Shrinkage drift parameter estimation for multi‐factor Ornstein–Uhlenbeck processes

DOI10.1002/asmb.775zbMath1224.91173OpenAlexW4239609925MaRDI QIDQ5391297

Sévérien Nkurunziza, S. Ejaz Ahmed

Publication date: 6 April 2011

Published in: Applied Stochastic Models in Business and Industry (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/asmb.775

zbMATH Keywords

maximum likelihood estimatorVasicek processmulti-factor Ornstein-Uhlenbeck processesshrinkage drift parameter estimation

Mathematics Subject Classification ID

Statistical methods; risk measures (91G70) Markov processes: estimation; hidden Markov models (62M05) Interest rates, asset pricing, etc. (stochastic models) (91G30)

Related Items (12)

\(L^2\)-tracking of Gaussian distributions via model predictive control for the Fokker-Planck equation ⋮ The risk of tensor Stein-rules in elliptically contoured distributions ⋮ Preliminary test and estimation in some multifactor diffusion processes ⋮ Extension of some important identities in shrinkage-pretest strategies ⋮ Optimal method in multiple regression with structural changes ⋮ Shrinkage strategy in stratified random sample subject to measurement error ⋮ Estimation and testing in multivariate generalized Ornstein-Uhlenbeck processes with change-points ⋮ Inference in a multivariate generalized mean-reverting process with a change-point ⋮ Estimation and testing in generalized mean-reverting processes with change-point ⋮ Robust inference strategy in the presence of measurement error ⋮ A class of Stein-rules in multivariate regression model with structural changes ⋮ Shrinkage Estimation of the Memory Parameter in Stationary Gaussian Processes

Cites Work

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• Prediction of predator-prey populations modelled by perturbed ODEs
• Estimation of the coefficients of a diffusion from discrete observations
• Approximate discrete-time schemes for statistics of diffusion processes
• Stochastic Volatility With an Ornstein–Uhlenbeck Process: An Extension
• An equilibrium characterization of the term structure
• Notes on the distribution of quadratic forms in singular normal variables

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