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Unified moment-based modelling of integrated stochastic processes

Kyriakou, I. ORCID: 0000-0001-9592-596X, Brignone, R. & Fusai, G. ORCID: 0000-0001-9215-2586 (2023). Unified moment-based modelling of integrated stochastic processes. Operations Research, doi: 10.1287/opre.2022.2422


In this paper we present a new method for simulating integrals of stochastic processes. We focus on the nontrivial case of time integrals, conditional on the state variable levels at the endpoints of a time interval, through a moment-based probability distribution construction. We present different classes of models with important uses in finance, medicine, epidemiology, climatology, bioeconomics and physics. The method is generally applicable in well-posed moment problem settings. We study its convergence, point out its advantages through a series of numerical experiments and compare its performance against existing schemes.

Publication Type: Article
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Publisher Keywords: Stochastic volatility; linear and nonlinear reducible models; Pearson curves; moments; simulation
Subjects: H Social Sciences > HF Commerce > HF5601 Accounting
H Social Sciences > HG Finance
Q Science > QA Mathematics
Departments: Bayes Business School > Actuarial Science & Insurance
Bayes Business School > Finance
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