Estimating drift parameters in a non-ergodic Gaussian Vasicek-type model
Khalifa Es-Sebaiy () and
Mohammed Es.Sebaiy ()
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Khalifa Es-Sebaiy: Kuwait University
Mohammed Es.Sebaiy: Cadi Ayyad University
Statistical Methods & Applications, 2021, vol. 30, issue 2, No 2, 409-436
Abstract:
Abstract We study a problem of parameter estimation for a non-ergodic Gaussian Vasicek-type model defined as $$dX_t=\theta (\mu + X_t)dt+dG_t,\ t\ge 0$$ d X t = θ ( μ + X t ) d t + d G t , t ≥ 0 with unknown parameters $$\theta >0$$ θ > 0 , $$\mu \in {\mathbb {R}}$$ μ ∈ R and $$\alpha :=\theta \mu $$ α : = θ μ , where G is a Gaussian process. We provide least square-type estimators $$(\widetilde{\theta }_T,\widetilde{\mu }_T)$$ ( θ ~ T , μ ~ T ) and $$(\widetilde{\theta }_T,\widetilde{\alpha }_T)$$ ( θ ~ T , α ~ T ) , respectively, for $$(\theta ,\mu )$$ ( θ , μ ) and $$(\theta ,\alpha )$$ ( θ , α ) based a continuous-time observation of $$\{X_t,\ t\in [0,T]\}$$ { X t , t ∈ [ 0 , T ] } as $$T\rightarrow \infty $$ T → ∞ . Our aim is to derive some sufficient conditions on the driving Gaussian process G in order to ensure the strongly consistency and the joint asymptotic distribution of $$(\widetilde{\theta }_T,\widetilde{\mu }_T)$$ ( θ ~ T , μ ~ T ) and $$(\widetilde{\theta }_T,\widetilde{\alpha }_T)$$ ( θ ~ T , α ~ T ) . Moreover, we obtain that the limit distribution of $$\widetilde{\theta }_T$$ θ ~ T is a Cauchy-type distribution, and $$\widetilde{\mu }_T$$ μ ~ T and $$\widetilde{\alpha }_T$$ α ~ T are asymptotically normal. We apply our result to fractional Vasicek, subfractional Vasicek and bifractional Vasicek processes. This work extends the results of El Machkouri et al. (J Korean Stat Soc 45:329–341, 2016) studied in the case where $$\mu =0$$ μ = 0 .
Keywords: Gaussian Vasicek-type model; Parameter estimation; Strong consistency; Joint asymptotic distribution; Fractional Gaussian processes; Young integral (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:spr:stmapp:v:30:y:2021:i:2:d:10.1007_s10260-020-00528-4
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DOI: 10.1007/s10260-020-00528-4
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