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Piecewise constant martingales and lazy clocks View Full Text

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Article Info

DATE

2019-02-11

AUTHORS

Christophe Profeta, Frédéric Vrins

ABSTRACT

Conditional expectations (like, e.g., discounted prices in financial applications) are martingales under an appropriate filtration and probability measure. When the information flow arrives in a punctual way, a reasonable assumption is to suppose the latter to have piecewise constant sample paths between the random times of information updates. Providing a way to find and construct piecewise constant martingales evolving in a connected subset of ℝ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\mathbb {R}$\end{document} is the purpose of this paper. After a brief review of possible standard techniques, we propose a construction scheme based on the sampling of latent martingales Z~\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\tilde {Z}$\end{document} with lazy clocksθ. These θ are time-change processes staying in arrears of the true time but that can synchronize at random times to the real (calendar) clock. This specific choice makes the resulting time-changed process Zt=Z~θt\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$Z_{t}=\tilde {Z}_{\theta _{t}}$\end{document} a martingale (called a lazy martingale) without any assumption on Z~\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\tilde {Z}$\end{document}, and in most cases, the lazy clock θ is adapted to the filtration of the lazy martingale Z, so that sample paths of Z on [0,T] only requires sample paths of θ,Z~\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\left (\theta, \tilde {Z}\right)$\end{document} up to T. This would not be the case if the stochastic clock θ could be ahead of the real clock, as is typically the case using standard time-change processes. The proposed approach yields an easy way to construct analytically tractable lazy martingales evolving on (interval of) ℝ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\mathbb {R}$\end{document}. More... »

PAGES

2

References to SciGraph publications

  • 1994. Jumping filtrations and martingales with finite variation in SÉMINAIRE DE PROBABILITÉS XXVIII
  • 1999. Continuous Martingales and Brownian Motion in NONE
  • 2017. Stochastic Calculus, An Introduction Through Theory and Exercises in NONE
  • 1996. Projection d’une diffusion sur sa filtration lente in SÉMINAIRE DE PROBABILITÉS XXX
  • 2005. Stochastic Integration and Differential Equations in NONE
  • 2017. Enlargement of Filtration with Finance in View in NONE
  • 2004. Stochastic Calculus for Finance II in NONE

    • Journal

    TITLE

    Probability, Uncertainty and Quantitative Risk

    ISSUE

    1

    VOLUME

    4

    Subjects

  • FOR: Mathematical Sciences
  • FOR: Statistics

    • Author Affiliations

  • Université d’Évry, Évry, France
  • Louvain Finance Center (LFIN) and Center for Operations Research and Econometrics (CORE), Voie du Roman Pays 34, 1348, Louvain-la-Neuve, Belgium

    • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s41546-019-0036-4

    DOI

    http://dx.doi.org/10.1186/s41546-019-0036-4

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1112046517

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