The Master in Econometrics (MSc) at the University of Amsterdam (UvA) deals with statistical modelling, estimation and testing of economic models using economic and financial time series data.
Econometrics: Financial Econometrics
The Amsterdam School of Economics' Master’s in Econometrics provides a balanced and rigorous training in the quantitative analysis of problems in economics and finance. You will become fluent in the application of advanced mathematical and statistical methods, supported by modern software packages such as E-Views and Matlab. The multidisciplinary one-year programme consists of advanced courses in both mathematical economics and econometrics.
The programme in brief
To fully understand the field of Financial Econometrics, you'll need the skills, expertise and techniques that are required to apply robust statistical methods, to be used in exploring all topics, research and issues relevant to the discipline. Dive into(non) linear time series analysis, the Black-Scholes-Merton model and learn everything there is to know about Binomial Option Pricing – the subjects are endless. The multidisciplinary character of the programme is reflected in the wide range of courses you can take, such as: Stochastic Calculus, Micro-Econometrics, Financial Mathematics of Insurance, and Bounded Rationality.
All of the acclaimed lecturers in the programme are researchers in one of the ten research programmes of the Amsterdam School of Economics (ASE). Benefit from a curriculum designed to cover both the knowledge and skills required for financial econometrics careers in the field of business as well as in research. The ASE’s affiliation with a number of internal and external economics-related research institutes enriches the research and career opportunities for students in the Master’s programme.
The Financial Econometrics track of the master Econometrics is a one-year programme of 60 ECTS credits (1 ECTS credit = 0.5 US credits). The academic year runs from September to the middle of July and is divided into two semesters, each with three periods. Refer to the academic calendar for exact dates.
The curriculum for the Master’s in Econometrics is quite demanding, with classes taking up 12-15 hours a week on average. An additional 25 hours are required for class preparation, homework, debates, casework and computer time.
In the first semester, you'll be given a solid basis in econometrics with several core courses for students of all tracks. General Equilibrium Theory teaches you to formulate the general equilibrium model and understand its basic properties, and critically evaluate underlying model assumptions and implications. Through Advanced Econometrics 1 and 2, you’ll obtain a deep understanding of econometric theory, practice and inference by using a variety of advanced techniques. The theoretical background and economic applications of Game Theory trains you in the ability to model interactive decision-making situations using game-theoretic techniques, and compute and characterise their equilibrium outcomes.
You'll take one track defining course: Derivatives. You’ll learn about the most important types of financial derivatives, their markets and use for financial institutions and other firms, and gain advanced knowledge of models for the pricing and hedging of derivatives. For your elective, you can choose from the wide variety offered for all Econometrics tracks.
During the first part of the second semester, you'll focus on your specialisation track in two track defining courses. Financial Econometrics covers topics such as non-linear time series, volatility models, and the pricing of complex derivatives, while Stochastic Calculus helps you obtain a working knowledge of probability theory, stochastic processes and stochastic calculus. A third course can be chosen from the wide variety offered for all Econometrics tracks. Part two will be spent on completing a thesis in Financial Econometrics. A research staff member from the Department of Quantitative Economics will supervise your work.
This school offers programs in:
Last updated December 7, 2017