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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.

169,181 papers · 148 categories

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123246369492 · Jun 202019922001200920182026
48 results for exponential Lévy processes

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.

This paper presents generalized momentum mappings for covariant Hamiltonian field theories. The new momentum mappings arise from a generalization of symplectic geometry to LVYL_VY, the bundle of vertically adapted linear frames over the bundle of field configurations YY. Specifically, the generalized field momentum obs…

2001-11-21abs ↗pdf ↗

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.

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.

The paper explores risk-minimization for exponential additive models, providing mathematical expressions and numerical examples.

problem Risk-minimization in incomplete markets for exponential additive models.
method Derive explicit mathematical expressions for local risk-minimization strategies in exponential additive models.
result Provide necessary conditions for deriving expressions and confirm integrability conditions for specific models.

Study optimal strategy for maximizing exponential utility in financial market with linear price impact.

problem Maximizing exponential utility in financial market with linear price impact.
method Purely probabilistic approach using duality.
result Computed optimal portfolio strategy and value for Ornstein-Uhlenbeck process.

Study optimizes inventory restocking for demand processes with exponential replenishment.

problem Optimizing inventory restocking for demand processes with exponential replenishment.
method Developed periodic barrier replenishment policies for spectrally positive Lévy demand processes.
result Optimal policies and value functions are concisely written in terms of scale functions.

Paper evaluates squared-exponential covariance function for Gaussian processes with integral observations.

problem Evaluating double line integrals of the squared exponential covariance function in Gaussian processes.
method Proposes a new approach to reduce double integrals to a single integral using the error function and efficiently computed with numerical techniques.
result Shows superior numerical robustness and accuracy compared to existing methods.

Develops European power option pricing under correlated interest rate and asset processes.

problem Pricing European power options under correlated interest rate and asset processes.
method Martingale method and Girsannov transform.
result Derives European power option pricing formulae under two market assumptions.

Optimizes spending by adjusting a discount factor modelled as an exponential CIR process.

problem Maximizing discounted spendings/dividend payments given an exponential CIR discounting factor.
method Analytical and numerical methods for deterministic and stochastic surplus processes.
result Explicit expressions for optimal strategies in deterministic cases, and constant-barrier strategies for small volatility in stochastic cases.

The study establishes conditions for stratified spaces to satisfy RCD(K, N) curvature-dimension condition.

problem Conditions for stratified spaces to satisfy RCD(K, N) curvature-dimension condition.
method Proves conditions for stratified spaces to satisfy RCD(K, N) using Ricci tensor bounds and cone angles.
result New examples of metric measure spaces satisfying RCD(K, N) curvature-dimension condition.

Study optimal stopping times for multi-dimensional processes with non-exponential discounting.

problem Optimal stopping in multi-dimensional processes with non-exponential discounting.
method Probabilistic potential theory to establish existence of optimal equilibria.
result Existence of optimal equilibria for multi-dimensional stopping problems.

Quantum systems with scrambling improve temporal information processing, but scaling requires exponential overhead.

problem Scalability and memory retention of quantum reservoirs in temporal information processing.
method Examined a quantum reservoir processing framework with scrambling reservoirs modeled by high-order unitary designs, analyzed in noiseless and noisy settings.
result Memory retention improves exponentially with reservoir size but worsens with reservoir iterations, requiring exponential shot overhead for scaling.

This paper sets baselines for reading comprehension benchmarks, finding simple models often perform well.

problem Understanding the difficulty of popular reading comprehension benchmarks.
method Established baselines for bAbI, SQuAD, CBT, CNN, and Who-did-What datasets.
result Simple models often outperform complex models on many benchmarks.

Paper explores duality in DPPs using embedding structure analysis.

problem Understanding the geometric structure of determinantal point processes.
method Analyzes the exponential family embedding of DPPs and uses the e-embedding curvature tensor.
result Discovers the duality between marginal and L-ensemble kernels.

New model captures time-varying volatility with stochastic exponential tails.

problem Capturing time-varying volatility and stochastic skewness in financial markets.
method Normal Tempered Stable distribution with time-varying parameter.
result Model better explains market option prices with stochastic exponential tails.

Develops quasi-likelihood analysis for marked point processes and applies it to Hawkes processes.

problem Analyzing multivariate marked point processes and their applications.
method Quasi-likelihood analysis for a general class of multivariate marked point processes, with focus on marked Hawkes processes.
result The quasi-likelihood analysis for marked Hawkes processes provides explicit conditions for ergodicity and Markovian transformation.

Modeling aggressive market order arrivals using Hawkes factor models.

problem Aggressive market order placements and their impact on stock prices.
method Bivariate marked Hawkes process with self-excitation and cross-excitation components.
result The Hawkes model with an exponential kernel produces better calibration than a monotonous exponential kernel.

Investigates stock models using tempered stable processes for option pricing.

problem Analyzing option pricing in stock models driven by tempered stable processes.
method Investigates exponential stock models driven by tempered stable processes, providing existence of equivalent martingale measures and pricing formulae.
result Existence of equivalent martingale measures and pricing formulae for European call options.

In a Markovian stochastic volatility model, we consider financial agents whose investment criteria are modelled by forward exponential performance processes. The problem of contingent claim indifference valuation is first addressed and a number of properties are proved and discussed. Special attention is given to the c…

2011-09-18abs ↗pdf ↗

Study compares exponential and power-law kernels in modeling high-frequency trading data.

problem Modeling high-frequency trading data with specific kernel types.
method Proposes and analyzes two bivariate Hawkes processes with exponential and power-law kernels.
result Identifies strengths and limitations of exponential and power-law kernels for high-frequency trading data.

Optimal insurance and investment strategy under exponential preferences in a correlated market model.

problem Optimal investment and reinsurance strategy for an insurance company under exponential preferences.
method Stochastic control techniques to construct a forward dynamic exponential utility and characterize the optimal strategy.
result Characterization of the optimal investment and reinsurance strategy in a correlated market model.

Extend classical theory of affine processes to path-dependent setting

problem Path-dependent affine processes
method Introduce path-dependent coefficients and provide analytic formulas for their Fourier--Laplace transform
result Define path-dependent affine processes through their exponential-affine Fourier--Laplace transform and establish a characterization theorem

Linear cost method approximates Gaussian Matérn processes with exponentially convergent accuracy.

problem High computational cost for Gaussian process inference and prediction.
method Optimal rational approximation of spectral density for Gaussian processes on bounded intervals.
result Exponential decrease in covariance error with increasing order of approximation.

New method reduces sample complexity for learning Ising model dynamics exponentially.

problem Learning binary graphical models from correlated samples produced by a dynamical process.
method Two estimators based on interaction screening objective and conditional likelihood loss.
result Sample complexity reduces exponentially for samples from a dynamical process far from equilibrium.

Introduces a new stationary GE-process for gold price analysis.

problem Analyzing gold price data with a flexible stationary process.
method Developed a new stationary GE-process with three parameters. Analyzed synthetic and real gold price data.
result Maximum likelihood estimators can be obtained for the unknown parameters.

Incorporates matrix exponential into generative flows for improved performance.

problem Improving generative flow models for better density estimation.
method Integrates matrix exponential into generative flows, proposing new layers and modifying network architecture.
result The proposed model achieves great performance on density estimation.