This course has two key objectives. The first is to take students who are familiar with the cornerstones of analytical work introduced in RSM3052H (equilibrium principles, spatial modelling, and the role of beliefs in game theory) and introduce them to a number of key areas where analytical work has made important contributions to the field of marketing. These include advertising, buyer-seller contexts characterized by asymmetric information, positioning, social responsibility, and two-sided markets.The second objective is to prepare students for a career in research, most immediately in terms of producing a research proposal that often evolves into a second-year research paper. The proposal will relate to a theoretical topic or an empirical topic. Students will go well beyond description of the research questions, methodology, and a literature review. The proposal will incorporate a detailed research plan and initial results.

The goals of this course are for PhD students in marketing to present their research ideas and receive feedback, as well as to critique the papers presented by External Marketing Speakers. The course contains three parts corresponding to three learning objectives. Part 1 is socialization into marketing academia. We will cover topics such as job market and academic career, the academic publication process, and how to write referee reports. Second-year students will practice writing a review. Part 2 is presenting research for feedback. The purpose of the presentations is to improve the student’s skills in crafting his/her research agenda, learn to convey this agenda to a broadly based audience of marketing scholars — in conferences and seminars, and improve through feedback. The other part of this process is providing constructive feedback to the colleagues and fellow students. Students will offer their perspective, their comments, and their suggestions to the presenters. Part 3 is about discussing and reviewing Frontier Research Successful scholars should keep track of the research advances in the fields. Our area’s seminar series invite external speakers from other schools, to present working papers. We will select their papers to discuss in the class. For each paper presented in the marketing seminar series by an external speaker on Fridays, we will discuss that paper in class on Mondays, which is four days prior to the speaker’s presentation. We will designate a student as the discussion leader (DL). DL will start the class discussion with a formal 15-minute discussion on the paper. Moreover, for each paper, I have invited one faculty member (who is an expert in that area) to lead the discussion after the DL had made his/her 15-minute presentation.

This course introduces students to the origins, the theory, the methods, the debates and the style, of research in the discipline of Judgment and Decision Making (JDM). The course starts with a historical overview of the emergence and the underlying philosophy of the field. We will dive deep into two major approaches to studying JDM. One of the approaches has roots in expected utility theory and is characterized by a demonstration of violations and the foundations of a new approach; while the other approach is rooted in cognitive psychology and pushes for models of different styles of decision-making and the decision of which model to use in making decisions. Topics covered will include utility theory, heuristics and biases, cognitive foundations of learning and hypothesis testing, contingent decision making, context based choice, mental accounting, intertemporal choice, judgment and decision engineering, the role of emotions in decision-making, choice architecture and applied behavioural science. Assessments include class participation (presentations/discussion), short research idea papers, and a final exam or paper.

This course covers recent research areas and topics in quantitative and/or behavioural marketing that are not covered in our other courses.

This course has two objectives. The first is to explore theoretical and methodological issues in the areas of employee selection, performance appraisal, and training. The second is to improve the student's skill in applying these theories and methodologies to organizational problems.

This seminar is an advanced graduate course in research methodology. This course will focus on the different stages involved in the process of conducting scientific research. There are three main objectives in this course. The first is to provide students with an understanding of the methodological concepts required to conduct empirical research. The second is to develop the ability of students to use these concepts in critically evaluating research. The third is to develop students’ skills in using these concepts to design their own research projects.

This course introduces advanced topics in organizational behaviour, with a special focus on the role of the individuals within organizations. It provides an overview of the research on individual attributes and characteristics, and how these influence cognitive processes and affect outcomes at the individual, group, and firm levels. The course begins with an overview of organizational behaviour research, tracing the origins of some of the most popular topics over the years, and proceeding to the in-depth study of these topics: personality and related attributes, attitudes and emotions, self-construal perceptions, culture and values, motivation, leadership, organizational justice, psychological contracts, cognition and decision making, and person-environment fit. For each chosen topic, both theory and empirical research will be covered, and the emphasis will be placed on the linkage between them

Organizational behaviour is the study of individual, group, and organizational actions and outcomes. This course introduces students to the study of meso OB, or the simultaneous study of two or more of these levels of analysis. Students learn multi-level theory and statistical techniques and read both classic and recent research and theory on topics that span levels, such as culture, social identity, status and power, and work group dynamics. Prior to each session, students will have read and reflected upon the assigned material. Meeting time will primarily be used to draw out key ideas from the theories, to discuss the contributions, strengths, and weaknesses of the work, to raise significant issues, and to consider the emerging general direction of the area. Students will develop their own meso research proposal and will present it to the class at the end of the semester.

A defining feature of scholarship in the applied behavioural sciences is its emphasis on empirical research, by collecting data and submitting it to quantitative analysis. This course covers fundamental issues in conducting the analysis of quantitative data collected in fields such as management, marketing, industrial relations, psychology, and related fields. It is designed for doctoral students who intend to conduct empirical research publishable in scholarly journals. This course covers model building and analysis, including topics such as an introduction to statistical inference, analysis of variance, regression analysis, testing and interpreting interaction effects, mediation analysis, hierarchical linear modeling, aggregation across levels of analysis, path analysis, and factor analysis. It concludes with strategies for managing the publishing process. A core focus of this course is on doing analyses that reflect current research in the applied behavioural sciences. Students are assigned core readings and, when appropriate, are given real empirical data to apply the method under discussion.

This course seeks to provide a forum in which to learn the process of doing research. The goal of this course is to improve your skills in the consumption and production of academic scholarship.

This course builds on the concepts that were covered in RSM3066H (Quantitative Methods in the Applied Behavioural Sciences) to expose students to more advanced statistical modeling techniques. The primary goals of the course are: 1) to provide students with an expanded toolkit of analytic approaches, 2) to facilitate statistical literacy and the ability to learn new techniques in the future, and 3) to provide a supportive group environment for discussing ongoing data issues. The statistical topics covered by this course will begin where the basic course left off, including working with Generalized Linear Models, Bayesian Statistics, Advanced Longitudinal Analyses, and Big Data. The course also provides a more detailed exploration of SEM and HLM, including more complex designs within these two approaches. The course also features "Data Workshop" days. These days allow discussion of real-world data challenges that students are facing in their ongoing research programs. Students will present their research questions, designs, and analytic strategies so that we can have group discussions about the underlying statistical issues. The goal here is to provide direct statistical support for student research projects.

Besides a firm grounding in their core discipline, PhD students in management also benefit from awareness of the multidisciplinary character of research in management and connections to standards of scientific inquiry across the disciplines. First, this course exposes students to the variety of research questions and research methodologies across the topic areas that dominate research and teaching at schools of management. Second, it provides guidance on developing research questions in management that make important contributions. Third, it provides opportunities for students to practice communicating the importance of their research to scholars in other management disciplines.

Independent course.

Independent course.

Independent course.

The objective of the course is to provide an applied background into macroeconomic issues that are relevant to finance professionals. Towards that end, the course presents a macroeconomic framework which will allow for a detailed examination of a series of interrelated topics, with a particular focus on monetary, fiscal and international economic developments with implications for financial sector developments.

This course emphasizes the theme of the "Accounting Art of War" (paraphrasing Sun Tzu. The second theme that this course embraces is the use of data analytics for financial statement analysis (e.g., the detection of accounting manipulations). The class emphasizes analysis rather than mechanical work. The objective of this course is to develop a set of tools for in-depth financial statements analysis and valuation.

This is a basic course in finance designed to provide the core skills necessary to complete more advanced work in finance and to provide the overall context of financial decision making. However, the pace is quick and those without much finance will find it difficult, but the material in this course is basic for understanding finance.

This course deals with the way companies, particularly financial institutions, manage risk. It covers credit risk, market risk, operational risk, and liquidity risk. The nature of bank regulation and the Basel capital requirements for banks are examined. Other topics include copulas, the calculation of economic capital, and RAROC.

This course will cover many aspects of investment banking — both from a financing perspective as well as mergers and acquisitions. The goal here is for you to understand many aspects of what is being done at an investment bank, including the products that are offered. On the corporate finance side there will be particular emphasis on how companies finance. We will go over the basics of why companies access public and private market as well as what the products are: debt, equity, preferreds, and securitizations. We will also cover the mechanics of going public, bought deals, and how to price equity and debt issues. We will also cover on the M&A side; creating and distributing value, M&A valuation techniques, and bankruptcy issues.

This course describes important fixed income securities and markets. It will provide an overview of traditional bond and term structure concepts as well as review a number of bond structures relevant to the different sectors of the fixed income market.

The applied portfolio management course will look at topics in portfolio management that go beyond the null of efficient markets. Topics covered will vary but may include alternatives to mean variance optimization such as the growth optimal portfolio, the role of active versus passive management and the relevance of recent anomalies that go under the rubric of inefficient markets or behavioural finance. Assignments will be done in groups back testing various investment strategies. The emphasis is on the interface between current investment research and real world investment strategies.

Course objectives are: to develop skills for quantifying risks; to evaluate risk and return modeling for forecasting risks and the associated potential returns; to identify and quantify parameter and model risks; and to develop trading/investment strategies taking explicit account of these risks. We will use learning-by-doing exercises to achieve these objectives. The first part of the course emphasizes developing Excel applications linked to actual financial data. We then apply what we have learned using experiential learning cases on the Rotman Interactive Trader platform for which our Excel applications will be linked to data from a simulated market, that is, data generated by the class participants. These interactive cases are analogous to using a flight simulator to learn to fly except in our case we are learning how to make effective financial decisions taking account of uncertainty about the future.

This course explains how the derivatives business works. It starts by using equity derivative examples to explain how dealers manufacture the derivatives that they sell to their customers. It then moves on to explain credit and interest rate derivatives

This quantitative course presents advanced material relevant for portfolio mangagers. First, it examines key elements of portfolio management with an emphasis on risk factors and strategic asset allocation (although tactical asset allocation and strategies designed to exploit apparent violations of market efficiency, etc. will also be discussed). Second, this course discusses implementation and oversight of portfolio strategies, performance evaluation, and practical issues related to hiring and evaluating asset managers. Discussionof these topics will be oftern based on relevant pratical examples and case studies.

This course will introduce students to the tools of machine learning with emphasis on their applications in finance. Students should be comfortable using Python before the course starts. They will also undertake three major machine learning projects (one individual and two in groups) using Python. The course will cover other financial innovations such as blockchain, payment systems, roboadvisors, InsurTech, and RegTech.

In this course, you will gain fluency in fundamental concepts, frameworks and methodologies useful to managers in crafting and executing business strategy. You will develop the ability to generate and evaluate strategic decisions in terms of positioning a company relative to external and internal factors to create sustainable value for shareholders and other constituents. Multi-business companies must also develop a corporate strategy to deliver value by focusing on interdependencies among the business units within a firm. As part of this journey, you will also understand what persistent performance differences are, why the field of strategy is focused on understanding them, and how they relate to the firm-level objective of maximizing profits. And you will become literate in the field of strategic management, including a grasp of its intellectual history, a solid understanding of its central ideas including the most up-to-date theories of strategy, and a good sense of how research insights are ultimately "commercialized" by strategy practitioners — a crucial skill to enable you to gain personal competitive advantage through evaluation and early adoption of new scholarly ideas throughout your career.

The purpose of this course is to improve participants ability to evaluate corporate and international strategies: in particular, the course will introduce participants to theories and methods that can improve management and decision-making in the area of vertical integration, diversification, international expansion, and new business development. The course will also introduce multi-business management tools such as business portfolio matrices.