From f097e9adb9e403d49c32707d1a0634296bcd71c0 Mon Sep 17 00:00:00 2001 From: Josia Pietsch Date: Mon, 17 Jul 2023 20:59:06 +0200 Subject: [PATCH] s/sub-martingale/submartingale/g --- inputs/lecture_16.tex | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/inputs/lecture_16.tex b/inputs/lecture_16.tex index dca129c..62dce27 100644 --- a/inputs/lecture_16.tex +++ b/inputs/lecture_16.tex @@ -183,21 +183,22 @@ Typically $\cF_n = \sigma(X_1, \ldots, X_n)$ for a sequence of random variables. for all $n$. \end{itemize} - $(X_n)_n$ is called a \vocab{sub-martingale}, + $(X_n)_n$ is called a \vocab{submartingale}, if it is adapted to $\cF_n$ but \[ \bE[X_{n+1} | \cF_n] \overset{\text{a.s.}}{\ge} X_n. \] - It is called a \vocab{super-martingale} + It is called a \vocab{supermartingale} if it is adapted but $\bE[X_{n+1} | \cF_n] \overset{\text{a.s.}}{\le} X_n$. \end{definition} \begin{corollary} + \label{cor:convexmartingale} 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}. - Then $(f(X_n))_n$ is a sub-martingale. - Likewise, if $f$ is concave, then $((f(X_n))_n$ is a super-martingale. + Then $(f(X_n))_n$ is a submartingale. + Likewise, if $f$ is concave, then $((f(X_n))_n$ is a supermartingale. \end{corollary} \begin{proof} Apply \autoref{cjensen}.