Advances in Applied Probability
Error bounds for one-dimensional constrained Langevin approximations for nearly density-dependent Markov chains
Continuous-time Markov chains are frequently used to model the stochastic dynamics of (bio)chemical reaction networks. However, except in very special cases, they cannot be analyzed exactly. Additionally, simulation can be computationally intensive. An…
Advances in Applied Probability
Convergence of hybrid slice sampling via spectral gap
It is known that the simple slice sampler has robust convergence properties; however, the class of problems where it can be implemented is limited. In contrast, we consider hybrid slice samplers which are easily implementable and where another Markov c…
Advances in Applied Probability
Change of measure in a Heston–Hawkes stochastic volatility model
We consider the stochastic volatility model obtained by adding a compound Hawkes process to the volatility of the well-known Heston model. A Hawkes process is a self-exciting counting process with many applications in mathematical finance, insurance, e…
Advances in Applied Probability
Antithetic multilevel particle filters
In this paper we consider the filtering of partially observed multidimensional diffusion processes that are observed regularly at discrete times. This is a challenging problem which requires the use of advanced numerical schemes based upon time-discret…