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Compounding processes, also known as perpetuities, play an important role in many applications; in particular, in time series analysis and mathematical finance. Apart from some special cases, the distribution of a perpetuity is hard to compute, and large deviations estimates sometimes involve complicated constants which depend on the complete distribution. Motivated by this, we propose provably efficient importance sampling algorithms which apply to qualitatively different cases, leading todoi:10.1109/wsc.2007.4419625 dblp:conf/wsc/BlanchetZ07 fatcat:nwhkmuqj5rhz3jusw6dlqh4g3q