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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,786 papers · 148 categories

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48 results for derived schemes

Strictification of isotropic distributions on derived schemes with shifted symplectic forms.

problem Understanding isotropic distributions on derived schemes with specific symplectic structures.
method Proving strictification result for isotropic distributions on derived schemes equipped with negatively shifted homotopically closed 2-forms.
result Derived schemes with 2-2-shifted symplectic structures globally admit Lagrangian distributions.

Continues work on derived manifolds and symplectic schemes, constructing virtual classes.

problem Constructing virtual fundamental classes for derived manifolds and schemes.
method Cosection localization, reduced virtual fundamental classes, and applications to Donaldson-Thomas theory.
result Virtual fundamental classes for (2)(-2)-shifted symplectic derived schemes are consistent with algebraic and differential geometric constructions.

Novel weak MLMC scheme for Lévy-driven SDEs, applied to financial derivatives pricing.

problem Approximating solutions to Lévy-driven SDEs for financial derivatives pricing.
method Weak multilevel Monte-Carlo scheme with state space discretization of Lévy processes.
result Efficient approximation of financial derivatives pricing models.

A new chaotic financial system is proposed by considering ethics involvement in a four-dimensional financial system with market confidence. A five-dimensional conformable derivative financial system is presented by introducing conformable fractional calculus to the integer-order system. A discretization scheme is propo…

2019-03-11abs ↗pdf ↗

Paper derives CLT for Bayesian neural networks trained with variational inference.

problem Analyzing the fluctuation behavior of Bayesian neural networks trained with different variational inference schemes.
method Rigorous derivation of CLT for three variational inference schemes: idealized, Bayes-by-Backprop, and Minimal VI.
result Minimal VI scheme has larger variances but is more computationally efficient.

This paper summarizes closed-form relations for SE(3) maps and their derivatives.

problem Closed-form expressions for SE(3) maps and their derivatives are scattered in the literature.
method Summarizes and provides proofs for relevant closed-form relations of the exponential and Cayley map on SE(3).
result Provides an implicit generalized-alpha scheme for rigid/flexible multibody systems using the Cayley map.

Derives local energy equation and proves consistency of staggered finite volume schemes for Euler equations.

problem Preserving conservation and consistency in staggered finite volume methods for Euler equations.
method Staggered discretization, material velocity upwinding, internal energy balance with correction term.
result Derives local total energy equation and proves schemes are conservative and consistent.

This paper proposes a new method to learn integration schemes for complex ODEs.

problem Learning efficient integration schemes for non-linear ODEs and their identification.
method A novel framework to learn integration schemes that minimize an integration-related cost function.
result The proposed learning-based approach provides integration schemes close to analytical solutions.

AES scheme improves Bermudan and American option pricing for Heston models.

problem Pricing Bermudan and American options under Heston models efficiently.
method AES scheme using non-central chi-square distribution for variance process.
result AES achieves higher accuracy and computational efficiency for Bermudan options.

Real-world large-scale datasets usually contain noisy labels and are imbalanced. Therefore, we propose derivative manipulation (DM), a novel and general example weighting approach for training robust deep models under these adverse conditions. DM has two main merits. First, loss function and example weighting are commo…

2019-05-27abs ↗pdf ↗

DSoftKI scales GP regression with full derivative observations.

problem Efficiently fitting and predicting full derivative observations in Gaussian Processes.
method Extends SoftKI by using local temperature vectors for interpolation, enabling encoding of local directional sensitivity.
result DSoftKI achieves accurate predictions and scales to larger datasets with full derivative observations.

Efficient simulation scheme for rough Heston model reduces computational cost.

problem Accurate and efficient simulation of the rough Heston model for option pricing.
method Weak simulation scheme based on Markovian approximations of the rough Heston process.
result The new scheme exhibits second order weak convergence with linear computational cost.

The paper introduces μμK-stability for polarized schemes and develops equivariant calculus.

problem The existence of μμ-cscK metrics and their stability.
method Develops equivariant calculus and introduces μμ-character to study μμK-stability.
result Derives μμ-Futaki invariant and an equivariant first Chern class for general test configurations.

Bayesian models that mix multiple Dirichlet prior parameters, called Multi-Dirichlet priors (MD) in this paper, are gaining popularity. Inferring mixing weights and parameters of mixed prior distributions seems tricky, as sums over Dirichlet parameters complicate the joint distribution of model parameters. This paper s…

2017-08-17abs ↗pdf ↗

Tackling climate change is at the top of many agendas. In this context, emission trading schemes are considered as promising tools. The regulatory framework for an emission trading scheme introduces a market for emission allowances and creates a need for risk management by appropriate financial contracts. In this work,…

2010-11-26abs ↗pdf ↗

Compact scheme solves American put options with regime-switching using finite differences and Hermite interpolation.

problem Pricing American put options with regime-switching model.
method Logarithmic transformation, compact finite difference scheme, Hermite interpolation.
result The scheme provides an accurate and fast solution compared to other methods.

The Runge-Kutta-Legendre scheme improves pricing American options and other derivatives.

problem Pricing American options and other derivatives with improved accuracy and stability.
method Runge-Kutta-Legendre finite difference scheme applied to Black-Scholes and Heston models.
result Improved convergence and stability compared to existing schemes.

New simulation method simplifies Heston model with Poisson conditioning for better accuracy and efficiency.

problem Computational expense in exact simulation schemes for Heston model.
method Proposes a new exact simulation scheme without modified Bessel function evaluations, leveraging conditional integrated variance simplification.
result Good performance in terms of accuracy, efficiency, and reliability compared to existing methods.

Study pricing derivatives in markets with long-range dependence and jumps.

problem Deriving pricing formulas for derivatives in markets with long-range dependence and jumps.
method Developed a fractional integro-partial differential equation (PIDE) and used semigroup theory and finite-difference schemes for numerical solutions.
result Closed-form pricing formula for European options and numerical solution for general options.

This paper uses Malliavin calculus to price and compute delta of financial derivatives in jump-diffusion models.

problem Pricing and delta computation of financial derivatives in jump-diffusion models with stochastic intensity.
method Utilizes Malliavin calculus to price and compute delta, applying the Euler scheme for convergence analysis.
result Established the convergence of approximated solution, financial derivative, and its delta Greeks.

Model financial market with fundraiser and stock, derive option prices.

problem Derive option prices in a market with a fundraiser and multiple solutions to the Black-Scholes equation.
method Model financial market with two types of agents, use Pitman's theorem for Bessel process, derive option prices using numerical scheme.
result Derive option prices for European options and call options in a market with a bubble.

Extends JKO scheme for iterative algorithms with unknown parameters.

problem Computational and statistical analysis of iterative algorithms with unknown parameters.
method Develops statistical methods to estimate unknown parameters and adapts JKO scheme.
result Establishes asymptotic theory for the statistical JKO scheme.

The stability and robustness of compact schemes for parabolic PDEs are analyzed.

problem Stability and robustness of compact schemes for solving parabolic PDEs.
method Compact spatial discretization, Crank-Nicolson temporal discretization, eigenvalue analysis of amplification matrix.
result An upper bound on the condition number of the amplification matrix is derived, showing stability.

Enhances CEV model pricing with high-order scheme and adaptive time stepping.

problem Improving accuracy in pricing American CEV models with irregularities.
method High-order time adapted scheme, local mesh refinement, adaptive time stepping, fifth-order 5(4) Dormand-Prince method.
result Highly accurate solution with reduced computational runtime.

At present, there is an explosion of practical interest in the pricing of interest rate (IR) derivatives. Textbook pricing methods do not take into account the leptokurticity of the underlying IR process. In this paper, such a leptokurtic behaviour is illustrated using LIBOR data, and a possible martingale pricing sche…

2004-01-23abs ↗pdf ↗

A model structure is defined on the category of derived differentiable schemes, and it is used to analyse the truncation 2-functor from derived manifolds to d-manifolds. It is proved that the induced 1-functor between the homotopy categories is full and essentially surjective, giving a bijection between the sets of equ…

2012-12-05abs ↗pdf ↗