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General Transfer Formula for Stochastic Integral with Respect to Multifractional Brownian Motion

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Abstract

In this work we show how results from stochastic integration with respect to multifractional Brownian motion (mBm) can be simply deduced from results of stochastic integration with respect to fractional Brownian motion (fBm), by using a “Transfer Principle”. To illustrate this fact, we prove an Itô formula for integral with respect to mBm by deriving it from Itô formula for integral with respect to fBm, of any Hurst index H in (0, 1).

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Notes

  1. The fBm is said to be normalized when \(\gamma _{H}=1\).

  2. see e.g. [15, Lemma 2.6]

  3. One can replace Z(0, H) by 0 in order to eliminate the singularity at \(t=0\), when \(2\,H-1\le 0\).

References

  1. Alòs, E., Mazet, O., Nualart, D.: Stochastic calculus with respect to Gaussian processes. Ann. Probab. 29(2), 766–801 (2001)

    Article  MathSciNet  Google Scholar 

  2. Ayache, A., Taqqu, M.S.: Multifractional processes with random exponent. Publ. Mat. 49(2), 459–486 (2005)

    Article  MathSciNet  Google Scholar 

  3. Benassi, A., Jaffard, S., Roux, D.: Elliptic Gaussian random processes. Rev. Mat. Iberoam. 13(1), 19–90 (1997)

    Article  MathSciNet  Google Scholar 

  4. Bender, C.: An Itô formula for generalized functionals of a fractional Brownian motion with arbitrary Hurst parameter. Stoch. Process. Appl. 104, 81–106 (2003)

    Article  Google Scholar 

  5. Bender, C.: An \(S\)-transform approach to integration with respect to a fractional Brownian motion. Bernoulli 9(6), 955–983 (2003)

    Article  MathSciNet  Google Scholar 

  6. Elliott, R., Van der Hoek, J.: A general fractional white noise theory and applications to finance. Math. Finance 13(2), 301–330 (2003)

    Article  MathSciNet  Google Scholar 

  7. Hille, E., Phillips, R.: Functional Analysis and Semi-Groups, volume 31. American Mathematical Society (1957)

  8. Holden, H., Oksendal, B., Ubøe, J., Zhang, T.: Stochastic Partial Differential Equations. A Modeling White Noise Functional Approach, 2nd edn. Springer, Berlin (2010)

    Book  Google Scholar 

  9. Hu, Y.-Z., Yan, J.-A.: Wick calculus for nonlinear Gaussian functionals. Acta Math. Appl. Sin. Engl. Ser. 25(3), 399–414 (2009)

    Article  MathSciNet  Google Scholar 

  10. Janson, S.: Gaussian Hilbert Spaces. Cambridge Tracts in Mathematics, vol. 129. Cambridge University Press, Cambridge (1997)

    Book  Google Scholar 

  11. Kuo, H.: White Noise Distribution Theory. CRC-Press, Boca Raton (1996)

    Google Scholar 

  12. Lebovits, J.: From stochastic integral w.r.t. fractional Brownian motion to stochastic integral w.r.t. multifractional Brownian motion. Ann. Univ. Buchar. Math. Ser. 4(LXII)(1), 397–413 (2013)

    MathSciNet  Google Scholar 

  13. Lebovits, J.: Stochastic calculus with respect to Gaussian processes. Potential Anal. 50(1), 1–42 (2019)

    Article  MathSciNet  Google Scholar 

  14. Lebovits, J.: Local Times of Gaussian Processes. (2020). Preprint http://adsabs.harvard.edu/abs/2017arXiv170305006L

  15. Lebovits, J., Lévy Véhel, J.: White noise-based stochastic calculus with respect to multifractional Brownian motion. Stochastics 86(1), 87–124 (2014)

    Article  MathSciNet  Google Scholar 

  16. Lebovits, J., Lévy Véhel, J., Herbin, E.: Stochastic integration with respect to multifractional Brownian motion via tangent fractional Brownian motions. Stochastic Process. Appl. 124(1), 678–708 (2014)

    Article  MathSciNet  Google Scholar 

  17. Lei, P., Nualart, D.: Stochastic calculus for Gaussian processes and application to hitting times. Commun. Stoch. Anal. 6(3), 379–402 (2012)

    MathSciNet  Google Scholar 

  18. Peltier, R., Lévy Véhel, J.: Multifractional Brownian motion definition and preliminary results, (1995). rapport de recherche de l’INRIA no. 2645

  19. Stoev, S., Taqqu, M.: How rich is the class of multifractional Brownian motions? Stoch. Process. Appl. 116, 200–221 (2006)

    Article  MathSciNet  Google Scholar 

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Correspondence to Joachim Lebovits.

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Appendix: Background on the Bochner integral

Appendix: Background on the Bochner integral

In order not to weigh down this statement we will only give the necessary tools to proceed. On can refer to [11, p. 247] as well as to [7] for more details about Bochner integral.

Definition 2

(Bochner integral [11], p. 247) Let I be a Borel subset of [0, 1] and \(\Phi :={(\Phi _t)}_{t\in I}\) be an \({({\mathcal {S}})}^*\)-valued process verifying:

  1. (i)

    the process \(\Phi \) is weakly measurable on I i.e. the map \(t \mapsto<-0.2\,cm<-0.1\,cm \Phi _t,\varphi \ -0.1\,cm>-0.2\,cm>\) is measurable on I, for every \(\varphi \) in \(({\mathcal {S}})\).

  2. (ii)

    there exists \(p \in {\textbf{N}}\) such that \(\Phi _t \in ({{\mathcal {S}}}_{-p})\) for almost every \(t \in I\) and \(t \mapsto {\Vert \Phi _t\Vert }_{-p}\) belongs to \(L^1(I)\).

Then there exists an unique element in \({({\mathcal {S}})}^{*}\), noted \(\int _{I} \Phi _{u} \ du \), called the Bochner integral of \(\Phi \) on I such that, for all \(\varphi \) in \(({\mathcal {S}})\),

$$\begin{aligned} {<< \ \int _{I} \Phi _u \ du,\varphi \ >>} = \int _{I}<< \ \Phi _{u},\varphi \ >> \ du. \end{aligned}$$
(A.1)

In this latter case one says that \(\Phi \) is Bochner-integrable on I with index p.

Proposition A.1

If \(\Phi -0.1\,cm:I -0.15\,cm \rightarrow -0.1\,cm {({\mathcal {S}})}^{*}\) is Bochner-integrable on I with index p then \({\Vert \int _{I} \Phi _t \ dt \Vert }_{-p} \le \int _{I} {\Vert \Phi _t\Vert }_{-p} \ dt.\)

Theorem A.2

([11], Theorem 13.5) Let \(\Phi :={(\Phi _t)}_{t\in [0,1]}\) be an \({({\mathcal {S}})}^{*}\)-valued process such that:

  1. (i)

    \(t\mapsto S(\Phi _t)(\eta )\) is measurable for every \(\eta \) in \({\mathscr {S}}({\textbf{R}})\).

  2. (ii)

    There exist p in \({\textbf{N}}\), b in \({\textbf{R}}^+\) and a function L in \(L^1([0,1], dt)\) such that, for a.e. t in [0, 1], \(|S(\Phi _t)(\eta )| \le L(t) \ e^{b {| \eta |}^2_{p} }\), for every \(\eta \) in \({\mathscr {S}}({\textbf{R}})\).

Then \(\Phi \) is Bochner integrable on [0, 1] and \(\int ^1_0 \Phi (s) \ ds \in ({{\mathcal {S}}}_{-q})\) for every \(q > p\) such that \(2 \cdot b\cdot e^2\cdot D(q-p) < 1\), where e denotes the base of the natural logarithm and where \(D(r):= \frac{1}{2^{2r}} \ \sum ^{+\infty }_{n=1} \frac{1}{n^{2r}}\), for any r in \((1/2,+\infty )\).

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Bender, C., Lebovits, J. & Lévy Véhel, J. General Transfer Formula for Stochastic Integral with Respect to Multifractional Brownian Motion. J Theor Probab 37, 905–932 (2024). https://doi.org/10.1007/s10959-023-01258-5

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