Given that $(X_n)_{n\geq 0}$ is a Markov Chain, prove that $(X_{kn})_{n\geq 0}$ is a Markov Chain.
I don't know what this exercise has been so difficult for me, I've been playing around with the definition and its consequences for a while a now without being able to prove it:
By definition I know that $P(X_{n+1}\;|\;X_0,...,X_n)=P(X_{n+1}\;|\;X_n)$, and I want to show that $P(X_{k(n+1)}\;|\;X_0,...,X_{kn})=P(X_{k(n+1)}\;|\;X_{kn})$. Is there an elementary way just using this information and just basic knowledge of how to algebraically manipulate conditional probabilities, to prove what I want to prove? Or do I need more information about Markov chains to do this problem?
If $A$ is the stochastic matrix for the given Markov chain, then $A^k$ is the matrix for the subsequence in question. Why is $A^k$ also a stochastic matrix?
Alternatively, show by induction that for a Markov chain $$ P(X_{n+1}|X_{i_1},\ldots ,X_{i_k})=P(X_{n+1}|X_i)$$ where $0\le i_1,\ldots, i_k\le n$ and $i=\max\{i_1, \ldots, i_k\}$.