Cellular dynamics are intrinsically noisy, so mechanistic models must incorporate stochasticity if they are to adequately model experimental observations. As well as intrinsic stochasticity in gene ...

Simulation research derives new methods for the design, analysis, and optimization of simulation experiments. Research on stochastic models develops and analyzes models of systems with random behavior ...

Fundamental concepts of probability theory; modeling and analysis of systems having random dynamics, and in particular, queueing systems. Homework, exams and problem-solving sessions. This course is a ...

The development of exotic options depending on the dynamics of implied volatilities calls for multi-factor stochastic volatility models (SVMs) such as the Bergomi variance curve model and the ...

We introduce an approximation of forward-start options in a multi-factor local-stochastic volatility model. We derive explicit expansion formulas for the so-called forward implied volatility, which ...

The whole picture of Mathematical Modeling is systematically and thoroughly explained in this text for undergraduate and graduate students of mathematics, engineering, economics, finance, biology, ...

This course is available on the BSc in Actuarial Science, BSc in Data Science and BSc in Mathematics, Statistics and Business. This course is not available as an outside option. This course is ...

Are you looking to develop the skills to solve real-world challenges in finance, risk management, and insurance? These fields often deal with unpredictable phenomena—like investment decisions, ...

Background and MotivationAccurately pricing American-style options, which allow early exercise at any time before expiry, remains a significant ...