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Akademický článek

Maximum Likelihood Estimation for the Fractional Vasicek Model

Autor: Katsuto Tanaka, Weilin Xiao, Jun Yu

Publikováno v: Econometrics, Vol 8, Iss 3, p 32 (2020)

This paper estimates the drift parameters in the fractional Vasicek model from a continuous record of observations via maximum likelihood (ML). The asymptotic theory for the ML estimates (MLE) is established in the stationary case, the explosive case

Externí odkaz: https://doaj.org/article/87fea7a9fa204fda947faf88bac89554

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Akademický článek

Long-Memory Processes and Applications

Autor: Yiming Ding, Yaozhong Hu, Weilin Xiao, Litan Yan

Publikováno v: Abstract and Applied Analysis, Vol 2014 (2014)

Externí odkaz: https://doaj.org/article/8b4b26dfaeba49f2b891da47dca55762

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Exact maximum likelihood estimators for drift fractional Brownian motions

Autor: Yaozhong, Hu, Weilin, Xiao, Weiguo, Zhang

This paper deals with the problems of consistence and strong consistence of the maximum likelihood estimators of the mean and variance of the drift fractional Brownian motions observed at discrete time instants. A central limit theorem for these esti

Externí odkaz: http://arxiv.org/abs/0904.4186

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Modeling and forecasting realized volatility with the fractional Ornstein–Uhlenbeck process

Autor: Jun Yu, Xiaohu Wang, Weilin Xiao

Publikováno v: Journal of Econometrics. 232:389-415

This paper proposes to model and forecast realized volatility (RV) using the fractional Ornstein–Uhlenbeck (fO–U) process with a general Hurst parameter, H . A two-stage method is introduced for estimating parameters in the fO–U process based o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::afeac9c3c709d538b8e08f03fe1732f7
https://doi.org/10.1016/j.jeconom.2021.08.001

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