Doob L1 typo
This commit is contained in:
parent
5691d2c553
commit
3e816f515e
3 changed files with 17 additions and 4 deletions
|
@ -8,10 +8,21 @@ Exercise 4.3
|
||||||
10.2
|
10.2
|
||||||
|
|
||||||
|
|
||||||
Martingales converging a.s.~but not in $L^1$.
|
\begin{example}[Martingale not converging in $L^1$]
|
||||||
|
Let $\Omega = [0,1]$, $\bP = \lambda\upharpoonright [0,1]$.
|
||||||
|
Define $X_n \coloneqq 2^n \cdot \One_{[0,2^n]}$,
|
||||||
|
and let $(\cF_n)_n$ be the canonical filtration.
|
||||||
|
Then $(X_n)_{n}$ is a Martingale
|
||||||
|
with $\bE[X_0] = 1$,
|
||||||
|
but $X_n \xrightarrow{a.s.} 0$.
|
||||||
|
\end{example}
|
||||||
|
|
||||||
|
|
||||||
Stopping times
|
Stopping times
|
||||||
|
|
||||||
|
\begin{example}[{Martingale such that $\bE[X_T] \neq \bE[X_0]$}]
|
||||||
|
Consider the simple random walk and $T = \inf \{n : X_n \ge 1\}$.
|
||||||
|
Obviously $X_T = 1$.
|
||||||
|
\end{example}
|
||||||
|
|
||||||
|
|
||||||
|
|
|
@ -193,7 +193,9 @@ Typically $\cF_n = \sigma(X_1, \ldots, X_n)$ for a sequence of random variables.
|
||||||
\end{definition}
|
\end{definition}
|
||||||
\begin{corollary}
|
\begin{corollary}
|
||||||
Suppose that $f: \R \to \R$ is a convex function such that $f(X_n) \in L^1(\bP)$.
|
Suppose that $f: \R \to \R$ is a convex function such that $f(X_n) \in L^1(\bP)$.
|
||||||
Suppose that $(X_n)_n$ is a martingale\footnote{In this form it means, that there is some filtration, that we don't explicitly specify}.
|
Suppose that $(X_n)_n$ is a martingale%
|
||||||
|
\footnote{In this form it means, that there is some filtration,
|
||||||
|
that we don't explicitly specify}.
|
||||||
Then $(f(X_n))_n$ is a sub-martingale.
|
Then $(f(X_n))_n$ is a sub-martingale.
|
||||||
\end{corollary}
|
\end{corollary}
|
||||||
\begin{proof}
|
\begin{proof}
|
||||||
|
|
|
@ -140,7 +140,7 @@ First, we need a very important inequality:
|
||||||
Let $X_n^\ast \coloneqq \max \{|X_1|, |X_2|, \ldots, |X_n|\}$
|
Let $X_n^\ast \coloneqq \max \{|X_1|, |X_2|, \ldots, |X_n|\}$
|
||||||
denote the \vocab{running maximum}.
|
denote the \vocab{running maximum}.
|
||||||
\begin{enumerate}[(1)]
|
\begin{enumerate}[(1)]
|
||||||
\item Then \[ \forall \ell > 0 .~\bP[X_n^\ast \ge \ell] \le \frac{1}{\ell} \int_{\{X_n^\ast \ell\}} |X_n| \dif \bP \le \frac{1}{\ell} \bE[|X_n|]. \]
|
\item Then \[ \forall \ell > 0 .~\bP[X_n^\ast \ge \ell] \le \frac{1}{\ell} \int_{\{X_n^\ast \ge \ell\}} |X_n| \dif \bP \le \frac{1}{\ell} \bE[|X_n|]. \]
|
||||||
(Doob's $L^1$ inequality).
|
(Doob's $L^1$ inequality).
|
||||||
\item Fix $p > 1$. Then \[
|
\item Fix $p > 1$. Then \[
|
||||||
\bE[(X_n^\ast)^p] \le \left( \frac{p}{p-1} \right)^p \bE[|X_n|^p].
|
\bE[(X_n^\ast)^p] \le \left( \frac{p}{p-1} \right)^p \bE[|X_n|^p].
|
||||||
|
|
Reference in a new issue