Focuses on practical aspects of corporate finance. Topics covered include: concepts of value creation, risk and required rates of return, financial maths, capital budgeting, capital structure and dividend policies.
Markets for shares, fixed income securities, options and futures. Methods of valuing shares, fixed income securities, options, and futures. Simple techniques of hedging risk. Portfolio diversification. Portfolio evaluation.
Explores the integration of sustainability principles into accounting and finance practices. Considers how businesses and organisations can measure, report, and manage their social, environmental, and economic impacts. Topics include sustainability reporting standards, ethical considerations, financial analysis tools, and strategies for sustainable financial decision-making.
A rigorous study of advanced capital budgeting procedures, more difficult aspects associated with capital structure and dividend decisions, mergers and acquisitions. Case study applications of financial management are used. A continuation of the material introduced in FINANCE 251.
Portfolio theory and equilibrium asset pricing models and empirical tests. Portfolio management (forecasting, construction, administration and evaluation) including issues relating to fixed interest and international equity investment. A continuation of the material introduced in FINANCE 261.
Examines theoretical and practical aspects of risk management with an emphasis on the effective use of futures, options and other financial derivatives to control market risk exposure. Reviews no-arbitrage methods used to value financial futures and options, including the Black- Scholes model and binomial tree numerical methods.
Provides a thorough understanding of the role of banks and other financial institutions in the economy. It focuses on the problems of risk management and regulation with a particular emphasis on problems, crises and most importantly the Global Financial Crisis.
Explores the most commonly used supervised machine learning techniques and their practical applications in portfolio management, trading, and valuation within the finance domain.
The theory and application of modern research methods in finance. The content will include the philosophy, process and design of scientific research. Prior knowledge of basic statistical techniques is assumed.
An introduction to the economic literatures relating to property rights, transaction cost economics, and agency theory. Application of these notions to the way in which organisations are structured. Identification of why some transactions are internalised and some are undertaken through markets. The application of these ideas to finance.
Examines the theory and application of modern research methods in finance. Through exposure to a range of contemporary research issues students will develop a basic framework of how to conduct research, and an overview of some of the pitfalls.
Examines contemporary theories and research practices in finance. Students apply the theories and practices by independently authoring and presenting a research project.
Applies contemporary machine learning techniques to problems in finance. Students will apply and evaluate machine learning models in areas such as and Economics 884 predictive modeling and natural language processing. It is recommended that students have prior knowledge of mathematics at the level of MATHS 208 and a basic understanding of finance theory.
Examines fundamental principles of corporate financial theory and discusses current issues, seminal theoretical contributions and empirical evidence regarding those theories. Specific topics will be chosen from capital structure, dividend policy, security issuance, mergers and acquisitions, corporate control and initial public offerings.
An applied practical opportunity for students to work with a New Zealand or international business or organisation in a consulting capacity to apply their advanced disciplinary knowledge and to develop research-informed strategic recommendations for a client.
Advanced coverage of contemporary issues in investments through readings of classic theoretical articles and recent empirical studies. Topics include market efficiency and empirical anomalies, risk-return relationships, and investment vehicles and strategies. This course builds on material covered in undergraduate courses in investments and financial markets, and it presumes the students have a working knowledge of calculus and linear algebra.
The theory and practice of financial risk management for portfolio managers with an emphasis on defining and measuring market risk. This course builds on material covered in FINANCE 362 and MATHS 208 with extensions to include the use of futures, options and other financial derivatives to manage market risk.
Students are expected to apply contemporary machine learning methods to topics in finance. The course focuses on the design and implementation of machine learning solutions in the field of finance.