Study on ruin probabilities for Lévy processes with light-tailed jumps.
problem Determining bounds on ruin probabilities for Lévy processes.
method Analyzing the Laplace exponent of the Lévy process to find bounds on ruin probabilities.
result Identification of a new case not previously considered in the literature.
Study on ruin probability with investment in risky assets modeled as semimartingales.
problem Analyzing ruin probability in a business process with investment in risky assets.
method Investigates ruin probability with investment in a Lévy process and semimartingale return, deriving upper bounds and conditions for ruin.
result Upper bounds on ruin probabilities decrease as a power function with increasing initial capital, and these bounds are asymptotically optimal.
This paper presents generalized momentum mappings for covariant Hamiltonian field theories. The new momentum mappings arise from a generalization of symplectic geometry to LVY, the bundle of vertically adapted linear frames over the bundle of field configurations Y. Specifically, the generalized field momentum obs…
The paper optimizes utility for switching models using Lévy processes.
problem Maximizing HARA utilities in Lévy switching models.
method Dual method, f-divergence minimal martingale measures, Hellinger and Kulback-Leibler processes.
result Expressions for optimal strategies and maximal expected utilities.
The paper defines and analyzes Poissonian occupation times for negative Lévy processes.
problem Analyzing the time spent below zero for Lévy processes with interruptions.
method Introduces Poissonian occupation times for spectrally negative Lévy processes.
result Extends results on continuous observation to interrupted observation.
Let M be a manifold, V be a vector field on M, and B be a Banach space. For any fixed function f:M→B and any fixed complex number λ, we study Hyers-Ulam stability of the global differential equation Vy=λy+f.
The optimal dividend problem by De Finetti (1957) has been recently generalized to the spectrally negative Lévy model where the implementation of optimal strategies draws upon the computation of scale functions and their derivatives. This paper proposes a phase-type fitting approximation of the optimal strategy. We con…
The study finds sparse sets that uniquely determine metrics on negatively curved manifolds.
problem Determining metrics on negatively curved manifolds using spectral data.
method Analyzing conjugacy classes and marked length spectra.
result Sparse sets exist that uniquely determine metrics on negatively curved manifolds.
New proof shows certain 3D spaces are essentially like infinite space.
problem Characterizing 3D spaces with non-negative Ricci curvature.
method Integrable Ricci curvature, Sobolev inequality, spectral non-negativity.
result Proves complete Riemannian 3-manifolds are diffeomorphic to R3. In this note we give, for a spectrally negative Levy process, a compact formula for the Parisian ruin probability, which is defined by the probability that the process exhibits an excursion below zero, with a length that exceeds a certain fixed period r. The formula involves only the scale function of the spectrally ne…
The study proves Strichartz and spectral projection theorems on specific types of curved surfaces.
problem Proving Strichartz and spectral projection theorems on curved surfaces.
method Using large negative curvature neighborhoods, the study proves theorems on asymptotically conic and Euclidean ends surfaces.
result The study proves theorems without loss of interval on specific types of curved surfaces.
Sharp spectral estimates for negatively curved foliations.
problem Estimating the bottom of the spectrum of Riemannian foliations.
method Analyzing the normal exponential map and using it to derive spectral estimates.
result Sharp estimates for the bottom of the spectrum of Riemannian foliations.
Proposes RNSE for clustering with adaptive similarity matrix learning.
problem Sub-optimal results due to mismatch between stages in Spectral Clustering.
method End-to-end single-stage learning with adaptive similarity matrix and non-negative constraints.
result Superior clustering performance on synthetic and real-world datasets.
Paper generalizes spectral embedding for better graph interpretation.
problem Modeling heterophilic connectivity and negative eigenvalues in graph data.
method Generalized latent position network model (Random Dot Product Graph).
result Consistent latent position estimates with asymptotically Gaussian error.
This paper considers magnitude, asymptotics and duration of drawdowns for some Lévy processes. First, we revisit some existing results on the magnitude of drawdowns for spectrally negative Lévy processes using an approximation approach. For any spectrally negative Lévy process whose scale functions are well-behaved at …
Paper calculates the distribution of time spent below zero in risk models.
problem Analyzing time spent below zero in risk models.
method Analytical expressions for the distribution of occupation times.
result Improved understanding of risk processes by providing distribution formulas.
Better spectral partitioning of signed graphs using standard Laplacian.
problem Meaningless partitioning using signed Laplacian eigenvectors.
method Use standard graph Laplacian for spectral partitioning.
result Fiedler vector of standard Laplacian is easier to compute and more beneficial.
The optimal capital structure model with endogenous bankruptcy was first studied by Leland (1994) and Leland and Toft (1996), and was later extended to the spectrally negative Levy model by Hilberink and Rogers (2002) and Kyprianou and Surya (2007). This paper incorporates the scale effects by allowing the values of ba…
Study optimizes dividend strategies for risk processes with Lévy jumps.
problem Optimizing dividend payments in risk processes with Lévy jumps.
method Analyzes spectrally positive and negative Lévy processes, using scale functions.
result Periodic barrier strategy is optimal for spectrally negative Lévy processes with completely monotone Lévy density.
The paper finds optimal threshold strategies for insurance companies with a positive terminal value at creeping ruin.
problem Optimizing dividend payments in an insurance company's surplus process with a positive terminal value at creeping ruin.
method Using fluctuation theory, the paper derives explicit formulas for the objective function and shows the optimality of threshold strategies.
result Threshold strategies are optimal for the dividend optimization problem under certain conditions.
Optimal dividend strategy found for risk models with regime switching.
problem Optimal dividend strategy for spectrally negative Markov additive models with regime switching.
method Introduced an auxiliary problem and transformed the original problem into a local optimization problem.
result The refraction-reflection strategy with regime-modulated thresholds is optimal.
A new method using negative-shifted gradient descent improves overparameterized linear regression by avoiding structural limitations of negative ridge endpoints.
problem Structural limitations of negative ridge endpoints in overparameterized linear regression.
method Negative-shifted gradient descent, which avoids the pole constraint of negative ridge endpoints.
result The method improves over all admissible endpoints by a polynomial factor in risk under explicit conditions.
In this paper we analyze so-called Parisian ruin probability that happens when surplus process stays below zero longer than fixed amount of time ζ>0. We focus on general spectrally negative Lévy insurance risk process. For this class of processes we identify expression for ruin probability in terms of some other quan…
Researchers find spectral gaps in quantum flag manifolds using twisted operators.
problem Finding spectral gaps in quantum flag manifolds.
method Tensoring Laplace and Dolbeault-Dirac operators with negative Hermitian holomorphic modules.
result Twisting Dirac and Laplace operators by negative line bundles produces a spectral gap for q close to 1.
We introduce a class of interest rate models, called the α-CIR model, which gives a natural extension of the standard CIR model by adopting the α-stable L{é}vy process and preserving the branching property. This model allows to describe in a unified and parsimonious way several recent observations on the sovereign …
This paper optimizes periodic dividend strategies for Lévy processes with transaction costs.
problem Maximizing dividends for spectrally negative Lévy processes with fixed transaction costs.
method Using periodic strategies and fixed transaction costs, the paper calculates the value function and shows optimality conditions.
result A sufficient condition for optimality is that the Lévy measure is completely monotonic.
Study shows excess-loss reinsurance is optimal for insurers under mean-variance criterion.
problem Optimizing reinsurance strategies for insurers under mean-variance criterion.
method Analyzes excess-loss reinsurance under a spectrally negative Lévy insurance model using expected value premium principle and Hamilton-Jacobi-Bellman equation.
result Excess-loss reinsurance is the unique equilibrium strategy under the mean-variance criterion.
The paper provides a representation for dynamic risk measures and capital allocations.
problem Representation of dynamic risk measures and capital allocations under Itô-Lévy model.
method Representation theorem for dynamic capital allocation derived from BSDEs with quadratic-exponential growth.
result Derivation of a capital allocation representation for dynamic entropic risk measure and static coherent risk measure.
New bounds on Bartnik mass for surfaces with non-negative first eigenvalue.
problem Bounding Bartnik mass for surfaces with spectral non-negativity condition.
method Proving upper bound on Bartnik mass using spectral non-negativity condition.
result Bounded above by √(|S²|_g/16π) under spectral non-negativity.
The Wiener-Hopf factorization is obtained in closed form for a phase type approximation to the CGMY Lévy process. This allows, for the approximation, exact computation of first passage times to barrier levels via Laplace transform inversion. Calibration of the CGMY model to market option prices defines the risk neutral…
Optimal estimates for spectral projection norms on compact manifolds.
problem Estimating norms of spectral projection operators on compact manifolds.
method Analyzing spectral windows with logarithmic growth and applying curvature constraints.
result Optimal estimates for L2(M)oLq(M) norms are derived, saturating on flat or negatively curved manifolds. Researchers calculate the price of a perpetual put option in Lévy models.
problem Calculating the price of a perpetual American put option in Lévy models.
method Derive the explicit price using geometric spectrally negative Lévy processes and optimal threshold.
result The optimal exercise time is the first epoch when the asset price drops below an optimal threshold.
New method uses geometric mean of Laplacians for better clustering of signed networks.
problem Existing spectral clustering methods for signed networks fail in noisy conditions.
method Proposes using geometric mean of Laplacians of positive and negative networks.
result Geometric mean outperforms arithmetic mean in recovering ground truth clustering.
Study optimal stopping for American call options with random time-horizon in Lévy models.
problem Optimal stopping of American call options in random time-horizon under Lévy models.
method Model random time-horizon as Omega default clock, analyze value function under different q and y. result Different values of q and y lead to various optimal strategies (up-crossing, two-sided exit). In this paper we consider the optimal dividend problem for an insurance company whose risk process evolves as a spectrally negative Lévy process in the absence of dividend payments. The classical dividend problem for an insurance company consists in finding a dividend payment policy that maximizes the total expected di…
New Bethe-Hessian method improves community detection in sparse networks.
problem Detect communities in sparse networks efficiently.
method Spectral clustering using the Bethe-Hessian matrix.
result Bethe-Hessian consistently estimates block number above Kesten-Stigum threshold.
Regularized spectral methods improve clustering in signed graphs, especially for sparse data.
problem Clustering signed graphs with positive and negative edges.
method Developed regularized versions of SPONGE and Signed Laplacian methods for clustering signed graphs, especially for sparse data.
result Theoretical guarantees and empirical performance improvements for clustering signed graphs, especially in sparse regimes.
Study revisits Leland-Toft model with Poisson observation intervals.
problem Optimal capital structure under discrete asset value updates.
method Spectrally negative Lévy model with Poisson observation process.
result Optimal bankruptcy strategy and capital structure derived.
This paper studies game-type credit default swaps that allow the protection buyer and seller to raise or reduce their respective positions once prior to default. This leads to the study of an optimal stopping game subject to early default termination. Under a structural credit risk model based on spectrally negative Le…
Study connects spectral properties to frame flows on curved manifolds.
problem Spectral properties and frame flows on curved manifolds.
method Link between spectral properties, frame flows, and polynomial maps between spheres.
result Ergodicity of frame flows on low-rank bundles.
Optimal stopping strategy for a Lévy process near its supremum.
problem Predicting optimal stopping distance for a Lévy process.
method Characterization using scale functions and threshold analysis.
result Non-trivial stopping strategy based on a threshold.
The paper compares spectral geometry in hyperbolic and spherical manifolds.
problem Understanding spectral geometry in spherical manifolds.
method Survey of known results and open problems.
result Analogous results hold in hyperbolic manifolds but not necessarily in spherical manifolds.
Mini-batch SGD with momentum is a fundamental algorithm for learning large predictive models. In this paper we develop a new analytic framework to analyze noise-averaged properties of mini-batch SGD for linear models at constant learning rates, momenta and sizes of batches. Our key idea is to consider the dynamics of t…
New method clusters signed graphs using matrix power means.
problem Clustering signed graphs with positive and negative relations.
method Signed Power Mean Laplacian, defined as matrix power mean of normalized standard and signless Laplacians.
result Signed power mean Laplacian captures ground truth clusters under reasonable settings.
Researchers approximate spectral targets on manifolds with constant negative curvature.
problem Prescribing an arbitrary finite portion of the Laplace-Beltrami spectrum on manifolds of constant negative curvature.
method Constructing macroscopically heterogeneous hyperbolic covering manifolds in d≥3 and using discrete spectral limit theorems in d=2. result Any finite strictly increasing target list can be approximated to arbitrary precision by a closed manifold of constant negative curvature.
On curved spaces, viscous fluids reach equilibrium quickly.
problem Thermalization of viscous fluids on negatively curved manifolds.
method Stochastic Navier-Stokes equations with kinematically selected deformation Laplacian.
result Exponential thermalization rate of $2νλ_\Def$.
Study improves understanding of Ricci curvature in manifolds.
problem Understanding Ricci curvature in manifolds with specific assumptions.
method Exploring m-intermediate Ricci curvature and proving comparison theorems.
result Stable weighted slicing in manifolds with non-negative m-intermediate Ricci curvature has almost non-negative Ricci curvature.
Geodesic balls with non-negative Ricci curvature have a sharp lower bound on their first Dirichlet eigenvalue.
problem Finding a sharp lower bound for the first Dirichlet eigenvalue of geodesic balls.
method Quantitative explicit inequality linking the width of geodesic balls to the spectral gap.
result A quantitative inequality relating the width of geodesic balls to the spectral gap between the first Dirichlet eigenvalue and its lower bound.