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Humboldt-Universität zu Berlin - High Dimensional Nonstationary Time Series

Qualification programme 2018-2022

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Programme structure

The aim of this IRTG cooperation is to train internationally competitive researchers with high scientific standards. The doctoral students will be introduced to challenging scientific problems at an early stage of their career. The qualification and tutoring concept of this IRTG will guarantee a solid, high level, education in mathematical and statistical tools together with a clear view for serious applications. The programme consists of a qualification phase comprising the necessary foundations, a development phase where students specialize in contents, methods and techniques, and a dissertation phase. We distinguish between a "default track" which is relevant for students entering the programme with the necessary background and a "qualifying track" for students lacking foundations. The default track lasts six semesters with the qualification and development phase to be finished after (at the latest) four semesters. The qualifying track lasts up to eight semesters as students have to catch up in foundations before they enter the core part of the programme. Hereby, qualifying students may qualify for a qualifying fellowship allowing them to extend their doctoral studies by up to 12 months. In the qualification track, students acquire the necessary background in a year or less and pursuit the default track afterwards.


Qualification phase

The programme starts once a year, at the beginning of the winter term (semester) (mid October). The qualification phase lasts maximally two semesters and is accomplished at the respective home university. The underlying criteria and the level of education will be the same at both institutions though the underlying courses naturally differ (for a list of courses see below).  At the start of the programme, a mentor will be assigned to each doctoral student helping with organizational matters and basic training questions. The mentor will be a more advanced doctoral student or a postdoctoral student. This helps to handle the transition between the two generations of doctoral researchers and promotes continuous integration and further exchange among the students. The mentor will typically be assigned during the Welcome Workshop “Rumble in the Jungle” in autumn where the new students and the second year students come together. At the end of the first semester, students will join the Haindorf Seminar. The participation in the five-day seminar will help the students to learn from the presentations of more advanced students and invited experienced researchers. Until the end of the first year of training, each student has to find his or her supervisor and has to present first their dissertation ideas.


Development phase

In the development phase, students follow courses with specialized topics providing the specific contents, which are necessary for their doctoral studies. These are courses regularly offered at HUB and XMU and/or (block) courses offered by invited guest scholars. The development phase lasts maximum three semesters and can overlap with the qualification phase in the second semester and the dissertation phase in the fourth semester. In this phase, the students will start to work on their first paper. They will now present their research work at the Haindorf Seminar and obtain valuable feedback from participating professors, guest lecturers and other doctoral students. Besides specialized course work and the start of their own research, this period is characterized by student exchanges between HUB and XMU. During their third semester (corresponding to the German winter term), XMU students stay at HUB where they are trained together with the HUB students. Hereby, the designated supervisors on both sides collaborate and form "research pairs" bringing together XMU and HUB students. These research pairs are co-supervised by the respective supervisors from both sides and have to start on a joint project, which forms the second paper in the HUB student’s doctorate. The fourth semester (corresponding to the summer term), HUB students spend at XMU, are trained together with their XMU colleagues and advance their joint papers.


Dissertation phase

The dissertation phase lasts two to three semesters. Students finalize two papers, write their third paper and integrate their research into an overarching theme. Typically, each of the papers has its own independent value and must meet with international standards. During this period, students are also encouraged to attend international conferences and to present their work. The presentation at the Motzen conference is obligatory for all students at the fourth and sixth semester. Furthermore, the mentors and supervisors help in selecting suitable conferences. We will keep an eye (in particular) on the American job market conferences in order to demonstrate that solid international RTGs are competitive research environments. Our past positive experiences have shown us that this is a realistic goal. Moreover, further visits at the partner institution are expected, for instance, to continue the established research collaborations.





Courses and Classes (Course Programme)

Students entering the programme have to document a background in the areas

  • Econometric Methods
  • Microeconomics or Macroeconomics
  • Time Series Analysis
  • Multivariate Analysis

of the extent of approximately 9 ECTS each.


Students lacking backgrounds in these areas receive a "qualification stipend", can extend their qualification period to two semesters such that they finish their development phase at latest after 24 months. Besides the regular course programme, they have to catch up in the aforementioned foundations. Courses in these areas are offered in cooperation with the BDPEMS and the MSc. "Statistics" at HUB (www.stat.de).


During the regular IRTG programme, students have to

  • collect 60 ECTS from course work and their own teaching,
  • regularly attend a research seminars during the dissertation phase (minimally 3 semesters),
  • attend at least one course in soft-skills,
  • be involved in the organization of at least one scientific event taking place at HUB, such as a conference, summer school or lecture series.


Minimally 25 ECTS have to be passed during the qualification phase, i.e. during the first year. The remaining credit points can be collected during the development phase and dissertation phase. Up to 10 ECTS can be collected from their own teaching, e.g., in tutorials.


In the qualification phase, students choose three courses between the following compulsory courses:

  • Advanced Econometrics (Fitzenberger, 6 ECTS)
  • Econometric Methods (Droge, 12 ECTS) 
  • Stochastics I (Reiß, in German, 10 ECTS)
  • Stochastics II: Stochastic Processes I (Reiß, in German or English, 10 ECTS)
  • Mathematical Statistics (Härdle/Spokoiny/Wang, 6 ECTS)
  • Non- and Semiparametric Modelling (Müller, 6 ECTS)
  • Modern Methods in Applied Stochastics and Nonparametric Statistics (Spokoiny, 6 ECTS)
  • Applied Multivariate Statistical Analysis (Härdle, 12 ECTS)
  • Mathematical Statistics Topics (Härdle, 6 ECTS)


In the development phase, students take courses, which allow them to specialize in certain areas. Our principle is not to setup specific specialization tracks in the development phase but to give students the possibility to compose their curriculum on an individual basis, which is tailored to the student's specific orientation. Therefore, students are obliged to collect their courses in agreement and consultancy with supervisors. Accordingly, students can choose from the following course areas. Please see table 4 for the complete list of all courses offered at HUB and XMU.

  • Estimation of Treatment Effects (HUB)
  • Mathematical Statistics (HUB)
  • Nonparametric Statistics (HUB)
  • Stochastics (HUB)
  • Statistics for Stochastic Processes (HUB)
  • Panel Data (HUB)
  • Time Series Analysis (HUB)
  • Selected Topics in Econometrics (HUB)
  • Advanced Financial Economics (XMU)
  • Derivates Analysis (XMU)
  • Advanced Microeconomics (XMU)
  • Advanced Macroeconomics (XMU)
  • Asset Pricing (XMU)


Alternatively or additionally, students can collect credit points (typically 3 credits) by attending topic or short courses taking place on an irregular basis and taught by external scholars. For this purpose, the IRTG plans to invite leading international scholars (see below for more details) to teach (block) courses in the areas:

  • Bootstrapping
  • Factor models
  • Volatility modeling
  • Regularization and shrinkage techniques
  • Forecasting
  • Modern parametric theory
  • Functional Time Series
  • Panel Data Models
  • Matrix Visualization
  • Big Data
  • Empirical Finance


Moreover, up to 9 ECTS can be taken in the form of external courses which are not directly offered within the programme but are all involved departments and institutions. These might be, for example, doctoral courses offered by the BDPEMS or the BMS. Furthermore, students can collect credit points by attending  summer/winter schools. The number of credit points awarded for such activities are individually fixed by the programme director.


The specific doctoral seminar, Privatissimum Statistics (PRI), takes place every Tuesday at 12 noon for two to four hours. It is a compulsory seminar, where students present and discuss preliminary results with participating researchers, other doctoral students and research guests. During the dissertation phase, students have to regularly participate in research seminars such as the

  • Economic Risk Seminar,
  • Mathematical Statistics Seminar,

which are both offered and hosted at HUB.


Furthermore, IRTG offers a wide range of training courses. These include key skills training courses provided by the department of continuing professional education (Berufliche Weiterbildung) of the HU. The doctoral students have to attend at least one course such as:

  • Advanced Thesis and Paper Writing
  • Statement Training
  • Rhetoric Seminar


Three to four times a year the Bloomberg seminar will be organized in cooperation with Bloomberg in order to inform the students on how to access data most efficiently. The seminar also functions as a platform for questions of the doctoral students concerning their individual challenges about data access, storage and editing. The mandatory seminar on “Rules of good scientific practice” ensures all doctoral students are well familiar with the international standards of research. 


Finally, students are obliged to (co-)organize at least one major scientific event, such as a conference, summer school or one of the activities illustrated below. Thereby, the idea is to also confront students with tasks of research administration and organization. Learning how to organize a conference, to raise funds and to set up an event schedule are important skills for every researcher. Moreover, it gives students the opportunity to establish valuable contacts to other (international) researchers and scholars.


Please see figure 2 for an overview of all components of the course programme. An example of successfully acquiring the required credits can be found in the Appendix 7 “Weg zur Promotion” of the Progress Report.


You may download a list of available courses here. Availability may be subject to change.


Soft skill electives


The program aims to foster both students' knowledge and curiosity and their soft skills as future team leaders and experts. Therefore, our students may also take courses outside of their field of studies:

Program for further Education and Qualification at HUB

 Here you may find a list with possible respective elective courses for the third and fourth semester.