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Econometrics and Statistics at Booth
Econometrics and Statistics at Booth
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Econometrics and Statistics at Booth

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  • 1. Applied Regression Analysis (41100) This course provides a thorough treatment of linear regression, the most powerful and widely used Econometrics and Statistics at Booth statistical tool in modern business analysis. While Business Statistics develops a broad conceptual Chicago Booth is among the world leaders in foundation, Applied Regression focuses on issues that quantitative analysis. From the classroom to the arise in regression analysis with real world data. boardroom and in academic research, faculty, students, and alumni take pride in their ability to use The focus in Applied Regression is on a broad set of data and quantitative skills to solve modern business examples that illustrate practical applications of the problems. The Chicago Booth statistics curriculum linear regression model. Students will learn how to focuses on the concepts underlying quantitative tools, take a practical problem, such as assessing the impact the issues involved in working with real world data, of inventory control on firm profitability, obtain and and the thinking required to put those tools together work with data, and design a regression model to with data to draw meaningful conclusions. provide a quantitative answer. The course also focuses on evaluation of regression models, and the Core Courses different issues involved in assessing how well a model explains outcomes in a given data set versus Chicago Booth students complete at least one statistics how well that model will predict future outcomes. course as a part of their degree requirements. Business Statistics (41000) and Applied Regression By providing a diverse array of examples, Applied Analysis (41100) form the foundation of quantitative Regression also familiarizes students with the ways in training at the Booth. Though designed as a two- which linear regression is employed in different areas course sequence, either course may be used to fulfill of business, including terminology and issues specific the statistics requirement. Most sections of 41000 and to finance, marketing, and economics. The major goal 41100 use Microsoft Excel or Minitab software. of the course is for students to become fluent in the language of regression analysis, which makes for a Business Statistics (41000) seamless transition to Booth elective courses as well as modern business careers. The first course in our statistics sequence, Business Statistics is designed with two broad objectives in Which Course to Take? mind. First, it is a “ground up” statistics class, designed to be accessible to students with no prior First year students are often faced with a choice knowledge of statistics. However, it is also designed between Business Statistics and Applied Regression to give students background in data analysis, Analysis. The two courses are designed as a probability, and statistics sufficient for all but a sequence: Although some topics overlap between handful of upper level elective courses at the Booth. them, the differing approaches complement each other and provide a strong foundation in quantitative To accomplish these goals, the course begins with data analysis. That said, both courses cover linear analysis and probability, building toward statistical regression, and either should provide sufficient inference and eventually culminating with linear background for most Booth electives. regression in the final weeks of the quarter. Much of the material is similar to a college-level statistics class, In almost all cases, students are highly encouraged to but the pace is considerably faster and the emphasis is start in Business Statistics. Although the two courses on understanding over memorization of formulas. differ more in their approaches than in their level, Applied Regression assumes proficiency with standard Business Statistics is concept-based rather than case- statistical tools, including hypothesis tests and based. It is both impossible and counterproductive to confidence intervals, and an understanding of the introduce (or to ask students to memorize) all of the concepts underlying those tools. While there is no wide variety of techniques and terminology used in formal criterion, students who can give a good answer different fields of business to solve many different and explanation to the question, “In a large sample of problems. Instead, we focus on unifying these i.i.d. observations, what is the sampling distribution of techniques around a set of core quantitative tools and the sample mean?” will usually feel comfortable in concepts. Students leave Business Statistics with an Applied Regression. understanding of the key elements in statistical analysis, providing a robust conceptual foundation that MBA program requirements also permit one of the enables students to understand, apply, and interpret the elective courses described below to be taken in place results of statistical techniques in any business of Business Statistics or Replied Regression. This is environment. strongly discouraged, with the exception of students who have previously completed graduate level courses in statistics, empirical economics, or econometrics.
  • 2. Elective Courses Financial Econometrics (41303, Professor Jeffrey Russell) Chicago Booth currently offers three elective courses in econometrics and statistics: Analysis of Financial This course is about the intersection of finance theory Time Series (41202), Financial Econometrics (41203), and statistical techniques. Finance theory produces and Statistical Insight into Marketing, Consulting and models that must be verified or falsified with data Entrepreneurship (41301). Students may obtain a from real world markets, which often requires concentration in Econometrics and Statistics by advanced statistical tools. Conversely, statistical completing any three statistics courses, including analysis of financial data can lead to empirical facts 41000, 41100, and the electives described below. that are inconsistent with existing theories, begging for These elective courses focus on applications of new models or investment strategies. statistical analysis to finance, marketing, and empirical economics, drawing on our faculty’s research at the The course begins with an overview of models of frontiers of these fields. time-varying expected returns and time-varying risk. These models are then used together to describe the Each of the elective courses assumes familiarity with tradeoff between risk and return in a cross section of statistics at the level of 41000 or 41100. Both 41202 assets, which is central to modern portfolio analysis. and 41203 use statistical software beyond Excel, such The latter part of the course covers long run as R, S-Plus, and Matlab. Prior experience with these relationships between asset prices, including present or similar software is helpful but is not assumed. value models and bid-ask spreads, and models for high Currently 41301 is offered in the summer quarter, but frequency (intraday) financial data and how to use may be offered during the regular academic year in the those models to evaluate trade execution strategies. future. The course also introduces the statistical tools, including maximum likelihood, robust inference, and Analysis of Financial Time Series (41202, cointegration analysis, that are required to understand Professor Ruey Tsay) and apply these models using financial market data. Financial Time Series introduces students to modern Students who complete Financial Econometrics will methods and applications involving time series data, have a core set of tools essential to modern finance including asset prices, market returns, and practitioners as well as an understanding of how those macroeconomic indicators, in the area of finance. The tools relate to modern finance theory. The course also course focuses on statistical techniques for offers a brief introduction to Matlab, a computing forecasting, volatility modeling, and risk management, package used in many Booth finance courses. This making it ideal for students with interest in course is thus an ideal lead-in to upper level empirical macroeconomics and all areas of quantitative finance, finance courses. including fixed income and financial engineering. Statistical Insight into Marketing, Consulting, and The course begins by familiarizing students with Entrepreneurship (41301, Professor Zvi Gilula) common characteristics and stylized facts about financial data, such as serial correlation, skewness, Marketing consulting is one of the fastest growing and and “fat tails” in asset returns, and how these features competitive areas in modern business. This course is differ across asset classes (e.g., stocks versus meant to give future consultants and entrepreneurs currencies). Students then learn to estimate and important tools and ways of thinking that are relevant evaluate dynamic models, both to explain observed to insightful consulting and understanding efficient phenomena in financial markets, such the relationship business practice. between yields on bonds of differing maturities and day-of-the-week or month effects in equity portfolio This course addresses a variety of practical consulting returns, and to forecast outcomes from quarterly GDP problems and their solutions, including analysis of growth to daily stock returns. customer attrition, optimal inventory management, and the prediction of purchasing behavior using The latter part of the course covers risk management, information such as media exposure, lifestyle, and including estimating and applying ARCH and political orientation. The course also considers how to GARCH models for time-varying volatility, using measure brand loyalty and the image of a company, as continuous time models to explain options prices, and perceived by the public and in particular its customers, reliably calculating Value at Risk based on historical from observed market data. data. More advanced topics, including factor models and multivariate time series, are covered if time Statistical tools, for example logistic regression, are permits. introduced as required. However, the course is taught in a way that emphasizes interpretation of results rather than computations or statistical theory. Students who have completed 41000 should find this course quantitatively manageable.

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