Financial Econometrics is a specialization of the Econometrics and Operations Research master's program. This hands-on study into the econometric methods used on a daily basis in the financial industry will let you become the quantitative financial specialist and will place you at the forefront of a successful professional career.
Financial Econometrics connects different academic disciplines including mathematics, statistics, finance, and business studies, and is primarily concerned with the use of financial economic theory and statistical techniques to analyse finance-economic data sets. The econometric methods can be used to analyse financial risk, investment strategies, financial economic policy, monetary policy, high-frequency trading, capital markets, financial stability, and many other topics.
Three core 6 EC courses (compulsory):
- Advanced Econometrics
- Multivariate Econometrics
- Time Series Models
Five specialization courses (of which one is compulsory and 2 or 3 elective):
- Asset Pricing
- Stochastic Processes: The Fundamentals
- Stochastic Processes for Finance and Derivatives Markets
- Financial Econometrics Case Study (compulsory; a practical study in a financial problem related to big data or high-frequency financial data)
One elective 6 EC course (or additional specialization course):
- Large Scale Data Engineering
- Web Data Processing Systems
- Financial Markets and Institutions
- Big Data Analytics
- Institutional Investments and Asset Liability Management
- Quantitative Financial Risk Management
- Computational Finance
Thesis (18 EC): an in-depth study on a challenging topic in financial econometrics with an emphasis on methodology, empirics or computing.
Typical placements include:
PhD student, Risk analyst, Quantitative Risk analyst, Risk Modeler, Investment analyst, Consultant Data Analytics, Systematic Quant, Systematic Trader, Financial Risk analyst, Financial Stability analyst, Capital Market analyst, Statistical researcher, Quantitative financial analyst, Quantitative researcher, Data analyst, Quantitative methods instructor, Data scientist, Capital Management consultant, Statistician, Quant Fund analyst, and many more
Why VU Amsterdam?
The program can be characterized as follows:
A program that will enhance your analytical skills, will invest in your quantitative insights, will learn you how to design and apply econometric methods in a finance context, and will broaden your quantitative horizons.
A program that will learn you how to analyse financial data, how to use statistical tools for financial questions of relevance, how to approach big data problems, how to interpret quantitative results, how to present the results of an econometric analysis, how to deduct conclusions and to make financial decisions from a quantitative analysis.
A program that will learn you to be a leading person in helping others to understand and work with quantitative methods in finance.
Admission with an International Degree
We welcome motivated and ambitious students who are interested in advancing their knowledge in Econometrics and related subjects and are aware of their role in society. In order to be successful in this program, you will need a solid basis in mathematics, statistics and econometrics. In particular, we expect that you have passed courses in mathematics (calculus, analysis), probability, mathematical statistics, and econometrics. Basic knowledge in computer programming is also required.
The track Econometrics of the Master's program Econometrics and Operations Research, with specializations Econometric Theory, Financial Econometrics, Empirical Marketing, and Quantitative Economics, is open to students with a university Bachelor's degree that provides a thorough knowledge in mathematics (analysis, calculus), probability, (mathematical) statistics, econometrics and computer programming. You need to have successfully completed courses and studied literature related to the core of this program, which is based on the following books.
- Calculus Early Transcendentals, James Stewart, Cengage Learning, International Metric Edition - 7th Edition, 2011.
- Linear Algebra and its Applications, David C. Lay, Steven R. Lay and Judi J. McDonald, Pearson Education, 5th Edition, 2016.
- A First Course in Probability, Seldon M. Ross, Pearson Education, 9th Edition, 2013.
- Fundamentals of Probability, with stochastic processes, Saeed Ghahramani, CRC Press, Taylor and Francis Group, 3rd Edition, 2016.
- Statistical Inference, George Casella and Roger L. Berger, Cengage Learning, 2008.
- Introduction to Econometrics, James H. Stock and Mark W. Watson, Pearson Education, 3rd Edition, 2014.
- Introductory Econometrics: A Modern Approach, Jeffrey M. Wooldridge, Cengage Learning, 2013.
- A Guide To Modern Econometrics, Marco Verbeek, Wiley, 5th Edition, 2017.
Basic skills in Computer Programming in Python, R, Matlab, Ox or Java.
If you can show certified exam results for courses that are related to the subjects and are of a comparable level (each course with a workload of 6 EC or close to it), this is satisfactory. The equivalence will be evaluated by the Examination Board and its approval determines the admission.
English language proficiency
The admission board wants to stress the intensity of the program: reading scientific articles and writing papers will be a key part, all in a very high pace. Your English language skills, both oral and written, are extremely important in this program. As you will have to communicate frequently with your fellow students and you will be working with and for international companies.
VU Amsterdam requires all applicants to take an English test. You can already apply online without having the test results. We do advise you to plan a test date as soon as possible. Below you will find the minimum English test scores for the program:
- Minimum general score 6,5
- Minimum score speaking 6,5
- Minimum score listening 6,5
- Minimum score writing 6,0
- Minimum score reading 6,0
- Paper-based test 580
- Internet-based test 92-93
- Cambridge Proficiency Exam A, B, C
- Cambridge Advanced Exam A, B, C