Parameter estimation in diffusion models with low regularity coefficients
Dmytro Ivanenko, Rostyslav Pogorielov
TL;DR
This paper develops methods for parameter estimation in diffusion models with low regularity coefficients, including software implementation and testing, to improve accuracy in stochastic differential equation models.
Contribution
It introduces new estimation techniques and software for models with low regularity coefficients, enhancing existing methods for stochastic differential equations.
Findings
Successful implementation of estimation software
Comparison showing improved accuracy
Validation through testing on models
Abstract
The article considers parameter estimation constructing such as quasi-maximum likelyhood estimation and one step estimation in statistical models generated by solution of stochastic differential equation. It has been developed a software for parameter estimating and has been presented correspondent testing and comparing.
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Taxonomy
TopicsStochastic processes and financial applications · Advanced Mathematical Modeling in Engineering · Stochastic processes and statistical mechanics