Help organisations manage risks
In the Financial Econometrics track, you learn how to apply econometric techniques to support portfolio management or for example in the valuation of securities. Financial econometrics is all about applying statistical methods to financial market data. Areas of study include capital markets, financial institutions, corporate finance and corporate governance. Topics often revolve around asset valuation of individual stocks, bonds, derivatives, currencies and other financial instruments.
- Familiarise yourself with the application of econometric techniques on financial data.
- Interpret the results from a financial perspective.
- Become an expert in the complex mathematics of the financial economy.
Why choose the Financial Econometrics track?
- Focus on the econometric techniques that have been developed for the analysis of financial markets, in addition to the 4 general courses of the MSc Econometrics.
- You have access to up-to-date cases and learnings from the field of financial econometrics. You will be lectured by professors and experts working in a wide range of economic organisations and fields.
- After graduation, you have an excellent job prospect at e.g. major international banks or other financial institutions.
Apart from the 4 general courses of the full programme, you will follow 5 track-specific courses and electives.
In this course you learn the basic principles of asset pricing and risk mitigation on a market consistent basis. The underlying principle for this course is the notion that the market consistent value of an insurance or pension contract is based on the market value of the best possible replicating portfolio plus a possible add-on for the remaining (unhedgeable) residual risk. Therefore we provide you with an introduction to mathematical techniques which can be used in complete markets, such as those for equity and interest derivatives.
Mandatory electives: semester 1
Choose 1 out of 2 electives:
- Complex Economic Dynamics
- Machine Learning for Econometrics
Mandatory electives: semester 2
Choose 1 out of 8 electives:
- Behavioural Finance
- Economic and Financial Network Analysis
- Machine Learning in Finance
- Quantitative Finance and Algorithmic Trading
- Real Estate and Alternative Investments
- Real Estate Finance
- Behavioural Macro and Finance
In this course you learn the elements of probability theory, stochastic processes and stochastic calculus relevant in the analysis of financial derivatives. You focus on the mathematical concepts and techniques and to a lesser extent on their application in pricing and hedging derivatives.
In this course you cover: linear time series analysis, volatility models, value at risk, VAR models and co-integration, multivariate volatility and correlation models, high-frequency data and realized variance. You will apply your knowledge to empirical data using Python and R.
Study and compare the performance of high-frequency trading (HFT) algorithms for trading Bitcoins on cryptocurrency exchanges. It is possible to develop profitable trading strategies on the Bitcoin market? Does the inclusion of social indicators, retrieved from sentiment analysis, lead to significantly better results?
- Value at risk
- Activa pricing
- High frequency data from stock markets