Subject: Stochastic Processes	Code: MC265	

Semester	 Hours: C+S+L	Type	 Section	
1	2+2+0	compulsory	Computational Mathematics - in Hungarian	

Teaching Staff in Charge	Assoc.Prof. SOOS Anna, Ph.D., asoos@math.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. Brownian motion
4. Stochastic differential equations	
Selective 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
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, 198	
Assessment	Exam