Paper proposes an analytical pricing model for puttable bonds with credit risk.
problem Analytical pricing of puttable bonds with credit risk.
method Developed a 2-factor structural PDE model and derived analytical pricing formula under specific conditions.
result Derived analytical pricing formula for puttable bonds with credit risk.
Unified geometric perspectives on PDEs, torsion invariants, and moduli theory.
problem Index theory and analytic torsion of nonlinear PDEs.
method Microlocal sheaf theory, factorization algebras, Spencer hypercohomology.
result Unified geometric perspectives on PDEs, torsion invariants, and moduli theory.
In this work, we have presented a simple analytical approximation scheme for generic non-linear FBSDEs. By treating the interested system as the linear decoupled FBSDE perturbed with non-linear generator and feedback terms, we have shown that it is possible to carry out a recursive approximation to an arbitrarily highe…
Paper calibrates GARCH diffusion model for option pricing using PDE methods.
problem Lack of fast, semi-analytic solution for GARCH diffusion model option pricing.
method PDE-based finite difference solver for accurate calibrations.
result PDE calibration of GARCH diffusion model to SPX options.
We consider a specific type of nonlinear partial differential equations (PDE) that appear in mathematical finance as the result of solving some optimization problems. We review some existing in the literature examples of such problems, and discuss the properties of these PDEs. We also demonstrate how to solve them nume…
The paper presents a PDE method for xVA incorporation in financial derivatives.
problem Incorporating value adjustments (xVA) in financial derivative pricing.
method Analytical solution of PDEs in the Black-Scholes framework.
result New semi-closed formulas for xVA are derived and compared to Monte-Carlo and numerical methods.
Critical points of scale-invariant curvature energies in 4D are analytic.
problem Analyzing critical points of curvature energies in 4D manifolds.
method Applying Noether's theorem to identify conservation laws and lower order elliptic system of PDEs, then using integrability by compensation and interpolation theory.
result Critical points of scale-invariant curvature energies in 4D are analytic.
Paper discusses recent progress on fractional Laplacian in conformal geometry.
problem Fractional Laplacian in conformal geometry.
method Analytic and geometric approaches.
result Recent developments reported in both analytic and geometric perspectives.
Develops numerical methods for PDEs on hypergraphs and networks.
problem Solving PDEs on complex geometric structures like hypergraphs and networks.
method Hybrid finite element methods, focusing on hybrid discontinuous Galerkin methods.
result Derives numerical approximations for PDEs on hypergraphs and networks.
The paper solves PDEs from matrices with orthogonal columns, linking them to Hessian metrics and symmetric spaces.
problem Solving third order PDEs for strictly convex smooth functions.
method Geometric methods using Hessian metrics and symmetric spaces.
result Explicit solutions and a family of non-generic solutions with applications in Poisson geometry and Kahler structures.
Undergraduate proves Morse inequalities using Witten's method.
problem Proving Morse inequalities for smooth manifolds.
method Witten's approach, PDE theory, harmonic oscillators.
result Analytical proof of Morse inequalities for smooth manifolds.
Paper solves PDEs for optimal investment strategies in volatile markets.
problem Finding optimal investment strategies in volatile markets.
method Numerical methods using time-changed Bessel bridges.
result Solves PDEs for relative arbitrage opportunities in volatility-stabilized markets.
Proves a conjecture about Riemann surfaces using PDEs.
problem Griffiths' conjecture on holomorphic vector bundles on compact Riemann surfaces.
method Combines techniques from Uhlenbeck-Yau and Pingali's reduction to prove a system of PDEs.
result Analytic proof of Griffiths' conjecture on compact Riemann surfaces.
Survey shows degenerate elliptic equations have analytic properties despite low regularity.
problem Understanding analytic properties of degenerate elliptic equations.
method Explains why solutions of a specific degenerate elliptic equation are analytic.
result Solutions of a specific degenerate elliptic equation are analytic despite low regularity.
Analyzes surfaces minimizing mean curvature variation using PDEs.
problem Finding surfaces of minimum mean curvature variation.
method Develops an analytic theory using partial differential equations.
result Establishes existence and regularity of minimizers.
PINNs struggle with data-to-PDE inconsistencies, limiting their accuracy.
problem Data inconsistency in PINNs affects their accuracy and convergence.
method Systematic analysis of PINNs with varying data fidelity and residual errors.
result PINNs saturate at an error level dictated by data inconsistency.
New theory proves representability of PDE solutions without complex machinery.
problem Proving representability of PDE solutions using traditional methods is difficult.
method Developed a new model of derived differential geometry using C∞-bornological rings. result Representability of derived moduli stacks of PDE solutions naturally follows from an Artin-Lurie style theorem.
Physics-informed WNO learns PDE solutions without labeled data.
problem Data-hungry nature of WNO framework.
method Physics-informed WNO for learning PDE solutions.
result Validated and illustrated with four nonlinear systems.
PDE-based G-CNNs add geometric symmetries to CNNs without augmentation.
problem Designing CNNs with built-in symmetries like rotation.
method Formulate CNN layers as PDE solvers on homogeneous spaces.
result PDE-G-CNNs achieve better performance with fewer parameters.
Study on hypersurfaces in Einstein manifolds using Killing spinors.
problem Characterizing hypersurfaces in Einstein manifolds.
method Describes PDEs for induced spinors and proves embedding results.
result Embedding results for real analytic pseudo-Riemannian manifolds.
A general method for analytic inversion in integral geometry is proposed. All classical and some new reconstruction formulas of Radon-John type are obtained by this method. No harmonic analysis and PDE is used.
Introduces a new PDE involving differential forms for Kähler geometry.
problem Solving a unified PDE for various important equations in Kähler geometry.
method Introduces a fully nonlinear PDE with differential form Λ and proves solvability conditions.
result Generalizes previous works and proves a conjecture for the dHYM equation.
The paper explains FX option pricing in target zones with non-deterministic short rates.
problem FX option pricing in target zones with non-deterministic short rates.
method Analytical solution of the pricing PDE with series of elementary functions.
result European option prices can be expressed via fast converging series of elementary functions.
New method uses neural networks to solve PDEs without grid discretization.
problem Solving PDEs with boundary conditions efficiently and accurately.
method Combining neural networks with TFC to transform PDEs into unconstrained optimization problems.
result Deep TFC method provides closed-form, differentiable approximations of PDE solutions.
Many physical systems are described by partial differential equations (PDEs). Determinism then requires the Cauchy problem to be well-posed. Even when the Cauchy problem is well-posed for generic Cauchy data, there may exist characteristic Cauchy data. Characteristics of PDEs play an important role both in Mathematics …
We perform detailed computations of Lie algebras of infinitesimal CR-automorphisms associated to three specific model real analytic CR-generic submanifolds in C^9 by employing differential algebra computer tools -- mostly within the Maple package DifferentialAlgebra -- in order to automate the handling of the arising h…
FNO-DEQ solves steady-state PDEs as fixed points, outperforming traditional FNOs.
problem Lack of understanding in designing neural network architectures for PDEs.
method Proposes FNO-DEQ, a deep equilibrium architecture that solves steady-state PDEs as fixed points.
result FNO-DEQ outperforms FNO-based architectures in predicting solutions to steady-state PDEs.
Bayesian PINNs optimize loss weights for PDEs and data.
problem Optimizing loss weights in physics-informed neural networks.
method Laplace approximation for efficient model evidence computation.
result Unified Bayesian setting for PDEs and noisy measurements.
Survey on recent developments in isometric immersions using PDE techniques.
problem Analyzing isometric immersions with low Sobolev regularity.
method Compensated compactness and Coulomb-Uhlenbeck gauges.
result Weak continuity and stability of Gauss-Codazzi-Ricci equations.
We present an analytic approach to solve a degenerate parabolic problem associated to the Heston model, which is widely used in mathematical finance to derive the price of an European option on an risky asset with stochastic volatility. We give a variational formulation, involving weighted Sobolev spaces, of the second…
NNGP combines neural nets and GPs for function approximation and PDE solving.
problem Function approximation and solving PDEs with high accuracy and uncertainty quantification.
method Generalized NNGP with larger hyperparameters trained by ML, analytical covariance formula.
result Generalized NNGP outperforms GPs and deep NNs for both smooth and non-smooth functions.
Paper explores solving HJB equations using neural networks.
problem Solving high-dimensional time-dependent HJB equations.
method Neural Galerkin methods with nonlinearly parametrized trial functions.
result Closed-form solutions for trial functions.
Robust PDE method for path-dependent Asian-style options using MPDATA.
problem Valuation of path-dependent Asian-style options.
method Non-oscillatory forward-in-time second-order MPDATA finite-difference scheme for solving 2D PDEs.
result MPDATA scheme improves solution over first-order upwind step, highlighting its importance.
We study a fully nonlinear PDE involving a linear combination of symmetric polynomials of the Kähler form on a Kähler manifold. A C0 \emph{a priori} estimate is proven in general and a gradient estimate is proven in certain cases. Independently, we also provide a method-of-continuity proof via a path of Kähler metri…
Abstract geometric structures flow harmonically.
problem Geometric structures on Riemannian manifolds.
method Twistorial interpretation and abstract harmonicity condition.
result Established analytic properties of geometric gradient flow.
Interdisciplinary study linking potential theory and elliptic PDEs.
problem Understanding solutions to nonlinear elliptic PDEs.
method Combining geometric and potential theory approaches.
result Validity of comparison principle and existence/uniqueness of solutions.
Analytic saddle spheres in S^3 are equators.
problem Characterizing saddle-shaped minimal surfaces in 3-sphere.
method Purely geometric approach, no PDE imposed.
result Analytic saddle spheres in S^3 are equators.
The paper develops a comprehensive valuation method for OTC claims that considers credit and funding risks.
problem Valuation of Over-The-Counter (OTC) claims that incorporate credit and funding liquidity risks.
method Develops a holistic approach using nonlinear mathematical models (semilinear PDEs and FBSDEs) and provides an analytical solution for the benchmark claim.
result An analytical solution for the benchmark claim is derived and expressed in terms of the Black-Scholes formula with dividends.
Novel IMEX scheme solves financial PDEs with mixed derivatives.
problem Numerical approximations for financial PDEs with mixed derivatives.
method Second order finite volume IMEX Runge-Kutta scheme.
result Achieves true second order convergence with non-regular initial conditions.
Study portfolio optimization with an exponential utility function and illiquid asset.
problem Optimizing a portfolio with a risk-free, liquid, and illiquid risky asset.
method Analytical substitution, Lie algebraic reduction, solving PDEs.
result Different optimization results for exponential utility function compared to HARA.
New method recovers PDEs from noisy data, even when conditions are violated.
problem Discovering PDEs from noisy, limited data.
method Randomized adaptive Lasso integrated into DeepMod.
result Recovery of PDEs with higher noise-to-sample ratios and single hyperparameters.
We use a path integral approach for solving the stochastic equations underlying the financial markets, and we show the equivalence between the path integral and the usual SDE and PDE methods. We analyze both the one-dimensional and the multi-dimensional cases, with point dependent drift and volatility, and describe a c…
Develops VPINNs for solving PDEs with reduced training cost and improved accuracy.
problem Solving partial differential equations efficiently and accurately.
method Integrates variational forms of PDEs into neural network loss functions, using Legendre polynomials as test spaces.
result VPINNs outperform PINNs in terms of accuracy and speed for solving PDEs.
We provide analytical pricing formula of corporate defaultable bond with both expected and unexpected default in the case with stochastic default intensity. In the case with constant short rate and exogenous default recovery using PDE method, we gave some pricing formula of the defaultable bond under the conditions tha…
The paper proves a local existence theorem for a CR torsion flow in pseudohermitian manifolds.
problem Existence of solutions to the CR torsion flow in pseudohermitian manifolds.
method Analytic partial differential equations approach.
result A unique smooth solution exists in a small time interval for the CR torsion flow.
We prove that a smooth Riemannian manifold admitting an imaginary generalized Killing spinor whose Dirac current satisfies an additional algebraic constraint condition can be embedded as spacelike Cauchy hypersurface in a smooth Lorentzian manifold on which the given spinor extends to a null parallel spinor. This is in…
A new sampling algorithm speeds up Langevin sampling for multimodal distributions.
problem Efficient sampling from multimodal distributions in Bayesian inference.
method Birth-death mechanism applied to Langevin diffusion.
result The algorithm accelerates mixing of Langevin diffusion, independent of potential barriers.
Analytical formula and Newton's method compared for nonlinear Black-Scholes equations.
problem Solving nonlinear Black-Scholes parabolic equations with market illiquidity and risk factors.
method Comparison of analytical approximation formula and Newton's method.
result Accuracy and time complexity of both methods compared using market data.