On the Quantitative Properties of Some Market Models Involving Fractional Derivatives

We review and discuss the properties of various models that are used to describe the behavior of stock returns and are related in a way or another to fractional pseudo-differential operators in the space variable; we compare their main features and discuss what behaviors they are able to capture. Then, we extend the discussion by showing how the pricing of contingent claims can be integrated into the framework of a model featuring a fractional derivative in both time and space, recall some recently obtained formulas in this context, and derive new ones for some commonly traded instruments and a model involving a Riesz temporal derivative and a particular case of Riesz–Feller space derivative. Finally, we provide formulas for implied volatility and first- and second-order market sensitivities in this model, discuss hedging and profit and loss policies, and compare with other fractional (Caputo) or non-fractional models.

The globalization theorem for the Curvature-Dimension condition

The Lott–Sturm–Villani Curvature-Dimension condition provides a synthetic notion for a metric-measure space to have Ricci-curvature bounded from below and dimension bounded from above. We prove that it is enough to verify this condition locally: an essentially non-branching metric-measure space $$(X,\mathsf {d},{\mathfrak {m}})$$ ( X , d , m ) (so that $$(\text {supp}({\mathfrak {m}}),\mathsf {d})$$ ( supp ( m ) , d ) is a length-space and $${\mathfrak {m}}(X) < \infty $$ m ( X ) < ∞ ) verifying the local Curvature-Dimension condition $${\mathsf {CD}}_{loc}(K,N)$$ CD loc ( K , N ) with parameters $$K \in {\mathbb {R}}$$ K ∈ R and $$N \in (1,\infty )$$ N ∈ ( 1 , ∞ ) , also verifies the global Curvature-Dimension condition $${\mathsf {CD}}(K,N)$$ CD ( K , N ) . In other words, the Curvature-Dimension condition enjoys the globalization (or local-to-global) property, answering a question which had remained open since the beginning of the theory. For the proof, we establish an equivalence between $$L^1$$ L 1 - and $$L^2$$ L 2 -optimal-transport–based interpolation. The challenge is not merely a technical one, and several new conceptual ingredients which are of independent interest are developed: an explicit change-of-variables formula for densities of Wasserstein geodesics depending on a second-order temporal derivative of associated Kantorovich potentials; a surprising third-order theory for the latter Kantorovich potentials, which holds in complete generality on any proper geodesic space; and a certain rigidity property of the change-of-variables formula, allowing us to bootstrap the a-priori available regularity. As a consequence, numerous variants of the Curvature-Dimension condition proposed by various authors throughout the years are shown to, in fact, all be equivalent in the above setting, thereby unifying the theory.

Effect of the boundary conditions, temporal, and spatial resolution on the pressure from PIV for an oscillating flow

The pressure field of an impinging synthetic jet has been computed from time-resolved, three-dimensional, three-component (3D-3C) particle image velocimetry (PIV) velocity field data using a Poisson equationbased pressure solver. The pressure solver used in this work can take advantage of the temporal derivative of the pressure to enhance the temporal coherence of the calculated pressure field for time-resolved velocity data. The reconstructed pressure field shows sensitivity to the implementation of the boundary conditions, as well as to the spatial and temporal resolution of the PIV data. The pressure from a 3D Poisson solver that does not consider the temporal derivative of the pressure shows high random error. Invoking the temporal derivative of the pressure eliminates this high-frequency noise, however, the calculated pressure exhibits an unphysical temporal drift. This temporal drift is affected by both the temporal resolution of the PIV data and the spatial resolution of the PIV vector field, which was systematically evaluated by downsampling the instantaneous data and increasing the interrogation window size. It was observed that decreasing the temporal resolution increased the drift, while decreasing the spatial resolution decreased the drift.

Temporal derivative computation in the dorsal raphe network revealed by an experimentally-driven augmented integrate-and-fire modeling framework

By means of an expansive innervation, the relatively few phylogenetically-old serotonin (5-HT) neurons of the dorsal raphe nucleus (DRN) are positioned to enact coordinated modulation of circuits distributed across the entire brain in order to adaptively regulate behavior. In turn, the activity of the DRN is driven by a broad set of excitatory inputs, yet the resulting network computations that naturally emerge from the excitability and connectivity features of the various cellular elements of the DRN are still unknown. To gain insight into these computations, we developed a flexible experimental and computational framework based on a combination of automatic characterization and network simulations of augmented generalized integrate-and-fire (aGIF) single-cell models. This approach enabled the examination of causal relationships between specific excitability features and identified population computations. We found that feedforward inhibition of 5-HT neurons by heterogeneous DRN somatostatin (SOM) neurons implemented divisive inhibition, while endocannabinoid-mediated modulation of excitatory drive to the DRN increased the gain of 5-HT output. The most striking computation that arose from this work was the ability of 5-HT output to linearly encode the derivative of the excitatory inputs to the DRN. This network computation primarily emerged from the prominent adaptation mechanisms found in 5-HT neurons, including a previously undescribed dynamic threshold. This novel computation in the DRN provides a potential mechanism underlying some of the functions recently ascribed to 5-HT in the context of reinforcement learning.

New and more fractional soliton solutions related to generalized Davey–Stewartson equation using oblique wave transformation

The generalized fractional Davey–Stewartson (DSS) equation with fractional temporal derivative, which is used to explore the trends of wave propagation in water of finite depth under the effects of gravity force and surface tension, is considered in this paper. The paper addresses the full nonlinearity of the proposed model. To extract the oblique soliton solutions of the generalized fractional DSS (FDSS) equation is the dominant feature of this research. The conformable fractional derivative is used for fractional temporal derivative and oblique wave transformation is used for converting the proposed model into ordinary differential equation. Two state-of-the-art integration schemes, modified auxiliary equation (MAE) and generalized projective Riccati equations (GPREs) method have been employed for obtaining the desired oblique soliton solutions. The proposed methods successfully attain different structures of explicit solutions such as bright, dark, singular, and periodic solitary wave solutions. The occurrence of these results ensured by the limitations utilized is also exceptionally promising to additionally investigate the propagation of waves of finite depth. The latest found solutions with their existence criteria are considered. The 2D and 3D portraits are also shown for some of the reported solutions. From the graphical representations, it have been illustrated that the descriptions of waves are changed along with the change in fractional and obliqueness parameters.

Performing calculus: Asymmetric adaptive stimuli-responsive material for derivative control

Materials (e.g., brick or wood) are generally perceived as unintelligent. Even the highly researched “smart” materials are only capable of extremely primitive analytical functions (e.g., simple logical operations). Here, a material is shown to have the ability to perform (i.e., without a computer), an advanced mathematical operation in calculus: the temporal derivative. It consists of a stimuli-responsive material coated asymmetrically with an adaptive impermeable layer. Its ability to analyze the derivative is shown by experiments, numerical modeling, and theory (i.e., scaling between derivative and response). This class of freestanding stimuli-responsive materials is demonstrated to serve effectively as a derivative controller for controlled delivery and self-regulation. Its fast response realizes the same designed functionality and efficiency as complex industrial derivative controllers widely used in manufacturing. These results illustrate the possibility to associate specifically designed materials directly with higher concepts of mathematics for the development of “intelligent” material-based systems.

On superconvergence of Runge–Kutta convolution quadrature for the wave equation

The semidiscretization of a sound soft scattering problem modelled by the wave equation is analyzed. The spatial treatment is done by integral equation methods. Two temporal discretizations based on Runge–Kutta convolution quadrature are compared: one relies on the incoming wave as input data and the other one is based on its temporal derivative. The convergence rate of the latter is shown to be higher than previously established in the literature. Numerical results indicate sharpness of the analysis. The proof hinges on a novel estimate on the Dirichlet-to-Impedance map for certain Helmholtz problems. Namely, the frequency dependence can be lowered by one power of $$\left| s\right| $$ s (up to a logarithmic term for polygonal domains) compared to the Dirichlet-to-Neumann map.

The Impact of Anomalous Diffusion on Action Potentials in Myelinated Neurons

Action potentials in myelinated neurons happen only at specialized locations of the axons known as the nodes of Ranvier. The shapes, timings, and propagation speeds of these action potentials are controlled by biochemical interactions among neurons, glial cells, and the extracellular space. The complexity of brain structure and processes suggests that anomalous diffusion could affect the propagation of action potentials. In this paper, a spatio-temporal fractional cable equation for action potentials propagation in myelinated neurons is proposed. The impact of the ionic anomalous diffusion on the distribution of the membrane potential is investigated using numerical simulations. The results show spatially narrower action potentials at the nodes of Ranvier when using spatial derivatives of the fractional order only and delayed or lack of action potentials when adding a temporal derivative of the fractional order. These findings could reveal the pathological patterns of brain diseases such as epilepsy, multiple sclerosis, and Alzheimer’s disease, which have become more prevalent in the latest years.

Heading perception depends on time-varying evolution of optic flow

There is considerable support for the hypothesis that perception of heading in the presence of rotation is mediated by instantaneous optic flow. This hypothesis, however, has never been tested. We introduce a method, termed “nonvarying phase motion,” for generating a stimulus that conveys a single instantaneous optic flow field, even though the stimulus is presented for an extended period of time. In this experiment, observers viewed stimulus videos and performed a forced-choice heading discrimination task. For nonvarying phase motion, observers made large errors in heading judgments. This suggests that instantaneous optic flow is insufficient for heading perception in the presence of rotation. These errors were mostly eliminated when the velocity of phase motion was varied over time to convey the evolving sequence of optic flow fields corresponding to a particular heading. This demonstrates that heading perception in the presence of rotation relies on the time-varying evolution of optic flow. We hypothesize that the visual system accurately computes heading, despite rotation, based on optic acceleration, the temporal derivative of optic flow.

The impact of the Chebyshev collocation method on solutions of the time-fractional Black–Scholes

This paper presents a numerical solution of the temporal-fractional Black–Scholes equation governing European options (TFBSE-EO) in the finite domain so that the temporal derivative is the Caputo fractional derivative. For this goal, we firstly use linear interpolation with the $$(2-\alpha)$$ ( 2 - α ) -order in time. Then, the Chebyshev collocation method based on the second kind is used for approximating the spatial derivative terms. Applying the energy method, we prove unconditional stability and convergence order. The precision and efficiency of the presented scheme are illustrated in two examples.