Courses

Tuesday,
08:00am to 10:00am
at HU Berlin, Spandauer Str. 1, Room 22
Description:

The course deals with patterns of international trade, both in theory and empirics. Starting with the classic Ricardian and Heckscher-
Ohlin trade models, students will be introduced to modern models, such as Eaton & Kortum (2002), Melitz (2003) and Melitz &
Ottaviano (2008). In the tutorial students will present recent selected papers.
Ungraded but obligatory: presentation and two summaries (1 page each).
Literature: Robert C. Feenstra: „Advanced International Trade“ (2015), Princeton University Press;
Selected journal papers

Allgemeine Info:

Organisatorisches:
StO/PO MA 2005 - 2010: 6 LP, Modul: "Advanced International Trade: Theory and Empirics"
StO/PO MA 2016: 6 LP, Modul: "Advanced International Trade: Theory and Empirics"
StO/PO MEMS 2016: 6 LP, Modul: "Advanced International Trade: Theory and Empirics", Major: Macroeconomics

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Instructor:
at HU Berlin, Spandauer Straße 1, Room 125
Description:

The course deals with patterns of international trade, both in theory and empirics. Starting with the classic Ricardian and Heckscher-
Ohlin trade models, students will be introduced to modern models, such as Eaton & Kortum (2002), Melitz (2003) and Melitz &
Ottaviano (2008). In the tutorial students will present recent selected papers.
Ungraded but obligatory: presentation and two summaries (1 page each).
Literature: Robert C. Feenstra: „Advanced International Trade“ (2015), Princeton University Press;
Selected journal papers

Exam: Written exam (90 min)

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Tuesday,
10:00am to 12:00pm
at HU Berlin, Spandauer Str. 1, Room 21b
Description:

This course is designed for students and researchers who want to develop professional skills in modern quantitative finance. It is offered to interested students who have had some experience with probability, statistics and software applications but have not had advanced courses in mathematical finance. Although the course assumes only a modest background it moves quickly between different fields of applications and in the end, the participant can expect to have theoretical and computational tools that are deep enough and rich enough to be relied on throughout future professional careers. The compulsory textbook is readable for the graduate student in financial engineering as well as for the inexperienced newcomer to quantitative finance who wants to get a grip on modern statistical tools in financial data analysis. The experienced reader with a bright knowledge of mathematical finance will probably skip some sections but will hopefully enjoy the various computational tools of the presented techniques. A graduate student might think that some of the econometric techniques are well known. The mathematics of risk management and volatility dynamics will certainly introduce him into the rich realm of quantitative financial data analysis. The computer inexperienced user of this course is softly introduced into the interactive course concept and will certainly enjoy the various practical examples. The textbook is an e-book which is designed as an interactive document: a stream of text and information with various hints and links to additional tools and features. The course "Advanced Methods in Quantitative Finance" consists of four parts: Preliminaries, Value at Risk, Credit Risk and Implied Volatility. The first part of the course is a quick refresher of the most important concepts needed for this course. In the second part we treat the Approximation of the Value at Risk in conditional Gaussian Models, show how the VaR can be calculated using copulae and we discuss techniques of risk assessment beyond VaR. We then quantify the risk of yield spread changes via historical simulations. The third part deals with an analysis of rating migration probabilities. The forth part is devoted to the analysis of implied volatilities and their dynamics. We start with an analysis of the implied volatility surface and show how common PCA can be applied to model the dynamics of the surface. In the next two chapters we estimate the risk neutral state price density from observed option prices and the corresponding implied volatilities. We then calculate implied binomial trees to estimate the SPD, and present a method based on a local polynomial estimation of the implied volatility and its derivatives. The proposed methods are used to develop trading strategies based on the comparison of the historical SPD and the one implied by option prices.

Literature:
www.quantlet.de

Exam: Oral Exam

Credits:
3.00
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Instructor:
Monday,
10:00am to 12:00pm
at Spandauer Straße 1, room 23
Thursday,
10:00am to 12:00pm
at Spandauer Straße 1, room 203; Empirical Tutorials take place at R025 (Thu)
Description:

The course aims at providing the basic concepts and methods for analysing panel data. It begins with introducing different static panel models with fixed and random effects, and discusses the problem of estimation in these models. The course covers tests of hypotheses with panel data as well as techniques for serial correlation, heteroscedasticity, simultaneous equations, dynamic models and models for qualitative dependent variables.
In the tutorials the methods are revisited and applied to empirical data using the software STATA. A deeper insight into advanced methods and additional topics is offered by means of assignments, empirical studies and/or literature reviews.

Literature:
- Baltagi, B.H., (2005), Econometric Analysis of Panel Data, 3rd ed., Wiley, New York.
- Hsiao, C., (2003), Analysis of Panel Data, 2nd ed., Cambridge University Press.
- Arellano, M. (2003), Panel Data Econometrics, Oxford: Oxford University Press.

Exam: written exam (90 min), two exam dates

Credits:
9.00
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Instructor:
Wednesday,
10:00am to 12:00pm
at FU Berlin, Garystr.
Description:

The aim of applied microeconometrics is to analyze individual behavior on the basis of micro data (cross-section and panel data) of individuals, households, and firms.
The standard linear regression model is generally not applicable to micro data due to the non-metric measurement and censoring of dependent variables at the individual level, selectivity and incomplete observability of endogenous variables, and the dependence of individual observations over time. The empirical methods most frequently applied in empirical microeconomics are surveyed and several applications in empirical microeconomics are presented. Students learn how to apply these methods using micro data and the software package STATA.

Literature:
M. Verbeek, A Guide to Modern Econometrics (4 ed.), Wiley, 2012.
A. C. Cameron and P. K. Trivedi, Microeconometrics. Methods and Applications, Cambridge University Press, 2005
W. H. Greene, Econometric Analysis (7 ed.), Pearson, 2012, Chapters 11 and 17-19.
J. M. Wooldridge, Econometric Analysis of Cross Section and Panel Data, MIT Press, 2 ed. 2010
Selected journal articles on empirical applications.

Exam: Written final exam; research paper

Credits:
6.00
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Instructor:
Monday,
04:00pm to 06:00pm
at HU Berlin, Spandauer Str. 1, Room 23
Description:

Learn from Nobel prize winners, such as Engle (ARCH Models, 2003), Scholes, Merton, (Derivative Valuation, 1997) or Modigliani (Financial Markets Analysis, 1985) to understand statistics of financial markets!
The class is addressed to students with excellent knowledge of multivariate statistics and students with good skills in statistical software. This course is a starting point for students interested in quantitative finance and students with ambitions to work in the derivative, investment and risk-control departments. Former students of this course work for example at Deutsche Bank, Sal. Oppenheim, Citigroup, European Central Bank, BAFin, KPMG, Nadler Company and many international universities.

Literature:
Franke, J., Härdle, W., and Hafner, C. (2015) Statistics of Financial Markets: an Introduction. 4th ed., Springer Verlag, Heidelberg. ISBN: 978-3-642-54538-2 (555 p)

Härdle, W., Hautsch, N. and Overbeck, L. (2009) Applied Quantitative Finance. 2nd extended ed., Springer Verlag, Heidelberg. ISBN 978-3-540-69177-8 (448 p)

Hull (2005) Options, Futures, and Other Derivatives. 6th ed., Prentice Hall. ISBN 0-13-149908- 4 (816 p)

Härdle, W., Simar, L. (2015) Applied Multivariate Statistical Analysis. 4th extended ed., Springer Verlag, Heidelberg. ISBN 978-3-662-45170-0 (580 p)

Cizek, P., Härdle, W., Weron, R. (2011) Statistical Tools for Finance and Insurance. 2nd ed., Springer Verlag, Heidelberg. ISBN: 978-3-642-18061-3 (420 p)

www.quantlet.de

Exam: Oral Exam

Credits:
3.00
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Instructor:
Thursday,
02:30pm to 05:30pm
at DIW
Description:

Course objectives:

Covers statistical methods relevant for the analysis of data based on structural economic models
• Discuss advantages and limitations of structural econometric models. Give students an understanding of why and when adding structure is important.
• Focus on discrete choice methods for cross section and panel data
• Provide insights into strategy (especially, identification) in important papers in structural Labour, Public & IO literature. Give a feel of how one may go about establishing a structural model.
• Establish basic estimation techniques & numerical methods such as simulation, numerical integration and discretisation; coding best-practice using Matlab, such as loops vs. vectorisation, readability vs. speed, and sustainable coding for several projects.
• The aim is to equip students with skills allowing them to carry out independent empirical research

Course organization:

• Part I is taught by Daniel Kemptner, Part II by Peter Haan, Luke Haywood, and Hannes Ullrich.
• Credit points: 12 ECTS. 5 sessions in Part I, 8 sessions in Part II. Both parts must be completed to gain credits.
• Prerequisites: skills in advanced econometric methods (Master or Ph.D. level)
• All sessions in this course take place at DIW.
• First session: 20.4.2017
• Final session: 20.7.2017 (Exam)

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Instructor:
Description:

the tutorial is Monday from 10-12 and the lecture from 14-16

Content:The Economics of Climate Change is an introductory course into economic assessment of climate change impacts and optimal mitigation and adaptation response. Welfare-economic concepts such as cost-benefit analysis, discounting, intergenerational equity, non-market valuation are applied to understand the impact of climate change and mitigation on long-term welfare and growth.
·         Topics: Along the lines of the Stern Review and the IPCC fifth assessment report, we provide a systematic overview of the relevant issues in climate change economics.
This includes, inter alia:
·         physics of climate change: global warming, radiative forcing, greenhouse gases, feedbacks, carbon cycle, uncertainties and projections
·         climate change impacts on biological and human systems, vulnerability, adaptive capacity, tipping points
·         social cost-benefit analysis, market and non-market valuation of impacts, discounting, and its ethical implications for inter-generational equity
·         stock pollutants: the atmosphere as a limited disposal space for greenhouse gases
·         macroeconomic modeling approaches to assess the costs of climate stabilization
·         concepts of social welfare
·         the interrelation between climate change and economic development and growth
·         theories of economic growth, such as the Solow and Ramsey growth models
·         Hotellig’s rule for optimal resource extraction
·         mitigation options in different sectors, including land and bioenergy, cities and transport, power generation and variable renewables

Credits:
6.00
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Instructor:
at Haus Tornow am See
Description:

This seminar is intended to give participants exposure to state of the art research in time series econometrics and its applications in empirical finance and macroeconomics.
The course provides doctoral students the opportunity to present their own, preliminary research in these areas.

Time and location: August 16-17, 2017 at Haus Tornow am See

Registration:

To register for the seminar, you will need to send an e-mail including an extended abstract (not more than one page) to simon.jurkatis@fu-berlin.de
Registration should take place as soon as possible, but not later than 31 May, 2017.

Requirements:

The seminar paper will be due few weeks before the date of the seminar. Papers are encouraged to be preliminary.

Credits:
3.00
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