State-dependent Importance Sampling for Regularly Varying Random Walks

  title={State-dependent Importance Sampling for Regularly Varying Random Walks},
  author={Jose H. Blanchet and Jingchen Liu},
Consider a sequence (Xk : k ≥ 0) of regularly varying independent and identically distributed random variables with mean 0 and finite variance. We develop efficient rare-event simulation methodology associated with large deviation probabilities for the random walk (Sn : n ≥ 0). Our techniques are illustrated by examples, including large deviations for the empirical mean and path-dependent events. In particular, we describe two efficient state-dependent importance sampling algorithms for… CONTINUE READING
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