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arXiv research

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.

168,695 papers · 148 categories

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48 results for Jump conditions

Develops efficient methods for approximating densities of financial models with jumps.

problem Approximating densities of affine jump diffusions with state-independent jump intensities.
method Recursive approach for deriving closed-form solutions to moments, constructing density approximations via moment matching.
result Superior computational efficiency and precision in option pricing and simulation compared to existing techniques.

We investigate which jump-diffusion models are convexity preserving. The study of convexity preserving models is motivated by monotonicity results for such models in the volatility and in the jump parameters. We give a necessary condition for convexity to be preserved in several-dimensional jump-diffusion models. This …

2006-01-22abs ↗pdf ↗

Affine jump-diffusions constitute a large class of continuous-time stochastic models that are particularly popular in finance and economics due to their analytical tractability. Methods for parameter estimation for such processes require ergodicity in order establish consistency and asymptotic normality of the associat…

2018-10-31abs ↗pdf ↗

Study on interest rate model with jumps, proving strong convergence in simulations.

problem Analytical solutions for complex interest rate models with jumps are difficult.
method Employed truncated Euler-Maruyama techniques to prove strong convergence.
result Justified strong convergence for Monte Carlo calibration and valuation.

Quantum computer method for pricing lookback options with jumps.

problem Pricing lookback options with discrete monitoring and jump conditions.
method Variational Quantum Imaginary Time Evolution (VarQITE) method to solve non-Hermitian Schrodinger equation.
result Quantum algorithm can handle jump conditions in lookback options pricing.

We develop a comprehensive mathematical framework for polynomial jump-diffusions in a semimartingale context, which nest affine jump-diffusions and have broad applications in finance. We show that the polynomial property is preserved under polynomial transformations and Lévy time change. We present a generic method for…

2017-11-21abs ↗pdf ↗

In this paper we outline methodology to efficiently simulate (jump) diffusion bridge sample paths without discretisation error. We achieve this by considering the simulation of conditioned (jump) diffusion bridge sample paths in light of recent work developing a mathematical framework for simulating finite dimensional …

2015-05-12abs ↗pdf ↗

New framework for optimal transport with jumps over intermediate spaces.

problem Optimal transport with mass jumps over intermediate spaces.
method Hierarchical Jump multi-marginal transport (HJMOT) on Polish spaces.
result Existence and uniqueness of Monge solutions under sequential differentiability and twist condition.

Optimizes dynamic investment portfolios with correlated jumps.

problem Maximizing expected terminal wealth in a multivariate Merton model with dependent jumps.
method Approximating CVaR with comonotonic bounds and maximizing expected terminal wealth.
result Improved optimization of dynamic investment portfolios.

Masking diffusion outperforms other discrete diffusion models by incorporating jump times into the model.

problem Improving the performance of discrete diffusion models.
method Conditioning on the jump schedule of discrete Markov processes.
result Schedule-conditioned discrete diffusion (SCUD) models outperform classical and masking diffusion models.

Study on short-term behavior of ATM-IV for jump-diffusion model.

problem Analyzing the short-time behavior of ATM-IV for a specific stochastic volatility model.
method Used Malliavin Calculus techniques to derive expressions for ATM-IV level and skew.
result Short-time behavior of ATM-IV level is consistent for all pure-jump Lévy processes.

Neural Jump ODE improves continuous-time prediction and filtering of irregularly sampled time series.

problem Theoretical guarantees for continuous-time prediction and filtering of irregularly observed time series.
method Introducing Neural Jump ODE (NJ-ODE) that models conditional expectation between observations with neural ODEs and jumps.
result Theoretical guarantees for the L2L^2-optimal prediction are provided, showing convergence of model output to optimal prediction.

We study convexity and monotonicity properties of option prices in a model with jumps using the fact that these prices satisfy certain parabolic integro-differential equations. Conditions are provided under which preservation of convexity holds, i.e. under which the value, calculated under a chosen martingale measure, …

2005-09-10abs ↗pdf ↗

Neural Jump ODEs improve online filtering and classification with robust performance.

problem Online filtering and classification in settings with irregular and partial observations.
method Modeling conditional expectation using Neural Jump ODEs, with theoretical convergence guarantees.
result Demonstrated superior performance over classical methods, especially in complex scenarios.

Unified framework for efficient trans-dimensional Bayesian inference using VI and NFs.

problem Efficient trans-dimensional Bayesian inference with reduced computational cost.
method Variational inference with normalizing flows to train transport proposals.
result Our approach minimizes reverse KL divergence and reduces computational cost.

This paper estimates VaR for corn and soybean markets using jump processes.

problem Quantifying potential losses in commodity portfolios under market conditions.
method Modeling VaR for a diversified portfolio of corn and soybean positions with standard Brownian motions and jump processes.
result Compared VaR values in markets with and without jumps, providing insights for risk management.

Many time series are effectively generated by a combination of deterministic continuous flows along with discrete jumps sparked by stochastic events. However, we usually do not have the equation of motion describing the flows, or how they are affected by jumps. To this end, we introduce Neural Jump Stochastic Different…

2019-05-24abs ↗pdf ↗

Neural Lévy model improves risk and density forecasting for financial returns.

problem Financial returns exhibit heavy tails, volatility clustering, and jumps.
method Proposes a neural Lévy jump-diffusion framework that learns conditional drift, diffusion, jump intensity, and size distribution.
result Demonstrates improved calibration, sharper tail control, and risk reduction.

The paper studies horizontal semimartingales on Riemannian manifolds and their connections to Euclidean spaces.

problem Stochastic lifts and anti-developments of semimartingales on Riemannian manifolds.
method Using stochastic differential geometry with jumps, the paper establishes correspondences between discontinuous semimartingales and their lifts.
result The paper extends previous results to include geodesics and small jumps, enabling the construction of martingales from local martingales.

Study on non-negative solutions for stochastic Volterra equations with jumps.

problem Existence and uniqueness of non-negative solutions for stochastic Volterra equations with jumps and non-Lipschitz coefficients.
method Developed a nonnegative approximation approach and used Yamada--Watanabe approximation technique for convergence proof.
result Established conditions for strong existence and pathwise uniqueness of non-negative solutions.

Unified analytical tool for non-Markovian jump processes.

problem Analyzing history-dependent jump processes with non-Markovian behavior.
method Developed a standard form of master equations using Laplace-space embedding and asymptotic solution.
result Unified analytical toolset for general non-Markovian processes, leading to the GLE approximation.

Using a Levy process we generalize formulas in Bo et al.(2010) for the Esscher transform parameters for the log-normal distribution which ensure the martingale condition holds for the discounted foreign exchange rate. Using these values of the parameters we find a risk-neural measure and provide new formulas for the di…

2014-02-09abs ↗pdf ↗