Modelling and asset allocation for financial markets based on a stochastic volatility microstructure model

DOI10.1080/00207720500089408zbMath1092.91019OpenAlexW1995463878MaRDI QIDQ5460680

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Publication date: 18 July 2005

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207720500089408

zbMATH Keywords

parameter estimationKalman filtermaximum likelihooddynamic asset allocationmarket microstructurestochastic volatility modelstochastic difference equationsfinancial dynamicscomtinuous time microstructure model

Mathematics Subject Classification ID

Related Items (5)

Bayesian analysis of heavy-tailed market microstructure model and its application in stock markets ⋮ A fast and efficient Markov chain Monte Carlo method for market microstructure model ⋮ ICLUS: A robust and scalable clustering model for time series via independent component analysis ⋮ Modeling financial time series based on a market microstructure model with leverage effect ⋮ Modelling financial time series based on heavy-tailed market microstructure models with scale mixtures of normal distributions

Cites Work

• Estimating continuous-time stochastic volatility models of the short-term interest rate
• Local linearization method for the numerical solution of stochastic differential equations
• Simulation of stochastic differential equations through the local linearization method. A comparative study
• Stochastic processes and filtering theory
• A local linearization approach to nonlinear filtering
• Computing integrals involving the matrix exponential
• Approximation of continuous time stochastic processes by a local linearization method
• Likelihood Inference for Discretely Observed Nonlinear Diffusions
• A comparative study of maximum likelihood estimators for nonlinear dynamical system models

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