The econometrics and statistics MBA concentration at Chicago Booth teaches you to view, organize, and interpret vast amounts of data in order to be better informed and to make better business decisions.
Steeped in Booth’s rich tradition of evidence-based thinking, our econometrics and statistics curriculum gives you the quantitative tools you need to test and refine your ideas.
You’ll learn advanced regression tools, study financial applications such as volatility modeling and value-at-risk calculations, and leverage big data to learn about behavior.
You’ll also examine the real-world application of finance theory to answer key questions: What is the default rate on a security? How should you update your portfolio when volatility or correlations are changing over time? How do you measure and forecast transaction costs? Our classes emphasize the use of statistics as an invaluable tool in understanding the real world and making better decisions.
To complete a concentration in econometrics and statistics, you’ll choose three courses in the discipline. Here are just a few of the options.
This course covers data mining: the analysis, exploration, and simplification of large high-dimensional datasets. You will learn how to model and interpret complicated “Big Data” and become adept at building powerful models for prediction and classification.
Techniques covered include an advanced overview of linear and logistic regression, model choice and false discovery rates, multinomial and binary regression, classification, decision trees, factor models, clustering, the bootstrap and cross-validation.
This course covers statistical concepts needed for modern business applications. The goal is to learn to use statistical tools, along with problem-solving and communication skills, to analyze data and make business decisions. These tools also form the foundation for Chicago Booth elective courses, particularly in marketing, economics, and finance.
Regression is a powerful and widely used data analysis technique used to analyze a variety of complex, real-world problems. Topics covered include: 1) review of simple linear regression; 2) multiple regression (understanding the model, model specification, and casual inference; interpreting the coefficients, R-squared, t- and F-tests, model diagnostics, model building, and model selection); 3) time series (autocorrelation functions, auto regression, prediction); and 4) logistic regression.
The topics covered are of real-world, practical interest and are closely linked to material covered in other advanced finance courses. Topics covered include ARMA models, volatility models (GARCH), factor models, issues in the analysis of panel data, and models for transactions data and the analysis of transactions cost.
In this course, you will learn about state-of-the-art machine learning techniques and how to apply them in business related problems. Techniques will be introduced in the context of business applications and the emphasis will be put on how machine learning can be used to create value and provide insights from data.
In order to compete in the arena of marketing consulting, you need to have the ability to identify upcoming trends and new problems in the marketing area and to be able to provide original, sound, fast, and applicable solutions to these problems. Unlike marketing research, marketing consulting is a problem-solving endeavor that requires a great deal of specificity and is fueled by experience. This course is meant to give future consultants and entrepreneurs important tools and ways of thinking that are relevant for insightful consulting and are useful in the practice of marketing consulting.
To see more econometrics and statistics courses, visit our course catalog and search by concentration area for your program of interest.
Our econometrics and statistics faculty include award-winning authors and National Science Foundation grant recipients. Faculty conduct research in high-dimensional statistical methods, big data analysis, credit ratings, process control, and other areas.
Our econometrics and statistics faculty are conducting research that’s making significant contributions to the field. Chicago Booth Review frequently writes about their work.
Research by Chicago Booth’s Dacheng Xiu and others suggests that today’s computers can predict asset returns with an unprecedented accuracy.
Machine Learning Can Help Money Managers Time Markets, Build Portfolios, and Manage Risk
Chicago Booth’s Dacheng Xiu and coauthors investigate whether many of the investable factors identified in the finance literature are redundant.
The 300 Secrets* to High Stock Returns (Caveat*: Most of Them Probably Won't Work)
Research by Chicago Booth’s Max Farrell, Tengyuan Liang, and Sanjog Misra suggests that deep learning can have excellent performance when properly used.
How (In)accurate Is Machine Learning?
Faculty members at Booth are connected to some of the most important leaders across various industries. Our faculty regularly invite these leading practitioners and influencers to speak to students in the Booth classroom, providing you with greater access to learn, network, and grow.
Learn from Industry ExpertsDevelop your skills and build a dynamic global network. As an MBA student in econometrics and statistics at Booth, you’ll have many opportunities to get involved in research centers, student groups, competitions, and other activities.
Test your theories and gain valuable experience in some of the world’s most prestigious competitions on campus and around the globe.
Participate in a Competition
Get involved, develop new skills, and meet new people in a wide array of student-led groups.
Join a Full-Time MBA Group
Pursue your interests and expand your network by joining a student-led group for Part-Time MBA students.
Explore Part-Time MBA Student Groups
