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 ...

Rice University researchers have developed a theoretical framework using stochastic analysis to predict menopause timing. By modeling ovarian follicle transitions, the study reveals a universal ...

This paper studies dynamic identification of parameters of a dynamic stochastic general equilibrium model from the first and second moments of the data. Classical results for dynamic simultaneous ...

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, ...

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 ...

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 ...