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MDP for integral functionals of fast and slow processes with averaging

Author

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  • Guillin, A.
  • Liptser, R.

Abstract

We establish the moderate deviation principle (MDP) for the family ofwhere 0

Suggested Citation

  • Guillin, A. & Liptser, R., 2005. "MDP for integral functionals of fast and slow processes with averaging," Stochastic Processes and their Applications, Elsevier, vol. 115(7), pages 1187-1207, July.
    • Handle: RePEc:eee:spapps:v:115:y:2005:i:7:p:1187-1207
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    References listed on IDEAS

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    1. Guillin, Arnaud, 2001. "Moderate deviations of inhomogeneous functionals of Markov processes and application to averaging," Stochastic Processes and their Applications, Elsevier, vol. 92(2), pages 287-313, April.
    2. Veretennikov, A. Yu., 1997. "On polynomial mixing bounds for stochastic differential equations," Stochastic Processes and their Applications, Elsevier, vol. 70(1), pages 115-127, October.
    3. Miguel Arcones, 2002. "Moderate deviations for M-estimators," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 11(2), pages 465-500, December.
    4. Gao, Fuqing, 2001. "Moderate deviations for the maximum likelihood estimator," Statistics & Probability Letters, Elsevier, vol. 55(4), pages 345-352, December.
    5. Wu, Liming, 2001. "Large and moderate deviations and exponential convergence for stochastic damping Hamiltonian systems," Stochastic Processes and their Applications, Elsevier, vol. 91(2), pages 205-238, February.
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    Cited by:

    1. Antoine Jacquier & Konstantinos Spiliopoulos, 2018. "Pathwise moderate deviations for option pricing," Papers 1803.04483, arXiv.org, revised Dec 2018.

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