2126 CHAPTER 63. THE QUADRATIC VARIATION OF A MARTINGALE

and Pn (t) is a martingale. Then from 63.2.9, Qn (t) is a submartingale and converges foreach t to something, denoted as [M] (t) in L1 (Ω) uniformly in t ∈ [0,T ]. This is becausePn (t) converges uniformly on [0,T ] to N (t) in L2 (Ω) and ||M (t)||2 does not depend on n.Then also [M] is a submartingale which equals 0 at 0 because this is true of Qn and becauseif A ∈Fs where s < t,∫

AE ([M] (t) |Fs)dP≡

∫A[M] (t)dP = lim

n→∞

∫A

(||M (t)||2−Pn (t)

)dP

= limn→∞

∫A

E(||M (t)||2−Pn (t) |Fs

)dP≥ lim inf

n→∞

∫A||M (s)||2−Pn (s)dP

= lim infn→∞

∫A

Qn (s)dP =∫

A[M] (s)dP.

Note that Qn (t) is increasing because as t increases, the definition allows for the pos-sibility of more nonzero terms in the sum. Therefore, [M] (t) is also increasing in t. Thefunction t→ [M] (t) is continuous because ||M (t)||2 = [M] (t)+N (t) and t→ N (t) is con-tinuous as is t → ||M (t)||2 . That is, off a set of measure zero, these are both continuousfunctions of t and so the same is true of [M] .

Now put back in Mα p∧δ in place of M. From the above, this has shown∣∣∣∣∣∣Mα p∧δ (t)∣∣∣∣∣∣2 = [Mα p∧δ

](t)+Np (t)

where Np is a martingale and[Mα p∧δ

](t) = lim

n→∞∑k≥0

∣∣∣∣∣∣Mα p∧δ(t ∧ τ

nk+1)−Mα p∧δ (t ∧ τ

nk)∣∣∣∣∣∣2

= limn→∞

∑k≥0

∣∣∣∣M (t ∧ τnk+1∧α p∧δ

)−M (t ∧ τ

nk ∧α p∧δ )

∣∣∣∣2 in L1 (Ω) , (63.2.10)

the convergence being uniform on [0,T ] . The above formula shows that[Mα p∧δ

](t) is a

Ft∧δ∧α p measurable random variable which depends on t ∧ δ ∧α p.(Note that t ∧ δ is areal valued stopping time even if δ = ∞.) Therefore, by Proposition 63.2.2, there exists arandom variable, denoted as

[Mδ](t) which is the pointwise limit as p→∞ of these random

variables which is Ft∧δ measurable because, for a given ω, when α p becomes larger than t,the sum in 63.2.10 loses its dependence on p. Thus from pointwise convergence in 63.2.10,[

](t)≡ lim

n→∞∑k≥0

∣∣∣∣M (t ∧δ ∧ τnk+1)−M (t ∧δ ∧ τ

nk)∣∣∣∣2

In case δ = ∞, the above gives an Ft measurable random variable denoted by [M] (t) suchthat

[M] (t)≡ limn→∞

∑k≥0

∣∣∣∣M (t ∧ τnk+1)−M (t ∧ τ

nk)∣∣∣∣2

Now stopping with the stopping time δ , this shows that[Mδ

](t)≡ lim

n→∞∑k≥0

∣∣∣∣M (t ∧δ ∧ τnk+1)−M (t ∧δ ∧ τ

nk)∣∣∣∣2 = [M]δ (t)

2126 CHAPTER 63. THE QUADRATIC VARIATION OF A MARTINGALEand P, (t) is a martingale. Then from 63.2.9, Q, (tf) is a submartingale and converges foreach f to something, denoted as [M] (rt) in L! (Q) uniformly in t € [0,T]. This is becauseP, (t) converges uniformly on [0,7] to N (t) in L? (Q) and ||M (t)||? does not depend on n.Then also [M] is a submartingale which equals 0 at 0 because this is true of Q,, and becauseifA € Y, where s <t,[ew (t)|F%)dP = | [M] (t) dP = limnoo J 4(\IM (I? — Fale) aP= lim E (\|M()|? —Pa (| Fs) dP > lim int [ \|M(s)|? Pa (s)aPA neo JAnoo |= lim inf, | Q, (s) dP = | [M] (s) dP.n—ycoNote that Q, (t) is increasing because as f increases, the definition allows for the pos-sibility of more nonzero terms in the sum. Therefore, [M] (t) is also increasing in t. Thefunction t > [M](t) is continuous because ||M (t)||° = [M] (t) +N (t) and t > N(t) is con-tinuous as is t > ||M(t)||*. That is, off a set of measure zero, these are both continuousfunctions of t and so the same is true of [M].Now put back in M@"° in place of M. From the above, this has shown2jfaaen® (ef = [ame] (2) +p (1)where N, is a martingale and[meee®?) (1) = Fim Y ||" (1A chy.) M8" (eA th)lnro ES= Him | (A eh AQpA8)—M(tAtiAap,AS)|| inL'(Q), —— (63.2.10)the convergence being uniform on [0,7]. The above formula shows that |[M Ap/8] (t) isaFn8Aa, Measurable random variable which depends on t \ 6 A @,.(Note that t/\ 6 is areal valued stopping time even if 6 = 0.) Therefore, by Proposition 63.2.2, there exists arandom variable, denoted as [M 5] (t) which is the pointwise limit as p + © of these randomvariables which is ¥;,5 measurable because, for a given @, when @, becomes larger than t,the sum in 63.2.10 loses its dependence on p. Thus from pointwise convergence in 63.2.10,[M?] (1) = lim Y ||M (108A th,1) —M (CAS AzH)|l?ne SHIn case 6 =, the above gives an -¥; measurable random variable denoted by [M] (t) suchthat2[M1] (¢) = lim YP ||M (eA th) —M (At) |k>0Now stopping with the stopping time 6, this shows thatlm? (1) = lim J|M (tS Ath) —M(tAdAt8)|° = [MP (0)>0n—oo