Course Catalog

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Course Catalog

INTERNSHIP (BA3980)

Internships may be taken for 0 credits. Students may do more than one internship, but internship credit cannot cumulatively total more than 4 credits.

INTERNSHIP (BA3980)

Internships may be taken for 0 credits. Students may do more than one internship, but internship credit cannot cumulatively total more than 4 credits.

INTERNATIONAL BUSINESS (BA4003)

This course introduces students to the international business environment domains. It covers multinational corporation strategic imperatives and organizational challenges. It also addresses the following questions: What differentiates a global industry from a domestic one? What are the sources of competitive advantage in a global context? What organizational structural alternatives are available to multinationals?

SUSTAINABLE ASSET MANAGEMENT (BA4004)

We will explore the evolution of the Sustainable Finance sector, and its roots in ethically responsible investing. Following an in-depth analysis of corporate ESG (Environmental,Social & Governance) ratings and impact measurement, students will create a Sustainable Investment Portfolio using data provided by an ESG ratings agency. Students will then analyze and critique other SF vehicles such as active ownership, micro-finance, impact investing, green bonds and carbon trading sectors. Lastly, student will draw linkages between the SF vehicles studies and their role in achieving social/environmental goals. Pre-requisite:
Junior Standing

INVESTMENT ANALYSIS (BA4010)

Introduces the processes and analytical tools necessary for investment decision-making. Provides the basic skills, modes of analysis and institutional background useful to work in the investment area of finance firms or as an individual investor. Students who successfully complete the course are expected to be able to work in the field or to continue their specialization in Security Analysis or Portfolio Management.

MULTINATIONAL BUSINESS FINANCE (BA4018)

This course deals with the theory and practice of multinational financial management. Topics include: foreign exchange risk management, multinational working capital management, managing intra-corporate fund flows, foreign investment analysis, debt and equity financing, international financial crises, and Foreign Direct Investment.

COMPUTATIONAL FINANCE (BA4020)

This course is an introduction to applied computational methods for finance and the valuation of financial firms and elements of capital structure: equity, bonds, and options and additional methods for optimization of securities portfolios and hedging risk. We emphasize implementation and use selected models. Aimed at providing the necessary technical and analytical skills useful for graduate school work, working in financial firms or investment banks.

SUSTAINABLE FINANCE (BA4030)

Following an in-depth analysis of corporate ESG (Environmental, Social & Governance) ratings and impact measurement, students will create a Sustainable Investment Portfolio using these tools and risk/return analysis.Via hands-on involvement in an energy transformation project, students will gain key knowledge about locally based sustainability initiatives and their sources of financing.Students will also research, analyze and critique other prominent Sustainable Finance areas such as Micro Finance, Carbon Trading Schemes and Islamic Finance.

BEHAVIORAL FINANCE (BA4034)

Behavorial finance investigation is based on concepts of cognitive psychology decision theory. In addition, behavioral finance studies how real-life investors interpret and act on available information. Financial theories are dominated by efficient market theory assuming rational agents. he key assumption of financial models under this theory is the rational behavior of investors and other economic agents. Empirical observation demonstrates this assumption regularly is violated.Markets often are inefficient. Information disclosure is expensive, and accordingly is distributed asymmetrically. Heuristics may change the investors’ behavior and bias their decisions. Among biases are that each investment decision depends on our previous investment decisions: we are anchored by memory and experience and Bayesian approaches to the data are not of sufficient explanatory power to compensate for the remaining unknowns.