Stochastic differential equations for orthogonal eigenvectors of (G,ε)-Wishart process related to multivariate G-fractional Brownian motion
Abstract
In the present paper, we introduce a new process called multivariate G-fractional Brownian motion (B_{t}^{H}) where the Hurst parameter H is a diagonal matrix. Moreover, we give an approximation (R_{t}^{ε}) of Riemann-Liouville process of (B_{t}^{H}) by G-Itô's processes. Then we give stochastic differential equations for orthogonal eigenvectors of (G,ε)-Wishart fractional process defined by R_{t}^{ε}(R_{t}^{ε})^{∗}, which has 0 and |R_{t}^{ε}|² as eigenvalues. An intermediate asymptotic comparison result concerning the eigenvalue |R_{t}^{ε}|² is also obtained
Downloads
References
Alos E, Mazet O, Nualart D. Stochastic calculus with respect to fractional Brownian motion with Hurst parameter lesser than 1 2 , Stochastic Processes and their applications, 86 (1) 121 − 139 (2000). https://doi.org/10.1016/S0304-4149(99)00089-7 DOI: https://doi.org/10.1016/S0304-4149(99)00089-7
Amblard P, Coeurjolly J, Lavancier F, Philippe A. Basic properties of the Multivariate Fractional Brownian Motion. S'eminaires et congr'es, Soci'et'e math'ematique de France 2865 − 87 (2013).
Achard S, Gannaz I. Multivariate wavelet Whittle estimation in long-range dependence. Journal of Time Series Analysis, Wiley-Blackwell, 37 (4) 476 − 512 (2016). https://doi.org/10.1111/jtsa.12170 DOI: https://doi.org/10.1111/jtsa.12170
Boutabia H, Grabsia I. Chaotic expansion in the G−expectation space. Opuscula Mathematica 33(4)647 − 666 (2013). https://doi.org/10.7494/OpMath.2013.33.4.647 DOI: https://doi.org/10.7494/OpMath.2013.33.4.647
Chen W. Fractional G−White Noise Theory, Wavelet Decomposition for Frac- tional G−Brownian Motion and Bid-Ask Pricing for European Contingent Claim Under Uncertainty, Preprint arXiv:1306.4070v1 [math:PR] (2013).
Bru MF.Diffusions of perturbed principal component analysis. Journal of Multivariate Analysis 29127 − 136 (1998).
Dunga NT, Thao TH. An approximate approach to fractional stochastic integration and its applications. Brazilian Statistical Association 24 (1) 57 − 67. (2010) https://doi.org/10.1214/08-BJPS013 DOI: https://doi.org/10.1214/08-BJPS013
Denis L, Hu M, Peng S. Function spaces and capacity related to a sublinear expectation application to G−Brownian motion paths. Potential Analysis. 34 (1) 139 − 161. https://doi.org/10.1007/s11118-010-9185-x DOI: https://doi.org/10.1007/s11118-010-9185-x
Didier G, Pipiras V. Integral representations of operator fractional Brownian motion. Bernoulli 17 (1) : 1 − 33. (2010) https://doi.org/10.3150/10-BEJ259 DOI: https://doi.org/10.3150/10-BEJ259
Gao F. Pathwise properties and homomorphic flows for stochastic differential equations driven by G−Brownian motion. Stochastic Processes and their Applications . 119 (10) 3356 − 3382 (2009) . https://doi.org/10.1016/j.spa.2009.05.010 DOI: https://doi.org/10.1016/j.spa.2009.05.010
Hu Y, Øksendal B. Fractional white noise calculus and applications to finance. Infinite Dimensional Analysis. Quantum Probability and Related Topics 6 (1) 1 − 32 (2003). https://doi.org/10.1142/S0219025703001110 DOI: https://doi.org/10.1142/S0219025703001110
Boutabia H, Meradj Si, Stihi S. Stochastic differential equations for eigenvalues and eigenvectors of a G−Wishart process with drift. Ukrainian Mathematical Journal 71 (4) 502 − 515 (2019). https://doi.org/10.1007/s11253-019-01664-1 DOI: https://doi.org/10.1007/s11253-019-01664-1
Majumdar SN. Handbook of Random Matrix Theory. Oxford University Press: (2011).
Mandelbrot B, Van Ness J. Fractional Brownian motions, fractional noises and applications. Society for Industrial and Applied Mathematics Review. 10 (4) 422 − 437 (1968). https://doi.org/10.1137/1010093 DOI: https://doi.org/10.1137/1010093
Peng S. Multi-dimensional G−Brownian motion and related stochastic calculus under G−expectation, Stochastic Processes and their Applications 118 (12) 2223 − 2253 (2008). https://doi.org/10.1016/j.spa.2007.10.015 DOI: https://doi.org/10.1016/j.spa.2007.10.015
Peng S. G−Brownian Motion and Dynamic Risk Measure under Volatility Uncertainty; arXiv 0711.2834v1 [math.PR] (2007).
Peng S. G−expectation, G−Brownian motion and related stochastic calculus of Itˆo type. Stochastic Analysis and Application, Abel Symposia 2541 − 567 (2007). https://doi.org/10.1007/978-3-540-70847-6 DOI: https://doi.org/10.1007/978-3-540-70847-6_25
Stihi S, Boutabia H, Meradji S. Stochastic diferential equations for Random matrices processes in the nonlinear framework, Opuscula Mathematica 38 (2) 261 − 283 (2018). https://doi.org/10.7494/OpMath.2018.38.2.261 DOI: https://doi.org/10.7494/OpMath.2018.38.2.261
Yue J, Huang NJ. Fractional Wishart Processes and ε−Fractional Wishart Processes with Applications. Computers and Mathematics with Applications 75 (8) 2955 − 2977 (2018). https://doi.org/10.1016/j.camwa.2018.01.024 DOI: https://doi.org/10.1016/j.camwa.2018.01.024
Copyright (c) 2022 Boletim da Sociedade Paranaense de Matemática

This work is licensed under a Creative Commons Attribution 4.0 International License.
When the manuscript is accepted for publication, the authors agree automatically to transfer the copyright to the (SPM).
The journal utilize the Creative Common Attribution (CC-BY 4.0).