Markets offer large number of different kinds of derivatives on underlying assets like financial instruments and commodities. A common derivative is an option giving the right to sell (put) or buy (call) a given stock at its expiry. Pricing the derivatives is typically based a stochastic model for the value of the underlying asset. This course covers two numerical techniques to compute the price of options. The first one is the Monte Carlo method which samples sufficient number of asset value paths. The second approach derives a partial differential equation for the price and then solves it numerically using a finite difference method. The course teaches the basic properties of these methods and how to implement them using Matlab. The Black-Scholes model (geometrical Brownian motion) for the underlying asset and some of its generalizations will be considered.

Period
18-08-2014 - 22-08-2014 (1 weeks)

Target group
The Summer School annually offers courses for advanced masters students, graduate students and post-docs in the various fields of science and information technology.

Course aim
Participating the Summer School is free of charge, but student have to cover the costs of own travel, accommodation and meals at Jyvskyl.



Credits
3.0 ECTS creditsObligatory attendance at lectures, and completing the exercises.Grading: Pass/fail

Course fee
EUR 0[Convert to USD]Participating the Summer School is free of charge, but student have to cover the costs of own travel, accommodation and meals at Jyvskyl.

Course leader
Coordinator: Dr. Sanna Mnkl (University of Jyvskyl, Finland)Lecturers: Senior Lecturer Lina von Sydow (Division of Scientific Computing, Uppsala, Sweden), and Prof. Jari Toivanen (Institute for Computational and Mathematical Engineering, Stanford

Scholarships
The 24th Jyvskyl Summer School is not able to grant any Summer School students financial support. In order to ensure your participation, we recommend that you take steps to secure your own funding, for example, by turning first to your home institution

University of Jyvaskyla Faculty of Mathematics and Science and Faculty of Information Technology
Address: Jyvaskyla Summer School, Faculty of Mathematics and Science P.O.Box 35 (YK312), FIN-40014 University of Jyvaskyla, Finland
Postal code: FIN-40014
City: Jyvaskyla
Country: Finland
Website: http://www.jyu.fi/summerschool
E-mail: jss@jyu.fi
Phone: +358505818351