Showing tha a random variable is a martingale

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To prove that the discrete time branching process Z(n) = X(n)/m^n is a martingale, the first condition is satisfied since E[Z(n)] = 1, indicating it is finite. The challenge lies in demonstrating that E[Z(n+1) | X(1), X(2), ..., X(n)] equals Z(n). It is noted that E[X(n+1) | X(n)] = mX(n), reflecting the mean offspring per individual. The next step involves substituting this expectation into the equation for Z(n+1) and simplifying to show it equals Z(n). Successfully proving this will confirm that Z(n) is indeed a martingale.
rickywaldron
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I'm having a bit of a problem proving the second condition for a martingale, the discrete time branching process Z(n)=X(n)/m^n, where m is the mean number of offspring per individual and X(n) is the size of the nth generation.

I have E[z(n)]=E[x(n)]/m^n=m^n/m^n (from definition E[X^n]=m^n) = 1
which is less than infinity, so first condition passes

Then I get lost with E[Z(n+1) given X(1),X(2)...X(n)]...any clues on how to show this is equal to Z(n)? Thanks
 
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Apparently E[X(n+1)|X(n)]=mX(n) as each individuum in the population has on the mean m offsprings.
 
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