Convergence analysis of Crank-Nicolson and Rannacher time-marching

This paper presents a convergence analysis of Crank-Nicolson and Rannacher time-marching methods which are often used in finite difference discretisations of the Black-Scholes equations. Particular attention is paid to the important role of Rannacher's startup procedure, in which one or more initial timesteps use Backward Euler timestepping, to achieve second order convergence for approximations of the first and second derivatives. Numerical results confirm the sharpness of the error analysis which is based on asymptotic analysis of the behaviour of the Fourier transform. The relevance to Black-Scholes applications is discussed in detail, with numerical results supporting recommendations on how to maximise the accuracy for a given computational cost

Sharp error estimates for discretisations of the 1D convection/diffusion equation with Dirac initial data

This paper derives sharp estimates of the error arising from explicit and implicit approximations of the constant coefficient 1D convection/diffusion equation with Dirac initial data. The error analysis is based on Fourier analysis and asymptotic approximation of the integrals resulting from the inverse Fourier transform. This research is motivated by applications in computational finance and the desire to prove convergence of approximations to adjoint partial differential equations

Coercivity of domain wall motion in thin films of amorphous rare earth-transition metal alloys

Computer simulations of a two dimensional lattice of magnetic dipoles are performed on the Connection Machine. The lattice is a discrete model for thin films of amorphous rare-earth transition metal alloys, which have application as the storage media in erasable optical data storage systems. In these simulations, the dipoles follow the dynamic Landau-Lifshitz-Gilbert equation under the influence of an effective field arising from local anisotropy, near-neighbor exchange, classical dipole-dipole interactions, and an externally applied field. Various sources of coercivity, such as defects and/or inhomogeneities in the lattice, are introduced and the subsequent motion of domain walls in response to external fields is investigated

Fat vs. thin threading approach on GPUs: application to stochastic simulation of chemical reactions

We explore two different threading approaches on a graphics processing unit (GPU) exploiting two different characteristics of the current GPU architecture. The fat thread approach tries to minimise data access time by relying on shared memory and registers potentially sacrificing parallelism. The thin thread approach maximises parallelism and tries to hide access latencies. We apply these two approaches to the parallel stochastic simulation of chemical reaction systems using the stochastic simulation algorithm (SSA) by Gillespie (J. Phys. Chem, Vol. 81, p. 2340-2361, 1977). In these cases, the proposed thin thread approach shows comparable performance while eliminating the limitation of the reaction system’s size

STOCHSIMGPU Parallel stochastic simulation for the Systems\ud Biology Toolbox 2 for MATLAB

Motivation: The importance of stochasticity in biological systems is becoming increasingly recognised and the computational cost of biologically realistic stochastic simulations urgently requires development of efficient software. We present a new software tool STOCHSIMGPU which exploits graphics processing units (GPUs)for parallel stochastic simulations of biological/chemical reaction systems and show that significant gains in efficiency can be made. It is integrated into MATLAB and works with the Systems Biology Toolbox 2 (SBTOOLBOX2) for MATLAB.\ud \ud Results: The GPU-based parallel implementation of the Gillespie stochastic simulation algorithm (SSA), the logarithmic direct method (LDM), and the next reaction method (NRM) is approximately 85 times faster than the sequential implementation of the NRM on a central processing unit (CPU). Using our software does not require any changes to the user’s models, since it acts as a direct replacement of the stochastic simulation software of the SBTOOLBOX2

Conditional sampling for barrier option pricing under the LT method

We develop a conditional sampling scheme for pricing knock-out barrier options under the Linear Transformations (LT) algorithm from Imai and Tan (2006). We compare our new method to an existing conditional Monte Carlo scheme from Glasserman and Staum (2001), and show that a substantial variance reduction is achieved. We extend the method to allow pricing knock-in barrier options and introduce a root-finding method to obtain a further variance reduction. The effectiveness of the new method is supported by numerical results

Optimal randomized multilevel algorithms for infinite-dimensional integration on function spaces with ANOVA-type decomposition

In this paper, we consider the infinite-dimensional integration problem on weighted reproducing kernel Hilbert spaces with norms induced by an underlying function space decomposition of ANOVA-type. The weights model the relative importance of different groups of variables. We present new randomized multilevel algorithms to tackle this integration problem and prove upper bounds for their randomized error. Furthermore, we provide in this setting the first non-trivial lower error bounds for general randomized algorithms, which, in particular, may be adaptive or non-linear. These lower bounds show that our multilevel algorithms are optimal. Our analysis refines and extends the analysis provided in [F. J. Hickernell, T. M\"uller-Gronbach, B. Niu, K. Ritter, J. Complexity 26 (2010), 229-254], and our error bounds improve substantially on the error bounds presented there. As an illustrative example, we discuss the unanchored Sobolev space and employ randomized quasi-Monte Carlo multilevel algorithms based on scrambled polynomial lattice rules.Comment: 31 pages, 0 figure

Rapid evolution of our understanding of the pathogenesis of COVID-19: Implications for therapy

COVID-19 severity appears to lie in its propensity to cause a hyperinflammatory response, attributed to the cytokine release syndrome (CRS) or ‘cytokine storm’, although the exact role of the CRS remains to be fully elucidated. Hyperinflammation triggers a hypercoagulable state, also thought to play a key role in COVID-19 pathogenesis. Disease severity is linked to age, sex and comorbid conditions, which in turn may be linked to oxidative stress and pre-existing depletion of nicotinamide adenine dinucleotide (NAD+). There is increasing evidence that the host genome may determine disease outcome. Since most information pertaining to COVID-19 has thus far been extrapolated from the ‘global North’, similar studies in African populations are warranted. Many studies are aimed at finding a therapeutic strategy based on scientific rationale. Some promising results have emerged, e.g. the use of corticosteroids in severe acute respiratory distress syndrome (ARDS)

The Beliefs and Practices of Second Grade Teachers Who Implement Independent Reading and Its Effect on Students’ Reading Achievement and Reading Volume

The purpose of the present study was to explore the beliefs and practices of teachers who implement independent reading in their classrooms. Results showed that teachers who implemented independent reading believed in the importance of both the quantity and quality of student reading. The teachers’ practices of independent reading showed students selecting books that were “just-right” for them to read, social experiences around reading, guided practice through reading conferences with the teacher, and setting a purpose for reading through response activities. A nonexperimental comparative design was used to examine the effects of independent reading on reading volume and reading achievement. Results indicated that there were no statistically significant effects between the independent reading group and the no independent reading group for reading achievement or reading volume. Additionally, there was no statistically significant difference in growth of reading achievement between higher and lower readers in the independent reading group