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FIN 500 – Investments

General Information

This course introduces into the theoretical foundations of modern portfolio management and their applications. It covers expected utility theory, measures of risk and return, the theory of portfolio selection, asset pricing models and their empirical test, the efficient markets hypothesis, and issues in stock portfolio management.

Learning Outcomes

The course provides students with an understanding of the theoretical and conceptual foundations of modern quantitative portfolio management. Students learn to understand investment strategies, and to interpret and evaluate them against the background of capital market theory and the efficient markets paradigm.

Faculty

Prof. Dr. Erik Theissen

Prof. Dr. Erik Theissen

Chair of Finance
University of Mannheim
Business School
L 9, 1–2
68161 Mannheim
Phone: +49 621 181–1518
Fax: +49 621 181–1519
E-mail: theissen uni-mannheim.de
Can Yilanci, M.Sc.

Can Yilanci, M.Sc.

PhD Student
University of Mannheim
Business School
L 9, 1–2 – Room 202
68161 Mannheim
Phone: +49 621 181–1526
Fax: +49 621 181–1519
E-mail: cyilanci mail.uni-mannheim.de
Consultation hour(s):
by appointment

Further Information

  • Time & Venue

    The course will start on Tuesday, September 06.

    Both the lecture and the exercise session take place in M 003 PWC Hörsaal (Schloss Mittelbau) from 12.00 until 15.15.

  • Language

    The course is taught in English. All materials and the exam will be in English.

  • Prerequisites & Access

    • Students should have successfully attended the courses Finanzwirtschaft I and II in the Mannheim Bachelor program (or similar courses at other institutions)
    • Students should definitely be familiar with the material covered in Brealey, Myers and Allen: Principles of Corporate Finance, 10th edition, McGraw-Hill 2011: Chapters 7,8,9,13
    • The course FIN500 also requires basic knowledge in mathematics (optimization (unconstrained and constrained), elementary matrix algebra) and statistics (expected value, variance, covariance, correlation, t-tests)
  • Teaching Evaluations