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Part of the book series: Stochastic Modelling and Applied Probability ((SMAP,volume 13))

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Abstract

A process M t = (M t 1, ... ,M t d) taking values in R d is a martingale with respect to the increasing σ-field family (F t ) if (M t i, F t ) is a martingale for each i = 1, ... ,d, or equivalently, if (θ,M t ,) is a real-valued martingale with respect to (F t ) for every θ, ∈ R d . Here we use (,) to denote inner product in R d. (M t , F t ) with M 0 = 0 (a.s.) is a d-dimensional, continuous L 2-martingale if for every θR d, (θ,M t ) is a continuous L 2-martingale with respect toF t . It is then easy to verify the existence of a unique d × d-matrix—valued process A t , = (A t ij) with the following properties:

  1. a.

    Each A t ij is F t -measurable.

  2. b.

    A 0 = 0 and A t (ω) is continuous in t for almost all ω.

  3. c.

    For θR d, (A t θ,θ) is the (continuous) increasing process associated with (θ,M t ).

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Notes

  • The proof of Theorem 4.2.1 is due to Meyer [44]. The variant of Ito’s formula given in Theorem 4.2.2 is due to Neveu [73].

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© 1980 Springer Science+Business Media New York

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Kallianpur, G. (1980). The Ito Formula. In: Stochastic Filtering Theory. Stochastic Modelling and Applied Probability, vol 13. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-6592-2_4

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  • DOI: https://doi.org/10.1007/978-1-4757-6592-2_4

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-2810-8

  • Online ISBN: 978-1-4757-6592-2

  • eBook Packages: Springer Book Archive

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