Rare events simulation for heavy-tailed distributions

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How researchers see this paper

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Ruin theory revisited: stochastic models for operational risk (2002, background): “Asmussen and Binswanger [4], and Asmussen et al. [ 5 ]; the keywords here”
Portfolio Value‐at‐Risk with Heavy‐Tailed Risk Factors (2002, background): “Most successful applications of importance sampling are based on an exponential change of measure; and the extension of light-tailed methods to heavy-tailed models can often give disastrous results, as demonstrated in Asmussen et al. (2000).”
HEAVY TAILS, IMPORTANCE SAMPLING AND CROSS–ENTROPY (2005, background): “Nevertheless, it is found in [ 6 ] that the most obvious non–i.i.d.”
Monte Carlo and Quasi-Monte Carlo Sampling (2009, background): “5 – and other well-known tools in risk theory [11, 13, 14].”
State-dependent importance sampling for regularly varying random walks (2008, methodology): “The work by Asmussen et al. (2000) provides a number of examples that indicates some of the problems that arise when trying to apply importance sampling ideas based on large deviations theory for systems with heavy-tailed characteristics; see also Bassamboo et al. (2005) for additional issues aris”
Improved algorithms for rare event simulation with heavy tails (2006, background): “Later, polynomial time importance sampling ideas were given in [7] and [17].”