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On the Exact Simulation of (Jump) Diffusion Bridges

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  • Murray Pollock

Abstract

In this paper we outline methodology to efficiently simulate (jump) diffusion bridge sample paths without discretisation error. We achieve this by considering the simulation of conditioned (jump) diffusion bridge sample paths in light of recent work developing a mathematical framework for simulating finite dimensional sample path skeletons (which flexibly characterise the entirety of sample paths).

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  • Murray Pollock, 2015. "On the Exact Simulation of (Jump) Diffusion Bridges," Papers 1505.03030, arXiv.org.
    • Handle: RePEc:arx:papers:1505.03030
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    References listed on IDEAS

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    1. Alexandros Beskos & Omiros Papaspiliopoulos & Gareth O. Roberts, 2008. "A Factorisation of Diffusion Measure and Finite Sample Path Constructions," Methodology and Computing in Applied Probability, Springer, vol. 10(1), pages 85-104, March.
    2. Casella, Bruno & Roberts, Gareth O., 2011. "Exact Simulation of Jump-Diffusion Processes with Monte Carlo Applications," MPRA Paper 95217, University Library of Munich, Germany.
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    Cited by:

    1. Martin Glanzer & Georg Ch. Pflug, 2020. "Multiscale stochastic optimization: modeling aspects and scenario generation," Computational Optimization and Applications, Springer, vol. 75(1), pages 1-34, January.
    2. Murray Pollock & Paul Fearnhead & Adam M. Johansen & Gareth O. Roberts, 2020. "Quasi‐stationary Monte Carlo and the ScaLE algorithm," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(5), pages 1167-1221, December.

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