JOURNAL ARTICLE

Fractional iterated Ornstein-Uhlenbeck Processes

Juan KalemkerianJosé R. León

Year: 2019 Journal:   Latin American Journal of Probability and Mathematical Statistics Vol: 16 (2)Pages: 1105-1105

Abstract

We present a Gaussian process that arises from the iteration of p fractional Ornstein-Uhlenbeck processes generated by the same fractional Brownian motion.When the values of the parameters defining the iteration are pairwise distinct, this iteration results in a particular linear combination of those processes.Although for H > 1/2 each term of the iteration is a long memory process, we prove that when p ≥ 2 the process obtained has short memory.We prove that the local Hölder index of the process is H, and obtain an explicit formula for the spectral density.We present a way to estimate the parameters and prove that the estimators are consistent and the results are asymptotically Gaussian.These processes can be used to model time series of long or short memory.

Keywords:
Ornstein–Uhlenbeck process Fractional Brownian motion Iterated function Pairwise comparison Gaussian process Mathematics Applied mathematics Gaussian Process (computing) Long memory Statistical physics Computer science Brownian motion Stochastic process Statistics Mathematical analysis Econometrics Physics

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5
Cited By
2.52
FWCI (Field Weighted Citation Impact)
6
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0.91
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Citation History

Topics

Complex Systems and Time Series Analysis
Social Sciences →  Economics, Econometrics and Finance →  Economics and Econometrics
Financial Risk and Volatility Modeling
Social Sciences →  Economics, Econometrics and Finance →  Finance
Stochastic processes and financial applications
Social Sciences →  Economics, Econometrics and Finance →  Finance

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