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Journal of Statistical Computation and Simulation Volume 85, 2015 - Issue 2
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Original Articles

Parameter identification for the discretely observed geometric fractional Brownian motion

Weilin XiaoSchool of Management, Zhejiang University, Hangzhou, People's Republic of China
,
Weiguo ZhangSchool of Business Administration, South China University of Technology, Guangzhou, People's Republic of China
&
Xili ZhangSchool of Management, Zhejiang University, Hangzhou, People's Republic of ChinaCorrespondence[email protected]
Pages 269-283 | Received 12 Mar 2013, Accepted 07 Jun 2013, Published online: 29 Jul 2013

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Yun Xiang & Shijie Deng. (2024) Optimal stop-loss rules in markets with long-range dependence. Quantitative Finance 24:2, pages 253-263.
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Luca Vincenzo Ballestra, Andrea Molent & Graziella Pacelli. (2022) Investigating long and short memory in cryptocurrency time series by stochastic fractional Brownian models. Communications in Statistics - Simulation and Computation 0:0, pages 1-11.
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Josephine Dufitinema, Seppo Pynnönen & Tommi Sottinen. (2022) Maximum likelihood estimators from discrete data modeled by mixed fractional Brownian motion with application to the Nordic stock markets. Communications in Statistics - Simulation and Computation 51:9, pages 5264-5287.
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David Stibůrek. (2017) Statistical inference on the drift parameter in fractional Brownian motion with a deterministic drift. Communications in Statistics - Theory and Methods 46:2, pages 892-905.
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Articles from other publishers (10)

Lin Sun, Jianxin Chen & Xianggang Lu. (2022) Parameter estimation for discretized geometric fractional Brownian motions with applications in Chinese financial markets. Advances in Continuous and Discrete Models 2022:1.
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Mohammed Alhagyan. (2022) The effects of incorporating memory and stochastic volatility into GBM to forecast exchange rates of Euro. Alexandria Engineering Journal 61:12, pages 9601-9608.
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John-Fritz Thony & Jean Vaillant. (2022) Parameter Estimation for a Fractional Black–Scholes Model with Jumps from Discrete Time Observations. Mathematics 10:22, pages 4190.
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Siti Nur Iqmal Ibrahim, Masnita Misiran & Mohamed Faris Laham. (2021) Geometric fractional Brownian motion model for commodity market simulation. Alexandria Engineering Journal 60:1, pages 955-962.
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Ananya Lahiri & Rituparna Sen. (2020) Fractional Brownian markets with time-varying volatility and high-frequency data. Econometrics and Statistics 16, pages 91-107.
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Zhaoqiang Yang. (2020) Default probability of American lookback option in a mixed jump-diffusion model. Physica A: Statistical Mechanics and its Applications 540, pages 123242.
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Chunhao Cai, Xuwen Cheng, Weilin Xiao & Xiang Wu. (2019) Parameter identification for mixed fractional Brownian motions with the drift parameter. Physica A: Statistical Mechanics and its Applications 536, pages 120942.
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Qiang Liu, Yun Xiang & Yonghong Zhao. (2019) An outperforming investment strategy under fractional Brownian motion. The North American Journal of Economics and Finance 47, pages 505-515.
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Lin Sun, Lin Wang & Pei Fu. (2018) Maximum likelihood estimators of a long-memory process from discrete observations. Advances in Difference Equations 2018:1.
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David Stibůrek. (2016) Sequential testing of hypotheses about drift for Gaussian diffusions. Statistical Methodology 33, pages 14-30.
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