How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
An unbounded predictable transform may lose integrability
Statement refuted
Assume AC. Predictability of finite real and boundedness of a martingale do not ensure integrability of the algebraic gain . The following gain is finite at every point and fails the integrable-transform domain already at time one.
Facts & Assumptions
Given: The hypotheses and conventions in the statement refuted.
Nonnegative finite and countable weighted sums of measures are measures. Nonnegative scalar multiples and countable weighted sums of measures are measures.
A Dirac measure at a specified point is a probability measure. A Dirac set function is a probability measure.
Under AC every integrable input has a measurable integrable conditional version. Conditional expectation as an ae class.
A known integrable variable conditions to itself; an independent one conditions to its mean. Conditioning a known variable and an independent variable.
Increasing nonnegative measurable limits pass through integrals. Monotone convergence for the integral.
AC supplies the inherited conditional-expectation existence and any stated choice of versions. The Axiom of Choice.
Every product increment must be integrable for an integrable transform. Discrete martingale transform.
Counterexample
Let with its full power-set sigma-algebra and masses . The weighted Dirac sum is a measure by [F1]–[F2]. Its first m two-point blocks have total mass , by multiplying the finite sum by two and subtracting; since , its limit is one. Hence . Let be all unions of the blocks and the full power set for . Complements and countable unions preserve block unions, so this is a filtration.
Set , for . These variables are adapted and bounded by one. For any , its positive-sign and negative-sign portions have equal probability: each equals . Thus , a finite subtraction, so the zero function meets all CE event identities. Consequently . At later times is already known and integrable, so it conditions to itself. Thus is a bounded martingale Martingale submartingale and supermartingale.
Define and for . Every value is finite, is constant on each block and hence -measurable, and later H values are known constants. Thus is predictable Predictable discrete time process and unbounded. The algebraic gain at every positive time is . For , the finite simple integral is . To justify the limiting step locally, augment every finite disjoint simple display by its complement with coefficient ; intersections of two augmented displays partition and carry equal coefficients, so finite additivity and prove representation independence. Common refinements give monotonicity. For any , a simple , and , the sets increase to , including on the zero level of , and continuity from below for the finite-sum measure gives . Let and take the supremum over to obtain MCT. Applying this to gives . Hence the product at time one is not integrable and violates [F7], and the gains cannot be a martingale. No signed conditional expectation of is formed. AC is inherited only from the CE notation used for the bounded M; all masses and factors are explicit.
Depends on
- Martingale submartingale and supermartingale
- Predictable discrete time process
- Discrete martingale transform
- Conditional expectation as an ae class
- Conditional expectation is unique almost surely
- Conditioning a known variable and an independent variable
- Nonnegative scalar multiples and countable weighted sums of measures are measures
- A Dirac set function is a probability measure
- Monotone convergence for the integral
- Nonempty intersections of sigma-algebras are sigma-algebras, so the generated sigma-algebra exists and is minimal
- Expectation of a nonnegative or integrable random variable
- The Axiom of Choice
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
41 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Durrett, Probability: Theory and Examples, fifth edition (standard reference, not scraped)