Stochastic Processes in Continuous Time
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.
KeywordsBrownian Motion Continuous Time Stochastic Differential Equation Weak Convergence Quadratic Variation
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