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