Abstract
We introduce new quantile estimators with adaptive importance sampling. The adaptive estimators are based on weighted samples that are neither independent nor identically distributed. Using the law of iterated logarithm for martingales, we prove the convergence of the adaptive quantile estimators for general distributions with non-unique quantiles, thereby extending the work of Feldman and Tucker (1966). We illustrate the algorithm with an example from credit portfolio risk analysis.
Full Text 
Sign-in/Register to access full text options
Sign-in/Register to access full text options 
Published version (
Free)
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
