A class of fractional Ornstein–Uhlenbeck processes mixed with a Gamma distribution        
        
    
        Volume 10, Issue 1 (2023), pp. 37–57
            
    
                    Pub. online: 21 November 2022
                    
        Type: Research Article
            
                
             Open Access
Open Access
        
            
    
                Received
14 October 2021
                                    14 October 2021
                Revised
7 November 2022
                                    7 November 2022
                Accepted
7 November 2022
                                    7 November 2022
                Published
21 November 2022
                    21 November 2022
Abstract
We consider a sequence of fractional Ornstein–Uhlenbeck processes, that are defined as solutions of a family of stochastic Volterra equations with a kernel given by the Riesz derivative kernel, and leading coefficients given by a sequence of independent Gamma random variables. We construct a new process by taking the empirical mean of this sequence. In our framework, the processes involved are not Markovian, hence the analysis of their asymptotic behaviour requires some ad hoc construction. In our main result, we prove the almost sure convergence in the space of trajectories of the empirical means to a given Gaussian process, which we characterize completely.
            References
 Baldi, P.: Stochastic Calculus: An Introduction Through Theory and Exercises. Universitext. Springer, Cham (2017). MR3726894. https://doi.org/10.1007/978-3-319-62226-2
 Barndorff-Nielsen, O.E., Schmiegel, J.: Brownian semistationary processes and volatility/intermittency. In: Advanced Financial Modelling, pp. 1–26. De Gruyter (2009). MR2648456. https://doi.org/10.1515/9783110213140.1
 Barndorff-Nielsen, O.E., Schmiegel, J.: Ambit Processes; with Applications to Turbulence and Tumour Growth. In: Benth, F.E., Di Nunno, G., Lindstrøm, T., Øksendal, B., Zhang, T. (eds.) Stochastic Analysis and Applications. Abel Symposia, pp. 93–124. Springer, Berlin, Heidelberg (2007). MR2397785. https://doi.org/10.1007/978-3-540-70847-6_5
 Barndorff-Nielsen, O.E., Benth, F.E., Veraart, A.E.D.: Ambit Processes and Stochastic Partial Differential Equations. In: Di Nunno, G., Øksendal, B. (eds.) Advanced Mathematical Methods for Finance, pp. 35–74. Springer, Berlin, Heidelberg (2011). MR2752540. https://doi.org/10.1007/978-3-642-18412-3_2
 Billingsley, P.: Convergence of Probability Measures, 1st edn. John Wiley & Sons, Inc., New York-London-Sydney (1968). MR0233396
 Bonaccorsi, S., Tubaro, L.: Mittag-Leffler’s Function and Stochastic Linear Volterra Equations of Convolution Type. Stoch. Anal. Appl. 21(1), 61–78 (2003). MR1954075. https://doi.org/10.1081/SAP-120017532
 Clément, P., Da Prato, G.: Some results on stochastic convolutions arising in Volterra equations perturbed by noise. Atti Accad. Naz. Lincei, Rend. Lincei, Mat. Appl. 7(3), 147–153 (1996) MR1454409
 Douissi, S., Es-Sebaiy, K., Tudor, C.A.: Hermite Ornstein–Uhlenbeck processes mixed with a Gamma distribution. Publ. Math. (Debr.) 96(1-2), 23–44 (2020). MR4062581. https://doi.org/10.5486/pmd.2020.8443
 Erdélyi, A., Magnus, W., Oberhettinger, F., Tricomi, F.: Higher Trascendental Functions vol. III. McGraw-Hill, New York (1955) MR0717723
 Es-Sebaiy, K., Tudor, C.A.: Fractional Ornstein-Uhlenbeck Processes Mixed with a Gamma Distribution. Fractals 23(03), 1550032 (2015). MR3375690. https://doi.org/10.1142/S0218348X15500322
 Es-Sebaiy, K., Farah, F.-E., Hilbert, A.: Weyl multifractional Ornstein–Uhlenbeck processes mixed with a Gamma distribution. Probab. Math. Stat. 40(2), 269–295 (2020). MR4206415. https://doi.org/10.37190/0208-4147.40.2.5
 Gorenflo, R., Kilbas, A.A., Mainardi, F., Rogosin, S.: Mittag-Leffler Functions, Related Topics and Applications. Springer Monographs in Mathematics. Springer, Berlin, Heidelberg (2020). MR4179587. https://doi.org/10.1007/978-3-662-61550-8
 Igloi, E., Terdik, G.: Long-range Dependence trough Gamma-mixed Ornstein-Uhlenbeck Process. Electron. J. Probab. 4 (1999). MR1713649. https://doi.org/10.1214/EJP.v4-53
 Luchko, Y.: The Wright function and its applications. In: Kochubei, A., Luchko, Y. (eds.) Basic Theory, pp. 241–268. De Gruyter (2019). MR3888404
 Mittag-Leffler, G.: Sur la représentation analytique d’une branche uniforme d’une fonction monogène: Cinquième note. Acta Math. 29, 101–181 (1905). MR1555012. https://doi.org/10.1007/BF02403200
 Newey, W.K., McFadden, D.: Large Sample Estimation and Hypothesis Testing. In: Engle, R.F., McFadden, D. (eds.) Handbook of Econometics vol. IV, pp. 2111–2245. Elsevier science B.V. (1994) MR1315971
 Popov, A.Y., Sedletskii, A.M.: Distribution of roots of Mittag-Leffler functions. J. Math. Sci. 190(2), 209–409 (2013). MR2883249. https://doi.org/10.1007/s10958-013-1255-3
 Riesz, M.: L’Intégrale de Riemann-Liouville et le probléme de Cauchy. Acta Math. 81, 222 (1949) MR0030102. https://doi.org/10.1007/BF02395016
 Tricomi, F., Erdélyi, A.: The asymptotic expansion of a ratio of gamma functions. Pac. J. Math. 1(1), 133–142 (1951). MR0043948. https://doi.org/10.2140/pjm.1951.1.133
 
                 
            