Saturday, 18 March 2017

probability - Use of the tower property of conditional expectation

Let




  • (Ω,A) and (E,E) be measurable spaces

  • I[0,) be at most countable and closed under addition with 0I


  • X=(Xt)tI be a stochastic process on (Ω,A) with values in (E,E)

  • F=(Ft)tI be the filtration generated by X

  • τ be a F-stopping time

  • f:EIR be bounded and EI-measurable



Clearly, Ys:=1{τ=s}E[f(Xs+t)tIFτ]

is Fs-measurable. Thus,



E[f(Xτ+t)tIFτ]=sIYs=sIE[YsFs]=sIE[1{τ=s}E[f(Xτ+t)tIFs]Fτ],



but I don't understand why the red part is true. It looks like the tower property, but we shouldn't be able to use it unless FτFs, which is obviously wrong. So, how do we need to argue?

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