Course Descriptions
Ph.D Program Structure – IIT Stuart School of Business
The IIT Stuart PhD program offers two areas of concentration (Operations and Finance), and requires 64 credits to complete the program. Effective Fall 2011 semester, the PhD program structure has been improved in two respects. First, the program offers a more meaningful set of core and elective courses. Second, the content of these courses have been significantly upgraded.
In the first year, full-time students will complete the PhD basic core (a six course sequence of two courses each in Economics, Statistics and Optimization areas as described below) before taking the Qualifying Exam, as shown next:
MSC 601 – Economics I offers a doctoral level introduction to Economics. Course begins with a description of the primary tools of microeconomic analysis including set theory and optimization using calculus. These tools are then applied to models of consumer behavior and the theory of the firm. The joint behavior of these two sectors is then discussed in a partial and general equilibrium context. The course concludes with applications of equilibrium analysis that include social choice and welfare economics, strategic behavior, and information economics.
MSC 604 – Economics II studies economic analysis at the aggregate, economy wide, level. Topics include business cycle theory, monetary economics, growth theory, and global macroeconomic interaction. The course provides a fundamental understanding of the aggregate price indices, interest rates, exchange rates and stock price movements.
MSC 602 – Probability & Statistics (Statistics I) provides a comprehensive introduction to the statistical approach to tackling research problems (random variables, transformations, popular distributions used in management science such as normal, Student T, Chi-square, and generalized lambda; sampling methods, parameter estimation, confidence intervals and joint confidence intervals, hypotheses testing, sample size and power, regression and correlation), and statistical modeling. It will focus on the mathematics of differential equations, stationary time series models, conditional heteroscedasticity, non-stationary time series, co-integration and non-linear models. Students will also learn techniques like maximum likelihood estimation, likelihood ratio tests, and generalized method of moments estimation. Students will be introduced to stochastic processes and applied probability, Bayesian statistics, computational inference, extreme value theory, statistical modeling, survival analysis, design of control and cohort experimental studies, introduction to SAS statistical software, issues in data-screening/diagnostic testing and analyses of large databases.
MSC 605 – Econometrics (Statistics II) emphasizes regression analysis. The course begins with the classical linear regression model and variations based upon non-linearity, non-normality, heteroscedasticity and autocorrelation. The course also includes a discussion of cross-section data, systems of regression equations, dynamic regressions, and models with discrete dependent variables. The course emphasizes in-sample and post-sample forecasting and hypothesis testing. The course is heavily project oriented and students will be expected to work with modern statistical packages like R, SAS, SPSS and RATS. Projects will be drawn from financial and business applications.
MSC 603 – Optimization I focuses on optimization techniques, with emphasis on linear and nonlinear programming, and applications of optimization techniques. Topics include: the simplex-method and its variants; interior point algorithms; duality and sensitivity analysis; integer linear programming; theory and computational methods of nonlinear programming; convex analysis and unconstrained methods; Kuhn-Tucker theory; saddle points and duality; quadratic, linearly constrained, nonlinearly constrained, penalty, and barrier methods.
MSC 606 – Optimization II introduces students to the theory and computational methods of integer programming; cutting plane, branch-and-bound, and Lagrangian relaxation methods; model formulation with integer variables; theory and computational methods of dynamic programming; and applications of dynamic programming to deterministic and stochastic decision problems.
Qualifying Exam
In the second year, full-time students will complete the PhD advanced core and advanced elective courses (a six course sequence consisting of two research-grounding courses and four advanced electives as shown below) before taking the Comprehensive Exam:
Two Research Grounding courses
MSC 611 – Philosophy of Management introduces doctoral students to the history and evolution of thinking in the management discipline. It will focus attention on theories of leadership and innovation, and showcase contributions of influential thought leaders in management. It will also showcase epistemological perspectives with substantial potential for enhancing business research. Finally, it addresses fundamental approaches and criteria for successful theory development.
MSC 612 – Advanced Research Methods provides an in-depth overview of the General Linear Model at both univariate and multivariate research levels. The course will review measurement issues (reliability, types of validity), multiple regression, ANOVA, MANOVA, step-down analysis, factor analysis, structural equation models (exploratory and confirmatory factor analysis), discriminant analysis, redundancy analysis, canonical correlation analysis, repeated measures analysis, categorical data analysis, contingent valuation method, conjoint analysis, cluster analysis, multidimensional scaling, correspondence analysis, and choice models. Additionally, a comprehensive presentation of multi-level analysis, meta-analysis, data mining and neural networks will be offered.
Four advanced electives chosen from the following list of courses
MSC 621 – Corporate Finance describes how corporations use financial decisions to create shareholder value. Topics include net present value calculations, real options theory, equilibrium models of required rates of return, capital structure, and divident policy. The course also covers the use of financial theories in organization structure through mechanisms like economic value added, enterprise risk management, and mergers and acquisitions. This course offers a more formal mathematical presentation of corporate finance than is found in similar courses in masters’ level programs.
MSC 622 – Enterprise Risk Management focuses on the two main silos of risk in the financial industry, namely, credit risk and operational risk. The course will also discuss asset and liability management, interest rate risk management, integration of credit risk and market risk, regulatory and compliance issues, and performance measurement and capital management. The quantitative aspects of the course include: volatility and correlation modeling, Monte Carlo simulation, stress-testing scenarios analysis, extreme and tail events modeling.
MSC 631 – Theory of Finance covers basic theoretical work on asset pricing. It begins with economic theories related to the demand for risky assets and introduces concepts like risk aversion and risk measurement. The course then develops the primary equilibrium models of asset valuation including CAPM, Arrow-Debreu and consumption CAPM. The course also covers arbitrage pricing theory, optimal growth models, and the theory of corporate financial structure.
MSC 632 – International Finance Theory combines elements of global macroeconomics with models of financial pricing. The basic aim of the course is to understand the fundamental economic factors that determine the values of exchange rates, interest rates, and equity prices within the confines of an open and free capital market in which participants are well informed, rational and forward looking. Topics include purchasing power parity, monetary models, Lucas models of linked markets, real business cycles, contagion, market efficiency, and rational expectations. The course also covers Mundell-Fleming and Dombusch models that differentiate between rapidly adjusting asset markets and gradually adjusting commodity markets.
MSC 641 – Operations I focuses on special topics in the operations area that are best aligned with the research interests of the instructor. More specifically, these may address the management of quality and related aspects such as the economics of quality (returns to investment in quality) and the management of customer satisfaction.
MSC 642 – Operations II focuses on special topics in the Operations area that are best aligned with the research interests of the instructor. For example, it will address supply chain management and related inventory management issues.
Comprehensive Exam
In the third and fourth year of study, students will take four advisor approved elective courses (or 12 credit hours @ 3 credit hours/course) and enroll for 16 dissertation credit hours (or more credit hours as needed).
The IIT Stuart PhD program offers two areas of concentration (Operations and Finance), and requires 64 credits to complete the program. Effective Fall 2011 semester, the PhD program structure has been improved in two respects. First, the program offers a more meaningful set of core and elective courses. Second, the content of these courses have been significantly upgraded.
In the first year, full-time students will complete the PhD basic core (a six course sequence of two courses each in Economics, Statistics and Optimization areas as described below) before taking the Qualifying Exam, as shown next:
MSC 601 – Economics I offers a doctoral level introduction to Economics. Course begins with a description of the primary tools of microeconomic analysis including set theory and optimization using calculus. These tools are then applied to models of consumer behavior and the theory of the firm. The joint behavior of these two sectors is then discussed in a partial and general equilibrium context. The course concludes with applications of equilibrium analysis that include social choice and welfare economics, strategic behavior, and information economics.
MSC 604 – Economics II studies economic analysis at the aggregate, economy wide, level. Topics include business cycle theory, monetary economics, growth theory, and global macroeconomic interaction. The course provides a fundamental understanding of the aggregate price indices, interest rates, exchange rates and stock price movements.
MSC 602 – Probability & Statistics (Statistics I) provides a comprehensive introduction to the statistical approach to tackling research problems (random variables, transformations, popular distributions used in management science such as normal, Student T, Chi-square, and generalized lambda; sampling methods, parameter estimation, confidence intervals and joint confidence intervals, hypotheses testing, sample size and power, regression and correlation), and statistical modeling. It will focus on the mathematics of differential equations, stationary time series models, conditional heteroscedasticity, non-stationary time series, co-integration and non-linear models. Students will also learn techniques like maximum likelihood estimation, likelihood ratio tests, and generalized method of moments estimation. Students will be introduced to stochastic processes and applied probability, Bayesian statistics, computational inference, extreme value theory, statistical modeling, survival analysis, design of control and cohort experimental studies, introduction to SAS statistical software, issues in data-screening/diagnostic testing and analyses of large databases.
MSC 605 – Econometrics (Statistics II) emphasizes regression analysis. The course begins with the classical linear regression model and variations based upon non-linearity, non-normality, heteroscedasticity and autocorrelation. The course also includes a discussion of cross-section data, systems of regression equations, dynamic regressions, and models with discrete dependent variables. The course emphasizes in-sample and post-sample forecasting and hypothesis testing. The course is heavily project oriented and students will be expected to work with modern statistical packages like R, SAS, SPSS and RATS. Projects will be drawn from financial and business applications.
MSC 603 – Optimization I focuses on optimization techniques, with emphasis on linear and nonlinear programming, and applications of optimization techniques. Topics include: the simplex-method and its variants; interior point algorithms; duality and sensitivity analysis; integer linear programming; theory and computational methods of nonlinear programming; convex analysis and unconstrained methods; Kuhn-Tucker theory; saddle points and duality; quadratic, linearly constrained, nonlinearly constrained, penalty, and barrier methods.
MSC 606 – Optimization II introduces students to the theory and computational methods of integer programming; cutting plane, branch-and-bound, and Lagrangian relaxation methods; model formulation with integer variables; theory and computational methods of dynamic programming; and applications of dynamic programming to deterministic and stochastic decision problems.
Qualifying Exam
In the second year, full-time students will complete the PhD advanced core and advanced elective courses (a six course sequence consisting of two research-grounding courses and four advanced electives as shown below) before taking the Comprehensive Exam:
Two Research Grounding courses
MSC 611 – Philosophy of Management introduces doctoral students to the history and evolution of thinking in the management discipline. It will focus attention on theories of leadership and innovation, and showcase contributions of influential thought leaders in management. It will also showcase epistemological perspectives with substantial potential for enhancing business research. Finally, it addresses fundamental approaches and criteria for successful theory development.
MSC 612 – Advanced Research Methods provides an in-depth overview of the General Linear Model at both univariate and multivariate research levels. The course will review measurement issues (reliability, types of validity), multiple regression, ANOVA, MANOVA, step-down analysis, factor analysis, structural equation models (exploratory and confirmatory factor analysis), discriminant analysis, redundancy analysis, canonical correlation analysis, repeated measures analysis, categorical data analysis, contingent valuation method, conjoint analysis, cluster analysis, multidimensional scaling, correspondence analysis, and choice models. Additionally, a comprehensive presentation of multi-level analysis, meta-analysis, data mining and neural networks will be offered.
Four advanced electives chosen from the following list of courses
MSC 621 – Corporate Finance describes how corporations use financial decisions to create shareholder value. Topics include net present value calculations, real options theory, equilibrium models of required rates of return, capital structure, and divident policy. The course also covers the use of financial theories in organization structure through mechanisms like economic value added, enterprise risk management, and mergers and acquisitions. This course offers a more formal mathematical presentation of corporate finance than is found in similar courses in masters’ level programs.
MSC 622 – Enterprise Risk Management focuses on the two main silos of risk in the financial industry, namely, credit risk and operational risk. The course will also discuss asset and liability management, interest rate risk management, integration of credit risk and market risk, regulatory and compliance issues, and performance measurement and capital management. The quantitative aspects of the course include: volatility and correlation modeling, Monte Carlo simulation, stress-testing scenarios analysis, extreme and tail events modeling.
MSC 631 – Theory of Finance covers basic theoretical work on asset pricing. It begins with economic theories related to the demand for risky assets and introduces concepts like risk aversion and risk measurement. The course then develops the primary equilibrium models of asset valuation including CAPM, Arrow-Debreu and consumption CAPM. The course also covers arbitrage pricing theory, optimal growth models, and the theory of corporate financial structure.
MSC 632 – International Finance Theory combines elements of global macroeconomics with models of financial pricing. The basic aim of the course is to understand the fundamental economic factors that determine the values of exchange rates, interest rates, and equity prices within the confines of an open and free capital market in which participants are well informed, rational and forward looking. Topics include purchasing power parity, monetary models, Lucas models of linked markets, real business cycles, contagion, market efficiency, and rational expectations. The course also covers Mundell-Fleming and Dombusch models that differentiate between rapidly adjusting asset markets and gradually adjusting commodity markets.
MSC 641 – Operations I focuses on special topics in the operations area that are best aligned with the research interests of the instructor. More specifically, these may address the management of quality and related aspects such as the economics of quality (returns to investment in quality) and the management of customer satisfaction.
MSC 642 – Operations II focuses on special topics in the Operations area that are best aligned with the research interests of the instructor. For example, it will address supply chain management and related inventory management issues.
Comprehensive Exam
In the third and fourth year of study, students will take four advisor approved elective courses (or 12 credit hours @ 3 credit hours/course) and enroll for 16 dissertation credit hours (or more credit hours as needed).
Last modified: 01/18/2012 14:41:01
