide graduate students with an opportunity to study a specialized area of statistics in more depth and to meet the educational needs of a rapidly growing field. Recent and future offerings are Fall 2017 Statistical Graphics, Spring 2018 (1) Applied Machine Learning for Financial Modeling and Forecasting, Spring 2018 (2) Applied Machine Learning for Image Analysis.

• Department: Statistics
• TR 5:40 p.m.-6:55 p.m.
• Instructor: Joyce T Robbins
  CULPA: 5 Info
• 3 points

RESEARCH DESIGN

• Department: School of Professional Studies
• R 6:10 p.m.-8 p.m.
• 3 points

RESEARCH DESIGN

• Department: School of Professional Studies
• R 6:10 p.m.-8 p.m.
• T 6:30 p.m.-8 p.m.
• T 8:30 p.m.-10 p.m.
• W 8:30 p.m.-10 p.m.
• Instructor: Siddhartha Dalal
  Info
• Instructor: Zachary Kornhauser
  Info
• Instructor: Natasa Rajicic
  Info
• Instructor: Aaron Cano
  Info
• 3 points

STRATEGIC COMM FOR RISK PROFESSIONALS

STRAT COMM FOR RISK PROF

• Department: School of Professional Studies
• F 2:10 p.m.-4 p.m.
• W 8:10 p.m.-10 p.m.
• W 6:10 p.m.-8 p.m.
• R 6:10 p.m.-8 p.m.
• M 8:10 p.m.-10 p.m.
• Instructor: Don Waisanen
  Info
• Instructor: Gino Perrotte
  Info
• Instructor: Kate Sweeney
  Info
• Instructor: Shannon M Daniels
  Info
• Instructor: Joseph D Ross
  Info
• 3 points

Corporate Finance

• Department: Finance
• 3 points

Corporate Finance

• Department: Finance
• 3 points

Corporate Finance

• Department: Finance
• 3 points

Corporate Finance

• Department: Finance
• 3 points

HEDGE FUNDS STRATEGIES & RISK

The hedge fund industry has continued to grow after the financial crisis, and hedge funds are increasingly important as an investable asset class for institutional investors as well as wealthy individuals. This course will cover hedge funds from the point of view of portfolio managers and investors. We will analyze a number of hedge fund trading strategies, including fixed income arbitrage, global macro, and various equities strategies, with a strong focus on quantitative strategies. We distinguish hedge fund managers from other asset managers, and discuss issues such as fees and incentives, liquidity, performance evaluation, and risk management. We also discuss career development in the hedge fund context.

• Department: Mathematics
• T 8:10 p.m.-10 p.m.
• Instructor: Eric Yeh
  Info
• 3 points

QUALITATIVE METHODS & RESEARCH

• Department: School of Professional Studies
• R 12:10 p.m.-3 p.m.
• Instructor: Edgar Rivera Colon
  Info
• 4 points

SCULPTURE I

• Department: Visual Arts
• F 10 a.m.-4 p.m.
• T 10 a.m.-4 p.m.
• Instructor: Jon Kessler
  CULPA: 5 Wikipedia Info
• Instructor: Sanford Biggers
  CULPA: 1 Wikipedia Info
• 3 points

POETRY WORKSHOP

• Department: Writing
• W 12:35 p.m.-3:35 p.m.
• T 12:05 p.m.-3:05 p.m.
• 6 points

PRECLINICAL COMPREHENSIVE CARE I

PRECLIN COMPREHENSIVE CARE I

• Department: Dental and Oral Surgery
• Instructor: Roseanna Graham
  h-index: 4 Info
• 0 points

MANAGING INFORMATION & KNOWLEDGE

In this course students learn the principles of management as they relate to enterprise-wide information and knowledge services. Attention is given to the philosophy and history of information and knowledge services, specifically as this background affects students’ future performance as managers and leaders in the workplace. The focus is on management and leadership skills, knowledge sharing, and the role of knowledge strategy in strengthening the corporate knowledge culture.

• Department: School of Professional Studies
• T 6:10 p.m.-8 p.m.
• Instructor: Guy St. Clair
  Wikipedia Info
• 3 points

MANAGING INFORMATION & KNOWLEDGE

MANAGING INFO & KNWLDGE - CEU

In this course students learn the principles of management as they relate to enterprise-wide information and knowledge services. Attention is given to the philosophy and history of information and knowledge services, specifically as this background affects students’ future performance as managers and leaders in the workplace. The focus is on management and leadership skills, knowledge sharing, and the role of knowledge strategy in strengthening the corporate knowledge culture.

• Department: School of Professional Studies
• T 6:10 p.m.-8 p.m.
• Instructor: Guy St. Clair
  Wikipedia Info
• 1.5 points

INTL ENVIRONMENTAL LAW

• Department: School of Professional Studies
• W 6:10 p.m.-8 p.m.
• Instructor: Richard Horsch
  CULPA: 2 Info
• 3 points

Pre-Clinical Comprehensive Care II

• Department: Dental and Oral Surgery
• Instructor: Roseanna Graham
  h-index: 4 Info
• 0 points

SCULPTURE III

• Department: Visual Arts
• M 10 a.m.-4 p.m.
• Instructor: Rirkrit Tiravanija
  Wikipedia Info
• 3 points

ENTERPRISE WIDE APPL/PROJ MGMT

• Department: School of Professional Studies
• T 7 p.m.-8:30 p.m.
• 3 points

SCIENCE FOR BIOETHICISTS

SCI FOR BIOETHICISTS (ONLINE)

• Department: School of Professional Studies
• W 4:30 p.m.-6 p.m.
• 3 points

SCIENCE FOR BIOETHICISTS

SCI FOR BIOETHICISTS (ONLINE)

• Department: School of Professional Studies
• W 4:30 p.m.-6 p.m.
• 0 points

PHILOSOPHY OF BIOETHICS

• Department: School of Professional Studies
• R 12:10 p.m.-2:40 p.m.
• Instructor: Arthur Kuflik
  Info
• 3 points

PHILOSOPHY OF BIOETHICS

PHIL OF BIOETHICS (ONLINE)

• Department: School of Professional Studies
• W 7:30 p.m.-9:30 p.m.
• Instructor: Arthur Kuflik
  Info
• 0 points

PHILOSOPHY OF BIOETHICS

PHIL OF BIOETHICS (ONLINE)

• Department: School of Professional Studies
• W 7:30 p.m.-9:30 p.m.
• M 7 p.m.-9 p.m.
• Instructor: Arthur Kuflik
  Info
• 3 points

PHILOSOPHY OF BIOETHICS

PHIL OF BIOETHICS (ONLINE)

• Department: School of Professional Studies
• M 7 p.m.-9 p.m.
• Instructor: Arthur Kuflik
  Info
• 0 points

STRATEGIC RISK MANAGEMENT

STRATEGIC RISK MGMT

• Department: School of Professional Studies
• T 6:10 p.m.-8 p.m.
• W 6:10 p.m.-8 p.m.
• R 8:10 p.m.-10 p.m.
• Instructor: Cecil R House
  Info
• Instructor: H.S. Bob Kostakopoulos
  Info
• Instructor: Frank Noto
  Info
• 3 points

FINANCIAL RISK MGMT & REGULATION

FINANCIAL RISK MGMT & REGULATN

Prerequisites: student expected to be mathematically mature and familiar with probability and statistics, arbitrage pricing theory, and stochastic processes.
The course will introduce the notions of financial risk management, review the structure of the markets and the contracts traded, introduce risk measures such as VaR, PFE and EE, overview regulation of financial markets, and study a number of risk management failures. After successfully completing the course, the student will understand the basics of computing parametric VaR, historical VaR, Monte Carlo VaR, cedit exposures and CVA and the issues and computations associated with managing market risk and credit risk. The student will be familiar with the different categories of financial risk, current regulatory practices, and the events of financial crises, especially the most recent one.

• Department: Mathematics
• R 8:10 p.m.-11 p.m.
• Instructor: Harvey Stein
  h-index: None Info
• 3 points

NONPROFIT FINANCIAL MGMT

• Department: School of Professional Studies
• W 6:10 p.m.-8 p.m.
• T 6:30 p.m.-8 p.m.
• 3 points

PORTFOLIO MANAGEMENT

• Department: School of Professional Studies
• W 4:10 p.m.-6 p.m.
• Instructor: Gregory J Muth
  Info
• 3 points

OPERATIONAL RISK MANAGEMENT

OPERATIONAL RISK MGMT

• Department: School of Professional Studies
• R 6:10 p.m.-8 p.m.
• M 6:10 p.m.-8 p.m.
• Instructor: Prasad Kodali
  Info
• 3 points

FIXED INCOME PORTFOLIO MGMT

Prerequisites: comfortable with algebra, calculus, probability, statistics, and stochastic calculus.
The course covers the fundamentals of fixed income portfolio management. Its goal is to help the students develop concepts and tools for valuation and hedging of fixed income securities within a fixed set of parameters. There will be an emphasis on understanding how an investment professional manages a portfolio given a budget and a set of limits.

• Department: Mathematics
• F 6:10 p.m.-8 p.m.
• Instructor: Rosanna Pezzo
  Info
• 3 points

Behavioural Finance

• Department: Finance
• 3 points

Behavioural Finance

• Department: Finance
• 3 points

CAPSTONE PROJECT SEMINAR

CAPSTONE PROJECT (PART 2)

• Department: School of Professional Studies
• Instructor: Madelyn Blair
  Info
• 4 points

NONPROFIT POLICY & ADVOCACY

NONPFT POLICY & ADVOCACY

• Department: School of Professional Studies
• R 4:10 p.m.-8 p.m.
• 3 points

FUNDAMENTALS OF SPORTS ANALYTICS

FUND OF SPORTS ANALYTICS

• Department: School of Professional Studies
• M 8:30 p.m.-10:20 p.m.
• M 6:10 p.m.-8 p.m.
• Instructor: Benjamin Alamar
  Info
• 3 points

FINANCIAL RISK MANAGEMENT

FINANCIAL RISK MGMT

• Department: School of Professional Studies
• W 8:10 p.m.-10 p.m.
• Instructor: David J Romoff
  Info
• 3 points