Babes-Bolyai University of Cluj-Napoca
Faculty of Mathematics and Computer Science
Study Cycle: Master

SUBJECT

Code
Subject
MC265 Stochastic Processes
Section
Semester
Hours: C+S+L
Category
Type
Computational Mathematics - in Hungarian
1
2+2+0
compulsory
Teaching Staff in Charge
Assoc.Prof. SOOS Anna, Ph.D.,  asoosmath.ubbcluj.ro
Aims
To give to the students the principal notions of the stochastic processes which are necessary in the model process of the economic fenomens.
Content
1. Stochastic processes discrete in space and time. Markov chains. Transition probability matrices of a Markov chain. Chapman-Kolmogorov equation. The homogeneous Markov chain. Classification of states. The ergodic Markov chain.
2. Stochastic processes discrete in space and continuous in time. The homogeneous Markov process. The Poisson process. The simple birth process. The simple death process. The simple birth- and- death process.
3. Wiener processes. Properties and quadratic variation. Brownian motion.
4. Martingale and semimartingale.
5. Stochastic integral Ito formula for Wiener processes and fractional Wiener processes.
6. Stochastic differential equations. Different type of equations. Numerical solutions.
7. Applications.
References
1. Bharucha-Reid, A.T., Elements of the Theory of Markov Processes and their Applications, McGraw-Hill Book Company, Inc, Now York. Toronto. London, 1960.
2. Iosifescu, M., Lanturi Markov finite si aplicatii, Ed. Tehnica, Bucuresti, 1977.
3. Karlin, S., A first cours in stochastic processes, Academic Press, New York and London, 1966
5. Medvegyev P.: Sztochasztikus analizis, Typotex, Budapest, 2004
4. Michalberger, P., Szeidl, L., Varlaki, P.: Alkalmazott folyamatstatisztika es idoszor-analizis, Typotex, 2001
5. Oksendhal, S.: Stochastic differential equations, Springer, 2001
6. Tusnady, G., Ziermann, M. Idosorok analizise, Muszaki Kiado, Budapest, 1986
Assessment
Exam.
Links: Syllabus for all subjects
Romanian version for this subject
Rtf format for this subject