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Linear Stochastic Dyadic Model [PDF]
Journal of Statistical Physics, 2021 AbstractWe discuss a stochastic interacting particles’ system connected to dyadic models of turbulence, defining suitable classes of solutions and proving their existence and uniqueness. We investigate the regularity of a particular family of solutions, called moderate, and we conclude with existence and uniqueness of invariant measures associated with
Luigi Amedeo Bianchi, Francesco Morandin
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Modelling stochastic correlation [PDF]
Journal of Mathematics in Industry, 2016 This work deals with the stochastic modelling of correlation in finance. It is well known that the correlation between financial products, financial institutions, e.g., plays an essential role in pricing and evaluation of financial derivatives. Using simply a constant or deterministic correlation may lead to correlation risk, since market observations ...
Teng, Long +2 more
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Multivariate Stochastic Variance Models [PDF]
The Review of Economic Studies, 1994 Abstract Changes in variance, or volatility, over time can be modelled using the approach based on autoregressive conditional heteroscedasticity (ARCH). However, the generalizations to multivariate series can be difficult to estimate and interpret. Another approach is to model variance as an unobserved stochastic process.
Harvey, Andrew +2 more
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MULTIFRACTIONAL STOCHASTIC VOLATILITY MODELS [PDF]
Mathematical Finance, 2013 The aim of this work is to advocate the use of multifractional Brownian motion (mBm) as a relevant model in financial mathematics. mBm is an extension of fractional Brownian motion where the Hurst parameter is allowed to vary in time. This enables the possibility to accommodate for varying local regularity, and to decouple it from long‐range dependence
Corlay, Sylvain +2 more
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Stochastic models of kleptoparasitism [PDF]
, 2007 In this paper, we consider a model of kleptoparasitism amongst a small group of individuals, where the state of the population is described by the distribution of its individuals over three specific types of behaviour (handling, searching for or fighting
Auger +28 more
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Stochastic neural network models for gene regulatory networks [PDF]
, 2003 Recent advances in gene-expression profiling technologies provide large amounts of gene expression data. This raises the possibility for a functional understanding of genome dynamics by means of mathematical modelling.
Burrage, K., Tian, T.
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Stochastic spatial models [PDF]
SIAM Review, 1999 The author considers a spatial model with the space represented as a grid of sites that can be in one of a finite number of states. The site changes its state with a rate that depends on states of a finite number of sites. Assuming that sites are independent, the behaviour of such models can be studied with the help of mean field ordinary differential ...
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The Annals of Probability, 1999 We study an ordinary differential equation controlled by a stochastic process. We present results on existence and uniqueness of solutions, on associated local times (Trotter and Ray-Knight theorems), and on time and direction of bifurcation. A relationship with Lipschitz approximations to Brownian paths is also discussed.
Burdzy, Krzysztof, Bass, Richard F.
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Stochastic Frontier Models [PDF]
, 2008 The stochastic frontier model was first proposed in the context of production function estimation to account for the effect of technical inefficiency. The inefficiency causes actual output to fall below the potential level (that is, the production frontier) and also raises production cost above the minimum level (that is, the cost frontier).
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Linear Stochastic Dividend Model [PDF]
SSRN Electronic Journal, 2019 In this paper, we propose a new model for pricing stock and dividend derivatives. We jointly specify dynamics for the stock price and the dividend rate such that the stock price is positive and the dividend rate nonnegative. In its simplest form, the model features a dividend rate that is mean-reverting around a constant fraction of the stock price ...
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