VTeX: Solutions for Science Publishing logo


  • List of journals
  • Browse subjects
  • About Publisher
  • Help
  • Sitemap
Login Register

  1. Home
  2. Journals
  3. MSTA
  4. Issues
  5. Volume 6, Issue 1 (2019)
  6. Fractional Cox–Ingersoll–R ...

Modern Stochastics: Theory and Applications*

Submit your article Information Become a Peer-reviewer VTeX
  • Article info
  • Full article
  • Related articles
  • More
    Article info Full article Related articles

Fractional Cox–Ingersoll–Ross process with small Hurst indices
Volume 6, Issue 1 (2019), pp. 13–39
Yuliya Mishura   Anton Yurchenko-Tytarenko  

Authors

 
Placeholder
https://doi.org/10.15559/18-MSTA126
Pub. online: 21 December 2018      Type: Research Article      Open accessOpen Access

Received
27 August 2018
Revised
3 December 2018
Accepted
3 December 2018
Published
21 December 2018

Abstract

In this paper the fractional Cox–Ingersoll–Ross process on ${\mathbb{R}_{+}}$ for $H<1/2$ is defined as a square of a pointwise limit of the processes ${Y_{\varepsilon }}$, satisfying the SDE of the form $d{Y_{\varepsilon }}(t)=(\frac{k}{{Y_{\varepsilon }}(t){1_{\{{Y_{\varepsilon }}(t)>0\}}}+\varepsilon }-a{Y_{\varepsilon }}(t))dt+\sigma d{B^{H}}(t)$, as $\varepsilon \downarrow 0$. Properties of such limit process are considered. SDE for both the limit process and the fractional Cox–Ingersoll–Ross process are obtained.

References

[1] 
Anh, V., Inoue, A.: Financial Markets with Memory I: Dynamic Models. Stoch. Anal. Appl. 23(2), 275–300 (2005). MR2130350. https://doi.org/10.1081/SAP-200050096
[2] 
Bollerslev, T., Mikkelsen, H.O.: Modelling and pricing long memory in stock market volatility. J. Econom. 73(1), 151–184 (2005)
[3] 
Cheridito, P., Kawaguchi, H., Maejima, M.: Fractional Ornstein-Uhlenbeck processes. Electron. J. Probab. 8(1), 1–14 (2003). MR1961165. https://doi.org/10.1214/EJP.v8-125
[4] 
Cox, J.C., Ingersoll, J.E., Ross, S.A.: A re-examination of traditional hypotheses about the term structure of interest rates. J. Finance 36, 769–799 (1981)
[5] 
Cox, J.C., Ingersoll, J.E., Ross, S.A.: An intertemporal general equilibrium model of asset prices. Econometrica 53(1), 363–384 (1985). MR0785474. https://doi.org/10.2307/1911241
[6] 
Cox, J.C., Ingersoll, J.E., Ross, S.A.: A theory of the term structure of interest rates. J. Finance 53(2), 385–408 (1985). MR0785475. https://doi.org/10.2307/1911242
[7] 
Ding, Z., Granger, C.W., Engle, R.F.: A long memory property of stock market returns and a new model. J. Empir. Finance 1(1), 83–106 (1993)
[8] 
Euch, O., Rosenbaum, M.: The characteristic function of rough Heston models. https://arxiv.org/pdf/1609.02108.pdf. Accessed 18 Aug 2018. arXiv: 1609.02108
[9] 
Feller, W.: Two singular diffusion problems. Ann. Math. 54, 173–182 (1951). MR0054814. https://doi.org/10.2307/1969318
[10] 
Heston, S.L.: A closed-form solution for options with stochastic volatility with applications to bond and currency options. Rev. Financ. Stud. 6(2), 327–343 (1993)
[11] 
Kuchuk-Iatsenko, S., Mishura, Y.: Pricing the European call option in the model with stochastic volatility driven by Ornstein-Uhlenbeck process. Exact formulas. Mod. Stoch. Theory Appl. 2(3), 233–249 (2015). MR3407504. https://doi.org/10.15559/15-VMSTA36CNF
[12] 
Kuchuk-Iatsenko, S., Mishura, Y., Munchak, Y.: Application of Malliavin calculus to exact and approximate option pricing under stochastic volatility. Theory Probab. Math. Stat. 94, 93–115 (2016). MR3553457. https://doi.org/10.1090/tpms/1012
[13] 
Leonenko, N., Meerschaert, M., Sikorskii, A.: Correlation structure of fractional Pearson diffusion. Comput. Math. Appl. 66(5), 737–745 (2013). MR3089382. https://doi.org/10.1016/j.camwa.2013.01.009
[14] 
Leonenko, N., Meerschaert, M., Sikorskii, A.: Fractional Pearson diffusion. J. Math. Anal. Appl. 403(2), 532–546 (2013). MR3037487. https://doi.org/10.1016/j.jmaa.2013.02.046
[15] 
Marie, N.: A generalized mean-reverting equation and applications. ESAIM Probab. Stat. 18, 799–828 (2014). MR3334015. https://doi.org/10.1051/ps/2014002
[16] 
Mishura, Y.: Stochastic Calculus for Fractional Brownian Motion and Related Processes. Springer, Berlin (2008). MR2378138. https://doi.org/10.1007/978-3-540-75873-0
[17] 
Mishura, Y., Piterbarg, V., Ralchenko, K., Yurchenko-Tytarenko, A.: Stochastic representation and pathwise properties of fractional Cox-Ingersoll-Ross process (in Ukrainian). Theory Probab. Math. Stat. 97, 157–170 (2017). Available in English at: https://arxiv.org/pdf/1708.02712.pdf. MR3746006
[18] 
Mishura, Y., Yurchenko-Tytarenko, A.: Fractional Cox-Ingersoll-Ross process with non-zero “mean”. Mod. Stoch. Theory Appl. 5(1), 99–111 (2018). MR3784040. https://doi.org/10.15559/18-vmsta97
[19] 
Mukeru, S.: The zero set of fractional Brownian motion is a Salem set. J. Fourier Anal. Appl. 24(4), 957–999 (2018). MR3843846. https://doi.org/10.1007/s00041-017-9551-9
[20] 
Nualart, D., Ouknine, Y.: Regularization of differential equations by fractional noise. Stoch. Process. Appl. 102, 103–116 (2002). MR1934157. https://doi.org/10.1016/S0304-4149(02)00155-2
[21] 
Yamasaki, K., Muchnik, L., Havlin, S., Bunde, A., Stanley, H.E.: Scaling and memory in volatility return intervals in financial markets. Proc. Natl. Acad. Sci. USA 102(26), 9424–9428 (2005)

Full article Related articles PDF XML
Full article Related articles PDF XML

Copyright
© 2019 The Author(s). Published by VTeX
by logo by logo
Open access article under the CC BY license.

Keywords
Fractional Cox–Ingersoll–Ross process fractional Brownian motion stochastic differential equation pathwise Stratonovich integral

MSC2010
60G22 60H05 60H10

Metrics
since February 2017
0

Article info
views

0

Full article
views

3

PDF
downloads

3

XML
downloads

Export citation

Copy and paste formatted citation
Placeholder

Download citation in file


Share


RSS

  • About Publisher
Powered by PubliMill  •  Privacy policy