Stochastic differential equations (SDEs) and random processes form a central framework for modelling systems influenced by inherent uncertainties. These mathematical constructs are used to rigorously ...
The study of stochastic differential equations (SDEs) has long been a cornerstone in the modelling of complex systems affected by randomness. In recent years, the extension to G-Brownian motion has ...
Brownian motion and Langevin's equation. Ito and Stratonovich Stochastic integrals. Stochastic calculus and Ito's formula. SDEs and PDEs of Kolmogorov. Fokker-Planck, and Dynkin. Boundary conditions, ...
This course is available on the MSc in Financial Mathematics, MSc in Quantitative Methods for Risk Management, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial ...
Studies mathematical theories and techniques for modeling financial markets. Specific topics include the binomial model, risk neutral pricing, stochastic calculus, connection to partial differential ...
This course is available on the MSc in Applicable Mathematics and MSc in Financial Mathematics. This course is available with permission as an outside option to students on other programmes where ...
This paper presents a novel and direct approach to solving boundary- and final-value problems, corresponding to barrier options, using forward pathwise deep learning and forward–backward stochastic ...
The course “Stochastische Analysis” is for master students who are already familiar with fundamental concepts of probability theory. Stochastic analysis is a branch of probability theory that is ...
The course “Stochastische Analysis” is for master students who are already familiar with fundamental concepts of probability theory. Stochastic analysis is a branch of probability theory that is ...
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