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Stochastic Processes

General data

Course ID:	360-MS2-1PSa
Erasmus code / ISCED:	(unknown) / (unknown)
Course title:	Stochastic Processes
Name in Polish:	Stochastic Processes
Organizational unit:	Faculty of Mathematics
Course groups:	(in Polish) Erasmus+ sem. letni
ECTS credit allocation (and other scores):	6.00 Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	English
Type of course:	elective courses
Full description:	(in Polish) Course profile: academic Form of study: stationary Course type: obligatory Academic discipline:science and natural science, field of study in the arts and science: mathematics Year: 1, semester: 2 Prerequisities: lecture 30 h. exercise class 30 h. Verification methods: lectures, exercises, consultations, studying literature, home works, discussions in groups. ECTS credits: 6 Balance of student workload: attending lectures15x2h = 30h attending exercise classes 15x2h = 30h preparation for classes 7x3h = 21h completing notes after exercises and lectures 7x2h = 14h consultations 12x1h = 12h the final examination: preparation.and take 12h + 3h = 15h control works: repeating the material and preparation 3x4h = 12h Quantitative description Direct interaction with the teacher: 77 h., 3 ECTS
Bibliography:	(in Polish) 1. P. Billingsley Probability and measure, Wiley Series in Probability and Mathematical Statistics, 1995 2. I. Gichman, A. Skorochod, The Theory of Stochastic Processes, Springer Verlag 1974 3. I. Karatzas, S. E. Shreve Brownian Motion and Stochastic Calculus Springer 1991. 4. T. Brzeźniak, T. Zastawniak Basic stochastic processes, A Course Through Exercises, Springer Verlag 1999 5. F. Klebaner Introduction To Stochastic Calculus With Applications, Imperial College Press, 2005 6. T.Mikosch Elementary stochastic calculus with finanse, World Scientific Publishing 2004
Learning outcomes:	(in Polish) Student has ability for modelling financial and actuarial phenomena by stochastic processes. Student knows: 1. the notion of stochastic process and its characteristics KA7_WG01 , KA7_KK02 2. the notion and properties of conditional expected value KA7_WG02 3. important examples of discrete and continuous stochastic processes KA7_WG10 , KA7_UW02 4. Markov chains and their properties KA7_UW11, KA7_UW16 5. Wiener process and its properties KA7_WG11 6. the notion and applications of Ito integral KA7_WG10 , KA7_UK02 7. Elements of stochastic differential equations KA7_WG06, KA7_WG11 , KA7_KK01
Assessment methods and assessment criteria:	(in Polish) The overall form of credit for the course: final exam.

Classes in period "Academic year 2023/2024" (past)

Time span:	2023-10-01 - 2024-06-30	Selected timetable range: weekly course term Go to timetable MO TU WYK W TH CW FR
Type of class:	Class, 30 hours more information Lecture, 30 hours more information
Coordinators:	Tomasz Czyżycki, Aneta Sliżewska
Group instructors:	Tomasz Czyżycki
Students list:	(inaccessible to you)
Credit:	Course - Examination Class - Grading

Classes in period "Academic year 2024/2025" (past)

Time span:	2024-10-01 - 2025-06-30	Selected timetable range: weekly course term Go to timetable MO TU W WYK TH FR CW
Type of class:	Class, 30 hours more information Lecture, 30 hours more information
Coordinators:	Tomasz Czyżycki
Group instructors:	Tomasz Czyżycki
Students list:	(inaccessible to you)
Credit:	Course - Examination Class - Grading

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