Teaching at the Institute of Finance and Commodity Markets

In teaching, we teach basic knowledge in the field of finance. Building on this, in the following semesters we focus on derivatives as well as on practical knowledge, such as programming in finance or portfolio management. In the further semesters we broaden the students' knowledge in the area of theoretical financial markets. We also offer seminars and theses on all topics.

Courses of studies of the institute

Bachelor
ENGINEERING AND BUSINESS ADMINISTRATION (6 SEMESTER)
Master
ECONOMICS AND MANAGEMENT (4 SEMESTER)
ENGINEERING AND BUSINESS ADMINISTRATION (4 SEMESTER)

Our courses this semester

  • Summer term 2023

    Bachelor Wirtschaftswissenschaft

    Kompetenzbereiche Betriebs- und Volkswirtschaftslehre

    • Praxismodul Finance (273014)

      Termine:Lehrpersonen:
      Fr. 14:30 - 16:00 | II-214Seebonn
      Inhalt:

      The aim of this course is to bridge the gap between theory and practice. The course has several parts:

      • Practical aspects of asset management
      • Workshop Trading Room Simulation: Students experience life as a financial trader in a simulated environment
      • Portfolio Challenge: Students have to build their own (hypothetical) portfolio of risky assets using real world stock market data and cricitcally evaluate the investment performance
      • Additional guest lectures on current topics of financial markets (tbd)

      Assessment of the course will be through one test and several assignmentsto be completed at home.

    • Seminar Finance: Derivatives & Risk Management (273015)

      Termine:Lehrpersonen:
      BlockveranstaltungKlöckner, Lauter
      Inhalt:

      Students write a term paper (Seminararbeit) about selected topics of derivatives and risk managemen. They present their work in a final meeting which also includes group discussion. More details are provided on the webpage of the Institute of Financial Markets.

      Bemerkungen:

      Prüfer: Prof. Dr. Prokopczuk

    Master Wirtschaftswissenschaft

    Kompetenzbereich (Area) Finance, Banking & Insurance

    • Advanced Derivatives (374006)

      Termine:Lehrpersonen:
      Mo. 11:00 - 12:30 | I-063Prokopczuk
      Inhalt:

      After a quick introduction, this course will focus on advanced topics of derivatives markets.

      Topics include:

      • Introduction to Stochastic Calculus
      • Black-Scholes Formula
      • Exotic Options
      • Interest Rate Derivatives
      • Numerical Procedures for Derivatives Pricing
      Literatur:

      Hull: Options, Futures and Other Derivatives

    • Exercise Advanced Derivatives (374023)

      Termine:Lehrpersonen:
      Fr. 09:15 - 10:45 | I-342Kowalke
      Inhalt:

      see lecture

      Literatur:

      see lecture

    • Master Seminar: Climate Risk in Finance & Insurance (374054)

      Termine:Lehrpersonen:
      BlockveranstaltungDecke, Prokopczuk, Schneider, Seebonn

    Mehrere Kompetenzbereiche (Areas)

    • Ringvorlesung Financial Markets and the Global Challenges (379059)

      Termine:Lehrpersonen:
      Di. 16:15 - 17:45 | I-342Blaufus, Dräger, Gassebner, Gnutzmann-Mkrtchyan, Prokopczuk, Schneider, Schöndube, Schröder, Sibbertsen, Todtenhaupt
      Inhalt:

      Financial markets are the backbone of the economy. The world is facing many challenges such as climate change, crime and international conflicts, ageing societies or economic disruptions. In this lecture series, faculty members of the School of Economics and Management will discuss how financial markets are related and/or might provide means to tackle these challenges. After attending the lecture series, students can pick one specific topic and write a term paper (Hausarbeit) supervised by the corresponding faculty member.

    Promotionsstudium

    1. Bereich: Fachliche Kompetenzen

    • Machine Learning: Theory and Applications (571007)

      Termine:Lehrpersonen:
      BlockveranstaltungSzimayer
      Inhalt:

      This course provides an overview of multiple machine learning techniques. The methods will be introduced on a theoretical level. Based on the presented theory, students implement these techniques using the programming language Python in computer lab sessions.
      The topics covered include:

      • Model Selection and Evaluation
      • Linear Models
      • Decision Trees
      • Support Vector Machines
      • Ensemble Learning
      • Clustering
      • Neural Networks and Outlook

      Based on the knowledge and skills develops in lectures and labs, research projects give students the opportunity to implement the techniques within an empirical research project in groups.

      Literatur:

      Zhou, Zhi-Hua (2021): Machine Learning, 1st ed.

      Bemerkungen:

      The examination of the course consists of a project report.

      Blockveranstaltung am 15./16.06.2023 und 22./23.06.2023 jeweils 9-18 Uhr im ITS-Pool. Anmeldung per Mail an sekretariat@fcm.uni-hannover.de bis zum 30.04.2023 erforderlich. Bitte beachten SIe die begleitende Übung 571008 Exercise Introduction to Machine Learning: Theory and Applications.

    • Exercise Machine Learning: Theory and Applications (571008)

      Termine:Lehrpersonen:
      BlockveranstaltungDöpp, Heuel

    3. Bereich: Wissenschaftliche Kompetenzen

    • Doktorandenseminar Finance (574001)

      Termine:Lehrpersonen:
      BlockveranstaltungDierkes, Dräger, Prokopczuk, Schneider
      Inhalt:

      PhD students in finance present their research projects.

    Forschungsveranstaltungen

    • Research Seminar Financial Markets and the Global Challenges (77782)

      Termine:Lehrpersonen:
      Mi. 11:00 - 12:30 | I-442Blaufus, Dierkes, Dräger, Gassebner, Gnutzmann-Mkrtchyan, Prokopczuk, Schneider, Schöndube, Schröder, Sibbertsen, Todtenhaupt
      Inhalt:

      External guests present their latest research

All courses of the institute

Further information and notes on university studies