Linked from

The 10 pages that link to Filtration (probability theory), each with the reason it gives.

• Stochastic processRelated: It formalizes how information about a process accumulates.

• Wiener processRelated: Filtrations formalize the information available as a Wiener process evolves.

• MartingaleRelated: A martingale’s conditional expectations are taken with respect to this growing information.

• Optional stopping theoremRelated: Stopping times and martingales are defined relative to evolving information.

• Itô's lemmaRelated: Adapted processes and Itô integrals are defined relative to evolving information.

• Doob martingaleRelated: The filtration specifies exactly which information each conditional expectation may use.

• Girsanov theoremRelated: The density process and drift must respect the information available at each time.

• Wald's equationRelated: Stopping-time hypotheses describe when the random count is determined relative to accumulated information.

• Doob's martingale inequalityNarrower topic: A martingale inequality is formulated relative to an evolving information structure.

• Azuma's inequalityRelated: The filtration defines the past against which each martingale increment is bounded and centered.