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Stochastic Processes in Continuous Time

  • Nicholas H. Bingham
  • Rüdiger Kiesel
Part of the Springer Finance book series (FINANCE)

Abstract

The underlying set-up is as in Chapter 3: we need a complete probability space (Ω, ℱ, ℙ), equipped with a filtration, i.e a nondecreasing family F = (F t ) t≥0 of sub-σ-fileds of F: F s F t F for 0 ≤ s ≤ t ≤ ∞; here F t represents the information available at time t, and the filtration (F t ) represents the information flow evolving with time.

Keywords

Brownian Motion Continuous Time Stochastic Differential Equation Weak Convergence Quadratic Variation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London 1998

Authors and Affiliations

  • Nicholas H. Bingham
    • 1
  • Rüdiger Kiesel
    • 1
  1. 1.Birkbeck CollegeUniversity of LondonLondonUK

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