  Construction of splitting-step methods and properties of related
non-negativity and boundary preserving numerical algorithms for solving
stochastic differential equations (SDEs) of Ito-type are discussed. We present
convergence proofs for a newly designed splitting-step algorithm and simulation
studies for numerous numerical examples ranging from stochastic dynamics
occurring in asset pricing theory in mathematical finance (SDEs of CIR and CEV
models) to measure-valued diffusion and superBrownian motion (SPDEs) as met in
biology and physics.
