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Introduction to Systematic Investment Strategies


Seminar

gehalten von Dr. Sergey Perminov und Konstantin Andreyev
 

  • Mittwochs, 8:00-10:00 Uhr, Raum 3042 KGIII.

 

Das erste Treffen findet am Mittwoch, 18. April 2018 statt.

 

Das Seminar wird auf Englisch gehalten werden.

 

Bewerbung

Die Bewerbung für das Seminar im Sommersemester 2018 ist bis zum 16.04.2018 möglich. Bitte senden Sie hierzu Ihre Bewerbungsunterlagen per Email mit:

  • Kreditpunkteauszug,
  • Matrikelnummer,
  • Studiengang/Studienjahr
     

an das Sekretariat.

 

Inhalt

This course is teaching students design and implement systematic investment strategies, which were long restricted to hedge funds and investment banks:

  • learn, design and program a modern systematic investment algo to capture market's inefficiencies,
  • use the secret weapon used by Wall Street to incorporate volumes of data, test strategies, conquer emotional biases, and beat the market,
  • learn to utilize Quantopian platform which provides end-to-end support for algorithmic investing, including algorithm writing, backtesting with a database of 12 years of historical & fundamental data, forward testing with live data, paper trading,
  • learn to evaluate, optimize and pick the best algo based on various backtest characteristics.

 

Using the Quantopian platform:

  • get access to the tools, capabilities and community you need to create and optimize your own trading algorithms in an open and transparent environment,
  • put those algorithms to work in the simulated historical trading.

 

You will be able to engage in a community where people can discuss concepts, processes and performance and learn from peers and experts. The result is a better way to understand design and function of systematic models.

Community: Quantopian is built around a community of more than 130.000 members. The members include finance professionals, scientists, developers, and students from more than 180 countries from around the world. These quants teach, advise, and help each other every day.

Python: Algorithms in Quantopian are written in Python. The Python language is ubiquitous in the tech and academic world today, and is not a proprietary, niche language only used for trading.

Format: The course can be taken as a standalone seminar (4 ECTS) or as a topics course (6 ECTS). In the seminar students will learn how to use quantopian platform to analyze investment problems, create algos and backtest them. The participants will move step by step and every week will be given a small task to complete. At each meeting, randomly selected students will present their work, telling fellow students how they approached the problem, what were the challenges and how it was solved. Students are encouraged to ask questions and discuss relevant points and challenges they are facing in order to improve mutual learning. Students will communicate online and offline with the project supervisors (Beneficious Investment Management) and other students on project-related issues.

Students wishing to earn extra credits, can take the course in the form of a topics course. This will require the same steps as the seminar as well as completion of an individual research based on learned techniques in the seminar and passing a 60min written examination. Individual research will be about exploring the real world phenomena, creating bespoke investment strategy, backtest and optimizing it.

 

Anrechnung

Für die erfolgreiche Teilnahme am Seminar können 4 ECTS-Punkte angerechnet werden.

Zusätzliche 2 ECTS-Punkte können erlangt werden, wenn man das Seminar als Topics Course weiter führt.

Die Veranstaltung kann von Studierenden der Studiengänge M.Sc. Economics,  M.Sc. VWL sowie M.Sc. Mathematik belegt werden.

Im M.Sc. Economics kann das Seminar in der Profillinie "Finance" angerechnet werden.

Im M.Sc. VWL kann das Seminar im Spezialisierungsbereich Accounting, Finance, and Taxation (PO 2014, gültig ab WS 2014/2015) angerechnet werden.

Master-Studierende der Mathematik des Profils Finanzmathematik können den Kurs als wirtschaftswissenschaftliches Wahlpflichtmodul verbuchen.

Benutzerspezifische Werkzeuge