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world:forward-downward-martingale [2026/02/03 16:03]
rdouc [Theorem 2 (Doob's Forward Convergence Theorem)]
world:forward-downward-martingale [2026/02/07 15:03] (current)
rdouc
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 ====== Upcrossing Inequality and Martingale Convergence ====== ====== Upcrossing Inequality and Martingale Convergence ======
- 
-**Intuition.**  ​ 
-A process cannot oscillate infinitely many times between two fixed levels $a<b$ without paying a cost.  ​ 
-Each complete upcrossing from $a$ to $b$ forces an increase of at least $b-a$.  ​ 
-The upcrossing inequality makes this idea precise and leads to almost sure convergence results for martingales and supermartingales. 
  
 ===== Doob's Upcrossing Inequality ===== ===== Doob's Upcrossing Inequality =====
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 <WRAP center round tip 80%> <WRAP center round tip 80%>
-Let $U_n[a,b]$ denote the number of completed upcrossings from $a$ to $b$ between times $0$ and $n$.  ​+Let $U_{0:n}[a,b]$ denote the number of completed upcrossings from $a$ to $b$ between times $0$ and $n$.  ​
 Then the following inequality holds: Then the following inequality holds:
 $$ $$
-Y_n \ge (b-a)\,U_n[a,b] - (X_n-a)^-.+Y_n \ge (b-a)\,U_{0:n}[a,b] - (X_n-a)^-.
 $$ $$
  
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 Summing the contributions of all completed upcrossings and accounting for the final correction yields the stated inequality. ∎ Summing the contributions of all completed upcrossings and accounting for the final correction yields the stated inequality. ∎
  
-===== Theorem ​(Doob'​s Forward Convergence Theorem) =====+===== Theorem ​(Doob'​s Forward Convergence Theorem) =====
  
-<WRAP center round info 80%>+<WRAP center round todo 80%>
 Let $(X_n)_{n\ge0}$ be a supermartingale such that Let $(X_n)_{n\ge0}$ be a supermartingale such that
 $$ $$
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 By the upcrossing inequality, for any $a<b$, By the upcrossing inequality, for any $a<b$,
 $$ $$
-(b-a)\,​\mathbb E[U_n[a,b]]+(b-a)\,​\mathbb E[U_{0:n}[a,b]]
 \le \le
 \mathbb E[Y_n] + \mathbb E[(X_n-a)^-]. \mathbb E[Y_n] + \mathbb E[(X_n-a)^-].
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 The $L^1$ boundedness assumption implies that $\sup_n \mathbb E[(X_n-a)^-]<​\infty$. The $L^1$ boundedness assumption implies that $\sup_n \mathbb E[(X_n-a)^-]<​\infty$.
  
-Therefore,+By the monotone convergence theorem
 $$ $$
-\sup_n ​\mathbb E[U_n[a,​b]]<​\infty,​+\mathbb E[U_{0:​\infty}[a,​b]]<​\infty,​
 $$ $$
 which implies that the total number of upcrossings is almost surely finite.  ​ which implies that the total number of upcrossings is almost surely finite.  ​
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 The conditional expectations stabilize and converge to the conditional expectation with respect to the remaining common information. The conditional expectations stabilize and converge to the conditional expectation with respect to the remaining common information.
  
-===== Theorem ​(Lévy'​s Downward Convergence Theorem) =====+===== Theorem ​(Lévy'​s Downward Convergence Theorem) =====
  
-Let $(\mathcal ​G_{-n})_{n\ge1}$ be a decreasing sequence of $\sigma$-fields such that+<WRAP center round todo 80%> 
 +Let $(\mathcal ​F_{-n})_{n\ge1}$ be a decreasing sequence of $\sigma$-fields such that
 $$ $$
-\mathcal ​G_{-\infty}+\mathcal ​F_{-\infty}
 = =
-\bigcap_{k\ge1}\mathcal ​G_{-k} +\bigcap_{k\ge1}\mathcal ​F_{-k} 
-\subseteq \cdots \subseteq \mathcal ​G_{-(n+1)} \subseteq \mathcal ​G_{-n} \subseteq \cdots \subseteq \mathcal ​G_{-1}.+\subseteq \cdots \subseteq \mathcal ​F_{-(n+1)} \subseteq \mathcal ​F_{-n} \subseteq \cdots \subseteq \mathcal ​F_{-1}.
 $$ $$
  
 For any random variable $Z$ satisfying $\mathbb E[|Z|]<​\infty$,​ we have For any random variable $Z$ satisfying $\mathbb E[|Z|]<​\infty$,​ we have
 $$ $$
-\lim_{n\to\infty}\mathbb E[Z\mid\mathcal ​G_{-n}]+\lim_{n\to\infty}\mathbb E[Z\mid\mathcal ​F_{-n}]
 = =
-\mathbb E[Z\mid\mathcal ​G_{-\infty}]+\mathbb E[Z\mid\mathcal ​F_{-\infty}]
 \quad\text{almost surely}. \quad\text{almost surely}.
 $$ $$
 +
 +</​WRAP>​
  
 ===== Proof ===== ===== Proof =====
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 Define the process Define the process
 $$ $$
-X_k := \mathbb E[Z\mid\mathcal ​G_k], \qquad -n\le k\le -1.+X_k := \mathbb E[Z\mid\mathcal ​F_k], \qquad -n\le k\le -1.
 $$ $$
 This is a martingale bounded in $L^1$. This is a martingale bounded in $L^1$.
  
-Similarly as before, we define $C_1=\mathsf{1}_{X_{-n} < a}$ . For all $-n  < k \leq -1$, we set $C_k=\mathsf{1}_{C_{k-1}=1} \mathsf{1}_{X_{k-1} \leq b}+ \mathsf{1}_{C_{k-1}=0} \mathsf{1}_{X_{k-1} <a}$. Define also $Y_k=\sum_{\ell=-n}^k C_\ell (X_\ell - X_{\ell-1})$. Then, for the same reasons, the number of upcrossing $U_n[a,b]$ between $-n$ and $-1$ can be bounded as follows:  ​+Similarly as before, we define $C_1=\mathsf{1}_{X_{-n} < a}$ . For all $-n  < k \leq -1$, we set $C_k=\mathsf{1}_{C_{k-1}=1} \mathsf{1}_{X_{k-1} \leq b}+ \mathsf{1}_{C_{k-1}=0} \mathsf{1}_{X_{k-1} <a}$. Define also $Y_k=\sum_{\ell=-n}^k C_\ell (X_\ell - X_{\ell-1})$. Then, for the same reasons, the number of upcrossing $U_{-n:-1}[a,b]$ between $-n$ and $-1$ can be bounded as follows:  ​
 $$ $$
-Y_n \geq (b-a) U_n[a,b] - (X_n-a)^-+Y_{-1} ​\geq (b-a) U_{-n:-1}[a,b] - (X_{-1}-a)^-
 $$ $$
  
 As before, the integrability of $Z$ ensures that the expected number of upcrossings is finite, which implies that $(X_k)$ converges almost surely as $k\to-\infty$. As before, the integrability of $Z$ ensures that the expected number of upcrossings is finite, which implies that $(X_k)$ converges almost surely as $k\to-\infty$.
  
-The limit must coincide with $\mathbb E[Z\mid\mathcal ​G_{-\infty}]$,​ which completes the proof. ∎+The limit must coincide with $\mathbb E[Z\mid\mathcal ​F_{-\infty}]$,​ which completes the proof. ∎ 
 + 
 +[[?​do=backlink|Linked pages]] 
  
world/forward-downward-martingale.1770131017.txt.gz · Last modified: 2026/02/03 16:03 by rdouc