Financial Mathematics II

Content

  • Girsanov change of measure, martingale representation; 
  • Continuous-time financial market models: Valuation and 

    hedging of derivatives in complete and incomplete financial
    markets, stochastic volatility;

  • Interest rate models: Term structure modeling, interest 

    rate derivatives, LIBOR market models; (elective)

Lecture Notes and Exercises

All materials will be available on Moodle.

Literature

  • Bingham, N. H. and Kiesel, R.: Risk-Neutral Valuation: Pricing and Hedging of Financial Derivatives. (Springer) 2nd edn., 2004.
  • Karatzas, I. and Shreve, S.: Brownian Motion and Stochastic Calculus. (Springer), 1998.
  • Lamberton, D. and Lapeyre, B.: Introduction to stochastic calculus applied to finance. (Chapman & Hall), 2nd edn., 2008.
  • Oksendal, B.: Stochastic Differential Equations. (Springer, Berlin), 5th edn., 1998.
  • Shiryaev, A.: Essentials of Stochastic Finance. (World Scientifc), 1999.
  • Revuz, D. and Yor, M.: Continuous Martingales and Brownian motion. (Springer), 1999.
  • Shreve, S.: Stochastic Calculus for Finance II: Continuous-Time Model. (Springer), 2004.
  • Steele, M.: Stochastic Calculus with Financial Applications. (Springer), 2001.

You can also find the literature in the Semesterapparat.

People

Lecturer
Robert Stelzer

Class teacher
Bennet Ströh

Time and Venue

  • The institute is offering all courses originally planned starting April 20th. Teaching will take place online using the university's moodle system. Further information is available on the moodle system.
  • The course will be taught in the second half of the summer term 2020. It is a (2+1)-course and there will be 4 hours of lecture and 2 hours of exercise every week.

Type

  • Master Mathematik (optional)
  • Master Wirtschaftsmathematik (optional)
  • Master Mathematische Biometrie (optional)
  • Master of Finance-Major Financial Mathematics (obligatory)
  • Master of Finance-Major Financial Economics (optional)
  • Master of Finance-Major Actuarial Science (optional)

Prerequisites

  • Elementary Probability and Measure Theory or Introduction to Measure Theoretic Probability
  • Stochastic Analysis
  • Recommended: Stochastics II