Courses
Courses
Asset Management and Hedge Fund Strategies (Master's course)
Faculty
Lasse Heje Pedersen
Big Data Asset Pricing (PhD course)
Faculty
Lasse Heje Pedersen and Theis Ingerslev Jensen
Prerequisites
The course is designed as a first-year Ph.D. course. The prerequisites are knowledge of asset pricing theory and econometrics at a M.Sc. level and an ability to work independently with data using a programmatic computer language such as Matlab, R, or Python. Students must participate in the whole course and do all problem sets.
Aim
The aim of the class is to introduce Ph.D. students in finance and related fields to empirical asset pricing research methods using big data.
Corporate Finance (Bachelor's course)
Faculty
Markus Ibert
Learning objectives
- Identify, explain, discuss, and apply the core concepts, models, and methods
- Calculate, interpret, and compare financial statistics, prices, returns, and costs
- Elaborate, present, and discuss solutions for financial decision problems
Derivatives and Fixed Income (Master's course)
Faculty
Peter Feldhütter
Learning objectives
- Understand and explain the payoff and risk properties of the main types of derivative securities
- Understand and explain how derivative securities can be used for risk management
- Understand, explain, and apply the central methods and models for the pricing of derivative securities
Derivatives and Risk Management (Master's course)
Faculty
Peter Feldhütter
Prerequisites
This is a mandatory course for the MSc in Advanced Economics and Finance. It is assumed that students have knowledge similar to the entry requirements for the MSc in Advanced Economics and Finance. For spring courses knowledge similar to the content of the 1st-semester courses is assumed as well. The courses have 45 contact hours (lectures and exercises), and there is a high level of interaction between lecturer and students, and in general a high work load.
- Be able to analyze, price, and discuss the use of derivative securities
- Be able to analyze, discuss, and apply the concept of no-arbitrage and its limitations
- Be able to analyze, discuss, and apply interest rate risk and credit risk modelling concepts
- Be able to apply and analyze Value-at-Risk based risk measures
- Be able to analyze and discuss financial risk management in financial institutions
Empirical Finance: Fixed income (PhD course)
Faculty
Peter Feldhütter
Prerequisites
Knowledge of asset pricing, corporate finance and econometrics at a M.Sc. level is expected. Otherwise, the course is designed as a first PhD course in empirical finance.
The course is open for other participants with an adequate background
Aim
This course is a course on fixed income at the PhD level. The course attempts to lay the groundwork for students who will later do actual empirical research work in fixed income. It is therefore a hands on course where the students will have to perform analysis on actual data, and where the examples are chosen to illustrate the typical questions asked in finance research. The focus is on classic estimation methods, but the course will also, where relevant, outline recent developments.
Financial Econometrics (Master's course)
Faculty
Rasmus Tangsgaard Varneskov
Learning objectives
The course will provide students with an understanding of how carry out econometric analysis within different subfields of finance. In particular, the students will obtain a toolbox consisting of knowledge of modern models, methods, and econometrics that are required for analyzing financial data
Prerequisites
Baseline knowledge of statistics, econometrics and asset pricing. Experience with coding is an advantage.
Financial Intermediation (Master's course)
Faculty
David Lando
Learning objectives
The course introduces students to financial intermediation with a main focus on banking:
- Explain the assets, liabilities and key sources of risk of some main types of financial intermediaries, including banks, investment banks, pension funds, mortgage institutions, and insurance companies
- Explain the key roles performed by banks in an economy including the role in the domestic and international payment system, maturity transformation, screening and monitoring of borrowers, and in the implementation of monetary policy
- Explain and discuss the composition and riskiness of bank assets for a representative bank
- Explain different short-term and long-term funding sources of banks, including deposits, interbank loans, repos, commercial paper, medium term notes, covered bonds, contingent capital, equity, funding in foreign currency, FX swaps
- Understand a simplified version of the Diamond-Dybvig model
- Use a structural (Merton) model of credit risk to value debt and equity and use the model flexibly to analyze deposit insurance, risk taking incentives, etc.
- Explain the concept and importance of off-balance sheet commitments .Explain and discuss shadow banking
- Explain the rationale behind banking regulation and discuss whether higher capital requirements affect bank lending. Explain and discuss key concepts in financial regulation such as risk weighted assets, capital ratios, the leverage ratio, net stable funding ratio, liquidity coverage ratios
- Understand and apply the single factor portfolio credit risk model
- Explain securitization and apply the single factor model to pricing of tranches with different priority in asset securitizations. Understand and apply the mixed binomial model.
- Discuss cost of capital for banks and capital allocation within banks.
- Understand the tools of monetary policy applied by central banks and how they operate through the banking system. Discuss payment systems and settlement,Introduce the market for Eurodollars..
Finansiering (Bachelor's course)
Faculty
Jens Dick-Nielsen