Multilevel Monte Carlo Methods for Simulated Maximum Likelihood Inference in Multivariate Diffusions

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Sammanfattning

Multilevel Monte Carlo is a novel method for reducing the computational cost
when computing conditional expectations of stochastic processes. This paper considers
the transition density for diffusion processes. It is known that the transition
density can be written as an expectation by utilizing the law of total probability
combined with the Markov property. This idea is combined with the multilevel
Monte Carlo framework to derive a new estimator.
Both the theoretical derivation and the simulations show that the proposed
method is able to reduce the variance of the estimates substantially, when keeping
the bias and computational cost fixed, relative to the standard approximations.
Originalspråkengelska
StatusPublished - 2016
EvenemangWORLD CONGRESS OF THE BACHELIER FINANCE SOCIETY - New York, USA
Varaktighet: 2016 juli 152016 juli 19
Konferensnummer: 9th
http://www.bacheliercongress.com/2016/conference.html

Konferens

KonferensWORLD CONGRESS OF THE BACHELIER FINANCE SOCIETY
Land/TerritoriumUSA
OrtNew York
Period2016/07/152016/07/19
Internetadress

Ämnesklassifikation (UKÄ)

  • Sannolikhetsteori och statistik

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