Short notes in R Markdown on finance, risk, and statistical learning.
A two-state Markov chain worked through end to end: the stationary distribution as the eigenvector of P⊤ for the eigenvalue 1, the second eigenvalue from the trace, why its eigenvector sums to zero, and why Pn converges to the stationary distribution at the geometric rate |λ2|.