Alphabeta Math
ExampleConstruction: Literature-sourcedVerification: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)
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Square of a martingale minus quadratic compensator

Example

Assume AC. Let a given independent family of real variables (Yk)k1 have EYk=0 and finite variances σk2=EYk2. For S0=0, Sn=k=1nYk and the filtration F0 trivial, Fn=σ(Y1,,Yn), one has Sn=k=1nσk2, and Sn2k=1nσk2 is a martingale.

Facts & Assumptions

Given: The hypotheses and conventions in the example.

[F1]

Disjoint groups of independent sigma-algebras remain independent. Disjoint groups of an independent sigma-algebra family remain independent.

[F2]

A known integrable variable conditions to itself; an independent one conditions to its mean. Conditioning a known variable and an independent variable.

[F3]

Conditional expectation is linear, order preserving and expectation preserving. Basic algebra and order properties of conditional expectation.

[F4]

Square-integrable variables have an integrable product by Cauchy–Schwarz. Cauchy-Schwarz for random variables.

[F5]

Predictable quadratic variation sums conditional squared increments. Predictable quadratic variation in discrete time.

[F6]

A square-integrable martingale squared minus its bracket is a martingale. Square minus predictable quadratic variation is a martingale.

[F7]

Nonnegative finite and countable weighted sums of measures are measures. Nonnegative scalar multiples and countable weighted sums of measures are measures.

[F8]

A Dirac measure at a specified point is a probability measure. A Dirac set function is a probability measure.

[F9]

AC supplies the inherited conditional-expectation existence and any stated choice of versions. The Axiom of Choice.

Verification

technique · direct
1.1

The generated sigma-algebras are nested, and finite sums are measurable by Arithmetic and lattice operations preserve measurability whenever they are defined. Cauchy–Schwarz with the constant one gives EYk(EYk2)1/2<. Repeated use of (a+b)22a2+2b2 shows that every finite sum Sn has finite second moment, and hence finite first moment. Group independence and [F2] give E[Yn+1Fn]=0, while the known Sn conditions to itself. Thus E[Sn+1Fn]=Sn, proving the martingale property Martingale submartingale and supermartingale.

givenF1F2F3F4
2.1

The measurable variable Yk2 is integrable and its Borel events belong to σ(Yk), independent of Fk1. Thus E[Yk2Fk1]=EYk2=σk2. Since SkSk1=Yk, the bracket formula gives Sn=k=1nσk2. The square-minus-bracket theorem now gives the asserted martingale. AC is inherited from these conditional classes and the bracket construction.

F1F2F5F6F9step 1.1
3.1

To see why the optional sum differs, take Ω={1,0,1} and P=14δ1+12δ0+14δ1. This is a measure by [F7]–[F8], and its total mass is one. Set Y1(ω)=ω and Yk=0 for k2. The family (Yk)k1 is independent because all but one member have only probability-zero or probability-one events. Here EY1=0 and EY12=1/2. Thus [S]1=Y12 takes values 0,1 with probabilities 1/2,1/2, whereas S1=1/2 everywhere. The compensated square takes values 1/2,1/2 of equal mass and thereafter stays fixed.

F5F7F8step 1.1step 2.1

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