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 ...

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 ...

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 ...

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 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 ...

In this paper, we consider a large class of continuous semi-martingale models and propose a generic framework for their simultaneous calibration to vanilla and no-touch options. The method builds on ...

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, ...