Prediction formulas for integrated fractional Brownian motion
DOI:
https://doi.org/10.17721/1812-5409.2025/2.3Keywords:
fractional Brownian motion, integrated fractional Brownian motion, covariance function, projection problem, projection coefficientsAbstract
This paper investigates the projection (prediction) of increments of the integrated fractional Brownian motion (ifBm). We introduce ifBm, calculate its covariance function, and establish the stationarity of its increments. Our primary goal is to determine the coefficients for the linear prediction of a future ifBm increment based on a series of past increments. We show that the prediction coefficients exhibit complex behavior, with their signs changing depending on the Hurst index (H). For overlapping increments, this sign change occurs at a non-trivial values of H. In contrast, for non-overlapping increments, the sign change happens at H=0.5, consistent with the properties of fractional Brownian motion itself. This work provides explicit formulas where possible and extensive numerical tables, offering insights into the properties and predictability of ifBm, laying the groundwork for further research.
Pages of the article in the issue: 19 - 30
Language of the article: English
References
Abundo, M., & Pirozzi, E. (2018). Integrated stationary ornstein–uhlenbeck process, and double integral processes. Physica A: Statistical Mechanics and Its Applications, 494, 265–275. https://doi.org/10.1016/j.physa.2017.12.043
Abundo, M., & Pirozzi, E. (2019). On the integral of the fractional brownian motion and some pseudo-fractional gaussian processes. Mathematics, 7(10), 991. https://doi.org/10.3390/math7100991
Alòs, E., Mazet, O., & Nualart, D. (2001). Stochastic calculus with respect to gaussian processes. The Annals of Probability, 29(2), 766–801. https://doi.org/10.1214/aop/1008956692
Alòs, E., & Nualart, D. (2003). Stochastic integration with respect to the fractional Brownian motion. Stochastics and Stochastics Reports, 75(3), 129–152. https://doi.org/10.1080/1045112031000078917
Anh, V. V., & Inoue, A. (2004). Prediction of fractional Brownian motion with Hurst index less than 1/2. Bulletin of the Australian Mathematical Society, 70(2), 321–328. https://doi.org/10.1017/S0004972700034535
Banna, O., Mishura, Y., Ralchenko, K., & Shklyar, S. (2019). Fractional brownian motion: Approximations and projections. ISTE Ltd and John Wiley & Sons Inc. https://doi.org/10.1002/9781119476771
Barton, R. J., & Vincent Poor, H. (1988). Signal detection in fractional Gaussian noise. IEEE Transactions on Information Theory, 34(5), 943–959. https://doi.org/10.1109/18.21218
Bender, C. (2003a). An Itô formula for generalized functionals of a fractional Brownian motion with arbitrary Hurst parameter. Stochastic Processes and their Applications, 104(1), 81–106. https://doi.org/10.1016/S0304-4149(02)00212-0
Bender, C. (2003b). An S-transform approach to integration with respect to a fractional Brownian motion. Bernoulli, 9(6), 955–983. https://doi.org/10.3150/bj/1072215197
Bender, C., & Elliott, R. J. (2004). Arbitrage in a discrete version of the Wick-fractional Black-Scholes market. Mathematics of Operations Research, 29(4), 935–945. https://doi.org/10.1287/moor.1040.0096
Bender, C., Sottinen, T., & Valkeila, E. (2008). No-arbitrage Pricing Beyond Semimartingales. Finance and Stochastics, 12(4), 441–468. https://doi.org/10.1007/s00780-008-0074-8
Benth, F. E. (2003). On arbitrage-free pricing of weather derivatives based on fractional Brownian motion. Applied Mathematical Finance, 10(4), 303–324. https://doi.org/10.1080/1350486032000174628
Beran, J. (1994). Statistics for Long-memory Processes. Chapman & Hall. https://doi.org/10.1201/9780203738481
Biagini, F., Hu, Y., Øksendal, B., & Sulem, A. (2002). A stochastic maximum principle for processes driven by a fractional Brownian motion. Stochastic Processes and their Applications, 100(1-2), 233–253. https://doi.org/10.1016/S0304-4149(02)00105-9
Biagini, F., Hu, Y., Øksendal, B., & Zhang, T. (2008). Stochastic calculus for fractional brownian motion and applications. Springer. https://doi.org/10.1007/978-1-84628-797-8
Bodnarchuk, I., & Mishura, Y. (2024). Combinatorial approach to the calculation of projection coefficients for the simplest gaussian-volterra process. Modern Stochastics: Theory and Applications, 11(4), 403–419. https://doi.org/10.15559/24-VMSTA252
Boufoussi, B., & Ouknine, Y. (2003). On a SDE driven by a fractional Brownian motion and with monotone drift. Electronic Communications in Probability, 8, 122–134. https://doi.org/10.1214/ECP.v8-1084
Carmona, P., & Coutin, L. (1998). Fractional Brownian motion and the Markov property. Electronic Communications in Probability, 3, 95–107. https://doi.org/10.1214/ECP.v3-998
Carmona, P., Coutin, L., & Montseny, G. (2003). Stochastic integration with respect to fractional Brownian motion. Annales de l’Institut Henri Poincaré, Probabilités et Statistiques, 39(1), 27–68. https://doi.org/10.1016/S0246-0203(02)01111-1
Cheridito, P. (2001). Mixed fractional Brownian motion. Bernoulli, 7(6), 913–934. https://doi.org/10.2307/3318626
Cheridito, P., Kawaguchi, H., & Maejima, M. (2003). Fractional Ornstein–Uhlenbeck processes. Electronic Journal of Probability, 8, 1–14. https://doi.org/10.1214/EJP.v8-125
Cheridito, P., & Nualart, D. (2005). Stochastic integral of divergence type with respect to the fractional Brownian motion with Hurst parameter H ∈ (0, 1/2). Annales de l’Institut Henri Poincaré, Probabilités et Statistiques, 41(6), 1049–1081. https://doi.org/10.1016/j.anihpb.2004.09.004
Cioczek-Georges, R., & Mandelbrot, B. B. (1995). A class of micropulses and antipersistent fractional Brownian motion. Stochastic Processes and their Applications, 60(1), 1–18. https://doi.org/10.1016/0304-4149(95)00046-1
Corcuera, J. M., Nualart, D., & Woerner, J. H. C. (2006). Power variation of some integral long-memory processes. Bernoulli, 12(4), 713–735. https://doi.org/10.3150/bj/1155735933
Coutin, L., & Decreusefond, L. (1999). Abstract nonlinear filtering theory in the presence of fractional Brownian motion. The Annals of Applied Probability, 9(4), 1058–1090. https://doi.org/10.1214/aoap/1029962865
Coutin, L., Nualart, D., & Tudor, C. A. (2001). Tanaka formula for the fractional Brownian motion. Stochastic Processes and their Applications, 94(2), 301–315. https://doi.org/10.1016/S0304-4149(01)00085-0
Dai, W., & Heyde, C. C. (1996). Itô’s formula with respect to fractional Brownian motion and its application. Journal of Applied Mathematics and Stochastic Analysis, 9(4), 439–448. https://doi.org/10.1155/S104895339600038X
Decreusefond, L., & Üstünel, A. S. (1998). Fractional Brownian motion: Theory and applications. ESAIM: Proceedings, 5, 75–86. https://doi.org/10.1051/proc:1998014
Decreusefond, L., & Üstünel, A. S. (1999). Stochastic analysis of the fractional brownian motion. Potential Analysis, 10, 177–214. https://doi.org/10.1023/A:1008634027843
Duncan, T. E. (2001). Some aspects of fractional Brownian motion. Nonlinear Analysis: Theory, Methods & Applications, 47(7), 4775–4782. https://doi.org/10.1016/S0362-546X(01)00589-2
Duncan, T. E., Pasik-Duncan, B., & Maslowski, B. (2002). Fractional Brownian motion and stochastic equations in Hilbert spaces. Stochastics and Dynamics, 2(2), 225–250. https://doi.org/10.1142/S0219493702000340
Dzhaparidze, K., & van Zanten, H. (2004). A series expansion of fractional Brownian motion. Probability Theory and Related Fields, 130(1), 39–55. https://doi.org/10.1007/s00440-003-0310-2
Dzhaparidze, K., & van Zanten, H. (2005). Krein’s spectral theory and the Paley-Wiener expansion for fractional Brownian motion. The Annals of Probability, 33(2), 620–644. https://doi.org/10.1214/009117904000000955
Jost, C. (2006). Transformation formulas for fractional Brownian motion. Stochastic Processes and their Applications, 116(8), 1341–1357. https://doi.org/10.1016/j.spa.2006.02.006
Malyarenko, A., Mishura, Y., Ralchenko, K., & Shklyar, S. (2023). Entropy and alternative entropy functionals of fractional gaussian noise as the functions of hurst index. Fractional Calculus and Applied Analysis, 26, 1052–1081. https://doi.org/10.1007/s13540-023-00155-2
Mandelbrot, B. B., & Van Ness, J. W. (1968). Fractional brownian motions, fractional noises and applications. SIAM Review, 10(4), 422–437. https://doi.org/10.1137/1010093
Mishura, Y., Ralchenko, K., & Shklyar, S. (2020). General Conditions of Weak Convergence of Discrete-Time Multiplicative Scheme to Asset Price with Memory. Risks, 8(1), 11. https://doi.org/10.3390/risks8010011
Norros, I., Valkeila, E., & Virtamo, J. (1999). An Elementary Approach to a Girsanov Formula and Other Analytical Results on Fractional Brownian Motions. Bernoulli, 5(4), 571–587. https://doi.org/10.2307/3318691
Nourdin, I. (2012). Selected Aspects of Fractional Brownian Motion. Springer. https://doi.org/10.1007/978-88-470-2823-4
Novikov, A., & Valkeila, E. (1999). On Some Maximal Inequalities for Fractional Brownian Motions. Statistics & Probability Letters, 44(1), 47–54. https://doi.org/10.1016/S0167-7152(98)00290-9
Nualart, D. (2003). Stochastic integration with respect to fractional Brownian motion and applications. Contemporary Mathematics, 336, 3–40.
Nualart, D., & Ouknine, Y. (2003). Stochastic differential equations with additive fractional noise and locally unbounded drift. In Giné, Houdré, & Nualart (Eds.), Stochastic Inequalities and Applications (Vol. 56, pp. 353–365). Birkhäuser. https://doi.org/10.1007/978-3-0348-8069-5_20
Pipiras, V., & Taqqu, M. S. (2017). Long-Range Dependence and Self-Similarity. Cambridge University Press. https://doi.org/10.1017/CBO9781139600347
Samorodnitsky, G. (2016). Stochastic processes and long range dependence. Springer Cham.https://doi.org/10.1007/978-3-319-45575-4
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Yevhenii Bundiuk, Yuliya Mishura, Enrica Pirozzi

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
