Stochastic simulation of rare events


Autoria(s): Gatto, Riccardo
Data(s)

2015

Resumo

Stochastic simulation is an important and practical technique for computing probabilities of rare events, like the payoff probability of a financial option, the probability that a queue exceeds a certain level or the probability of ruin of the insurer's risk process. Rare events occur so infrequently, that they cannot be reasonably recorded during a standard simulation procedure: specifc simulation algorithms which thwart the rarity of the event to simulate are required. An important algorithm in this context is based on changing the sampling distribution and it is called importance sampling. Optimal Monte Carlo algorithms for computing rare event probabilities are either logarithmic eficient or possess bounded relative error.

Formato

application/pdf

Identificador

http://boris.unibe.ch/77831/1/paper3.pdf

Gatto, Riccardo (2015). Stochastic simulation of rare events. In: StatsRef: Statistics Reference Online (pp. 1-11). Wiley 10.1002/9781118445112.stat07823 <http://dx.doi.org/10.1002/9781118445112.stat07823>

doi:10.7892/boris.77831

info:doi:10.1002/9781118445112.stat07823

Idioma(s)

eng

Publicador

Wiley

Relação

http://boris.unibe.ch/77831/

Direitos

info:eu-repo/semantics/restrictedAccess

Fonte

Gatto, Riccardo (2015). Stochastic simulation of rare events. In: StatsRef: Statistics Reference Online (pp. 1-11). Wiley 10.1002/9781118445112.stat07823 <http://dx.doi.org/10.1002/9781118445112.stat07823>

Palavras-Chave #510 Mathematics
Tipo

info:eu-repo/semantics/bookPart

info:eu-repo/semantics/publishedVersion

PeerReviewed