Stochastic analysis with applications (ΣΕΕ15): Διαφορά μεταξύ των αναθεωρήσεων
(Νέα σελίδα με 'Graduate Courses Outlines - [https://math.uoi.gr Department of Mathematics] === General === {| class="wikitable" |- ! School | School of Science |- ! Academic Unit | Department of Mathematics |- ! Level of Studies | Graduate |- ! Course Code | ΣΣΕ15 |- ! Semester | 2 |- ! Course Title | Stochastic analysis with applications |- ! Independent Teaching Activities | Lectures (Weekly Teaching Hours: 3, Credits: 7.5) |- ! Course Type | Specialized general know...') |
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Τελευταία αναθεώρηση της 16:39, 15 Ιουνίου 2023
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General
School | School of Science |
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Academic Unit | Department of Mathematics |
Level of Studies | Graduate |
Course Code | ΣΣΕ15 |
Semester | 2 |
Course Title | Stochastic analysis with applications |
Independent Teaching Activities | Lectures (Weekly Teaching Hours: 3, Credits: 7.5) |
Course Type | Specialized general knowledge |
Prerequisite Courses | - |
Language of Instruction and Examinations | Greek |
Is the Course Offered to Erasmus Students | Yes (in English, reading Course) |
Course Website (URL) | See eCourse, the Learning Management System maintained by the University of Ioannina. |
Learning Outcomes
Learning outcomes |
The course learning outcomes are: the presentation of the theoretical and practical fundamental concepts within Ito calculus, martingale methods, stochastic differential equations and diffusion processes. The application of this theory within linear filtering, optimal stopping and stochastic control, financial derivative. Upon successful completion of the course the student will be able to:
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General Competences |
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Syllabus
Stochastic processes in continuous time, processes adapted to an information flow, processes predictable with respect to an information flow, Brownian motion. Ito stochastic calculus. Martingales and representation theorems. Stochastic differential equations: existence and uniqueness of the solution. Theory of diffusions: Markov processes, Dynkin formula, Girsanov theorem. Applications: linear filtering, optimal stopping and stochastic control theory, Financial Derivatives.
Teaching and Learning Methods - Evaluation
Delivery | Face-to-face | ||||||||||
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Use of Information and Communications Technology | Use of ICT in communication with students | ||||||||||
Teaching Methods |
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Student Performance Evaluation |
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Attached Bibliography
- Karatzas I. and S. Shreve. Brownian Motion and Stochastic Calculus. Springer. 1998
- Lamberton, D. & Lapeyre, B. (1996). Introduction to Stochastic Calculus Applied to Finance. Chapman & Hall.
- Oksendal B.: Stochastic Differential Equations, 6th edition. Springer 2007.
- Revuz D. and M. Yor. Continuous martingales and Brownian motion. Springer. 2001
- Rogers L.C. and D. Williams.Diffusions, Markov Processes and Martingales. Vol.1 and 2, Cambridge University Press. 2002
- Steele J. M., Stochastic Calculus and Financial Applications, 2001.
- [Περιοδικό / Journal] Stochastic Analysis and Applications.