Checking date: 04/06/2021

Course: 2021/2022

Advanced Stochastic Processes
Study: Bachelor in Statistics and Business (203)

Coordinating teacher: D AURIA , BERNARDO

Department assigned to the subject: Department of Statistics

Type: Electives
ECTS Credits: 6.0 ECTS


Requirements (Subjects that are assumed to be known)
Stochastic Processes
GENERAL COMPETENCES. CG4 - Identify or create the appropriate model for the specific problem that arises in each business activity (finance, marketing, planning and control of production, etc.). Manipulate computationally and analytically established models, taking advantage of the power of statistical methods, optimization, etc., and perform the analysis of the results obtained. SPECIFIC COMPETENCES. CE02 - Model and analyze statistical data, both static and dynamic, using statistical techniques CE09 - Prepare, construct and validate statistical models that reproduce the fundamental characteristics of the problems under analysis. CE10 - Interpret the results of a quantitative analysis and draw practical conclusions about the real problem for which the statistical models have been constructed. Write reports and communicate the conclusions with the help of advanced graphic representation techniques. CE14 - Identify and use financial tools to solve problems such as risk estimation, calculating the cost of capital, valuation of assets and / or derivatives or estimating the movement of the interest rate and / or exchange rates. TRANSVERSAL COMPETENCES. CT3 - Be able to organize and plan your work, making the right decisions based on the information available, gathering and interpreting relevant data to make judgments and critical thinking within your area of ¿¿study.
Skills and learning outcomes
Description of contents: programme
1 - Brownian motion 1.1 Definition and properties 1.2 Derived Processes 1.3 Simulation 2 - Martingales in continuous time 2.1 Definition and properties 2.2 Optional sampling theorem 3 - Stochastic Integration 3.1 Definition and properties 3.2 Lema of Itô 3.3 Girsanov's theorem 3.4 Martingale Representation Theorem 4 - Introduction to differential stochastic equations 4.1 Itô's Stochastic Differential Equations 4.2 Linear Differential Equations 4.3 Digital solutions 5 - Applications of stochastic calculus to Finance 5.1 The Black-Scholes formula 5.2 Risk neutral measures 5.3 Pricing Exotic options 5.4 Pricing American options
Learning activities and methodology
Theory (4 ECTS). Lectures. Practice (2 ECTS). Problem solving lessons.
Assessment System
  • % end-of-term-examination 0
  • % of continuous assessment (assigments, laboratory, practicals...) 100
Calendar of Continuous assessment
Basic Bibliography
  • H. Bühlmann. Mathematical Methods in Risk Theory.. Springer. 1996 (2nd. ed)
  • R. Durrett. Essentials of stochastic processes. Springer. 2012 (2nd ed.)
  • S. Asmussen and H. Albrecher. Ruin Probabilities. World Scientific. 2010 (2nd. ed.)
  • S.M. Ross. Stochastic Processes. John Wiley & Sons, inc.. 1996 (2nd. ed.)
Recursos electrónicosElectronic Resources *
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The course syllabus may change due academic events or other reasons.