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The focus of this course is to apply the fundamental ideas and tools of corporate finance to real-world corporate decisions. This course is designed to be the second course in the standard finance sequence; that is, it is designed to be the natural follow-up to the Winter Managerial Finance course. This course will develop and extend standard tools and techniques of financial analysis, valuation, and model-building, and apply these methods to a wide range of cases. Case topics will include capital structure, valuation, mergers and acquisitions, private equity, international finance, and financial distress. Students will be expected to develop detailed model-based analyses for the cases using the tools and techniques we develop in this course, and to employ their analyses to reach and defend specific recommendations for these cases.

This experiential course will focus on how to make a business decision correctly. The theory will focus on common behavior biases and mistakes. Students will practice making business decisions by analyzing a business case each week.

The course will take the perspective of a mid-level manager or decision-maker who is responsible for collecting, analyzing, and utilizing financial information in the context of a major transaction. We will integrate theories presented throughout courses in the core, particularly accounting and finance, and take a hands-on approach to understand how the theory is implemented in practice. The focus of the course will be on developing critical financial modeling skills, understanding best practices, and recognizing common pitfalls. Students will work on a series of cases and build models that can be used for earnings and pro-forma financial statement forecasts, valuation, the assessment of financing needs, merger analysis, and LBO evaluation. Students will also gain experience presenting financial models and critically assessing them. By the conclusion of the course, students will develop the skills to construct complex financial models and the logical frameworks to utilize them for various organizational applications. [Note: This course is geared toward students relatively new to financial modeling; those with extensive financial modeling backgrounds may be better served by an alternative course.]

Students will engage in the development of corporate financial modeling cases and solutions. Students will also develop materials to aid others in building financial models, and serve as case leaders during lab workshops. Extensive background in financial modeling and experience with Excel is required.

This is a course about the financial decision-making process largely from the point of view of the CEO of an entrepreneurial venture, ranging from very early to very late stages. The course takes a two-pronged approach: First, we develop tools and concepts of corporate finance related to modeling, valuation, control, and investment decisions within an entrepreneurial context. Second, we use cases with firms at different stages of their life cycles from initial angel or venture capital investments through exit decisions, in order to see the issues that arise when these principles are applied in practice. In some cases we show the viewpoint of the entrepreneur and in others the perspective of the investor. After all, as an entrepreneur, one cannot negotiate effectively without understanding an investor's motivations. Conversely, an investor cannot evaluate a potential investment opportunity without appreciating the entrepreneur's perspective and incentives. Finally, we explore new developments in entrepreneurial finance such as crowdfunding and early liquidity provisions.

The purpose of this course is to familiarize students with the different types of trading strategies employed by various money management institutions. These financial trading strategies are used to manage the risk and return profiles of specific portfolios. Throughout the sessions, students will be challenged to understand and explore the application and implementation of these different strategies. Trading simulations employed on the Rotman Interactive Trader and Rotman Portfolio Manager (using real market data and computer generated data) will be used extensively in this course as a way to learn and test different strategies. All classes will be held in the new Real-time Analytics and Investment Lab (RAIL), located on the third floor of the Bass Building (B312). Students are expected to attend all sessions. Graded are based on in-class simulation results, class participation, and two written assignments. This course is designed to have a fast learning curve and is a pre-requisite for FIN563, the advanced extension of this course.

This course is an extension of FIN562, Financial Trading Strategies. Students will expand on introductory topics from the Financial Trading Strategies Course and be required to build extensive live-market models and risk management models. Class discussions will closely link current market events and pricing anomalies to theoretical and simulated markets and we will closely study the deviations between them.

This course is an introduction to empirical research in asset pricing. The focus of the course is on the interplay between financial economic theory, econometric method, and that analysis of financial market data. Topics include tests of asset pricing models, return predictability in time-series and cross-section, empirical studies of asset market imperfections, and studies of individual and professional investor behavior. Class discussions will draw on textbooks/monographs and original articles and working papers.

This course provides an introduction to empirical research in corporate finance, with an emphasis on the application of cross-sectional and panel data econometric techniques for causal inference. Topics include investment policy, entrepreneurship and innovation, financing decisions, firm ownership, corporate governance, managerial incentives, financial contracting, and the structure and internal organization of firms. The course assumes knowledge of econometrics at the level of MGTECON 603.