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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.

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285683111 · May 202619922001200920172026
48 results for Levy density

Calibrating a Lévy process usually requires characterizing its jump distribution. Traditionally this problem can be solved with nonparametric estimation using the empirical characteristic functions (ECF), assuming certain regularity, and results to date are mostly in 1D. For multivariate Lévy processes and less smooth …

2018-12-20abs ↗pdf ↗

Efficient methods for Lévy models using SINH-regular processes.

problem Efficient numerical methods for evaluating Lévy models.
method Defining SL-processes and sSL-processes, deriving properties of characteristic exponent, and showing all popular Lévy processes can be subordinated to Brownian motion.
result All crucial properties of characteristic exponent are consequences of a specific representation, and all popular Lévy processes are SL- or sSL-subordinated Brownian motion.

We consider a defaultable asset whose risk-neutral pricing dynamics are described by an exponential Levy-type martingale subject to default. This class of models allows for local volatility, local default intensity, and a locally dependent Levy measure. Generalizing and extending the novel adjoint expansion technique o…

2013-12-27abs ↗pdf ↗

We consider a stochastic volatility model with Lévy jumps for a log-return process Z=(Zt)t0Z=(Z_{t})_{t\geq 0} of the form Z=U+XZ=U+X, where U=(Ut)t0U=(U_{t})_{t\geq 0} is a classical stochastic volatility process and X=(Xt)t0X=(X_{t})_{t\geq 0} is an independent Lévy process with absolutely continuous Lévy measure νν. Small-time expansio…

2010-09-21abs ↗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.

We develop a scale-invariant truncated Lévy (STL) process to describe physical systems characterized by correlated stochastic variables. The STL process exhibits Lévy stability for the probability density, and hence shows scaling properties (as observed in empirical data); it has the advantage that all moments are fini…

1999-06-25abs ↗pdf ↗

Analyzes first exit times in a modified Barndorff-Nielsen and Shephard model.

problem Analyzing first exit times in a modified Barndorff-Nielsen and Shephard model.
method Formulated an approximate model driven by Brownian motion and Lévy subordinator, analyzed first exit times of log-return process.
result First exit time process decomposes into Brownian motion and Lévy subordinator components.

New method extracts stochastic laws from data, including Lévy noise.

problem Extracting stochastic laws from data with non-Gaussian noise.
method Using normalizing flows to estimate transition density, then applying nonlocal Kramers-Moyal formulas.
result Can learn stochastic differential equations with Lévy motion.

The paper tackles drift identification in Lévy α-stable stochastic systems, proposing a Fourier space approach.

problem Estimating the drift field of a stochastic differential equation driven by Lévy α-stable noise.
method Fourier space approach, parameterizing the drift field using Fourier series, minimizing a loss function with gradients computed via the adjoint method.
result The method is capable of learning drift fields in qualitative and/or quantitative agreement with ground truth fields.

In this paper, we revisit the optimal periodic dividend problem, in which dividend payments can only be made at the jump times of an independent Poisson process. In the dual (spectrally positive Lévy) model, recent results have shown the optimality of a periodic barrier strategy, which pays dividends at Poissonian divi…

2017-08-04abs ↗pdf ↗

The paper studies geometric properties of hydrodynamical density manifolds.

problem Understanding the geometry of hydrodynamical density manifolds.
method Formulating connections, gradients, Hessians, parallel transports, and curvatures on these manifolds.
result Closed-form formulas for sectional curvatures in one-dimensional density manifolds.

We consider a general d-dimensional Levy-type process with killing. Combining the classical Dyson series approach with a novel polynomial expansion of the generator A(t) of the Levy-type process, we derive a family of asymptotic approximations for transition densities and European-style options prices. Examples of stoc…

2014-04-11abs ↗pdf ↗

We investigate the pricing of cliquet options in a jump-diffusion model. The considered option is of monthly sum cap style while the underlying stock price model is driven by a drifted Lévy process entailing a Brownian diffusion component as well as compound Poisson jumps. We also derive representations for the density…

2018-10-23abs ↗pdf ↗

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.

MAFLA improves sampling from heavy-tailed distributions using MH-inspired corrections.

problem Sampling from heavy-tailed and multimodal distributions when neither target nor proposal densities can be evaluated.
method Metropolis-Adjusted Fractional Langevin Algorithm (MAFLA) with Score Balance Matching.
result MAFLA significantly improves finite-time sampling accuracy over unadjusted fractional Langevin dynamics.

FourNet approximates financial transition densities using Fourier transforms.

problem Approximating transition densities in finance with high accuracy.
method FourNet is a novel FFNN with Gaussian activation, learning from characteristic functions.
result FourNet can approximate transition densities arbitrarily well with finite neurons.

We derive a small-time expansion for out-of-the-money call options under an exponential Levy model, using the small-time expansion for the distribution function given in Figueroa-Lopez & Houdre (2009), combined with a change of numéraire via the Esscher transform. In particular, we quantify find that the effect of a no…

2011-05-16abs ↗pdf ↗

New method handles complex systems with discontinuous, heavy-tailed noise.

problem Handling discontinuous, heavy-tailed Lévy noise in stochastic systems.
method Developed nonlocal Kramers-Moyal formulas for SDEs with multiplicative Lévy noise.
result Validated framework for discovering interpretable SDE models from data.

Protocol diagnoses neural HJB-PIDE solvers for Lévy jumps, revealing a missing factor in their importance-proposal density.

problem Neural PDE solvers can match scalar diagnostics but miscompute operators, leading to systematic errors.
method Five-step diagnostic protocol decomposes neural solve into components, compares them with independent reference solutions.
result Corrected a missing 1/2-mixture factor in the neural method's importance-proposal density, improving control accuracy.

Density expansions for hypoelliptic diffusions (X1,...,Xd)(X^1,...,X^d) are revisited. In particular, we are interested in density expansions of the projection (XT1,...,XTl)(X_T^1,...,X_T^l), at time T>0T>0, with ldl \leq d. Global conditions are found which replace the well-known "not-in-cutlocus" condition known from heat-kernel asymptot…

2011-11-10abs ↗pdf ↗

We obtain explicit representations of locally risk-minimizing strategies of call and put options for the Barndorff-Nielsen and Shephard models, which are Ornstein--Uhlenbeck-type stochastic volatility models. Using Malliavin calculus for Levy processes, Arai and Suzuki (2015) obtained a formula for locally risk-minimiz…

2015-03-30abs ↗pdf ↗

We analyze the Levy processes produced by means of two interconnected classes of non stable, infinitely divisible distribution: the Variance Gamma and the Student laws. While the Variance Gamma family is closed under convolution, the Student one is not: this makes its time evolution more complicated. We prove that -- a…

2007-02-02abs ↗pdf ↗

Proposes second-order Esscher transform for Lévy models in financial markets.

problem Risk management and quantification in markets with jumps and Lévy dynamics.
method Derives densities, equivalent measures, and pricing formulas for European call options.
result Option prices are bounded and monotonic with the second-order Esscher parameter.

Study uses AI to price exotic options with a new Levy process model.

problem Pricing exotic options with a non-Gaussian Levy process model.
method Introduced a new multivariate Levy process model and used a generative AI model to estimate the probability density function.
result Developed a method to price quanto options using a trained generative AI model.

The scaling properties of oil price fluctuations are described as a non-stationary stochastic process realized by a time series of finite length. An original model is used to extract the scaling exponent of the fluctuation functions within a non-stationary process formulation. It is shown that, when returns are measure…

2008-09-06abs ↗pdf ↗

Proposes a method for approximating transition densities of SDEs driven by gamma processes.

problem Calculating transition densities for SDEs driven by gamma processes.
method Taylor-type approximation and conditional expectation of multiple stochastic integrals.
result Efficiency of the proposed method demonstrated through numerical tests.

New geometric interpretation of Amari-Cencov α-connections on probability densities.

problem Geometric interpretation of Amari-Cencov α-connections on probability densities.
method Riemannian metrics and Levi-Civita connections.
result Geodesics of α-connections are energy-minimizing curves.

In this manuscript we analyse the leading statistical properties of fluctuations of (log) 3-month US Treasury bill quotation in the secondary market, namely: probability density function, autocorrelation, absolute values autocorrelation, and absolute values persistency. We verify that this financial instrument, in spit…

2007-06-08abs ↗pdf ↗

This study describes the Fisher-Rao metric on Gaussian measures in infinite-dimensional spaces.

problem Understanding the Fisher-Rao metric in infinite-dimensional Gaussian settings.
method Explicit description and generalization of finite-dimensional quantities to infinite-dimensional Hilbert spaces.
result The Fisher-Rao metric and related geometric quantities generalize from finite to infinite dimensions.

Gaussian processes are rich distributions over functions, with generalization properties determined by a kernel function. When used for long-range extrapolation, predictions are particularly sensitive to the choice of kernel parameters. It is therefore critical to account for kernel uncertainty in our predictive distri…

2018-02-02abs ↗pdf ↗

The paper proposes a method to learn evolving multivariate distributions from sample paths.

problem Learning the temporal evolution of multivariate densities from sample data.
method Normalizing flows to construct time-dependent mappings.
result The method can approximate evolving probability density functions from observed data.

Derives integral representations for a Lévy process and its extremum, hitting time, with fast evaluation.

problem Efficiently evaluating the joint probability density function of a Lévy process, its supremum, and hitting time.
method Integral representations, Laplace-Fourier transforms, summation by parts, conformal deformation, trapezoid rules, Gaver-Wynn-Rho algorithm.
result Explicit calculations and fast evaluation of the joint cpdf for Lévy processes.

In this paper we present a rather general phenomenological theory of tick-by-tick dynamics in financial markets. Many well-known aspects, such as the Lévy scaling form, follow as particular cases of the theory. The theory fully takes into account the non-Markovian and non-local character of financial time series. Predi…

2000-01-10abs ↗pdf ↗

Efficient algorithm for CMDPs reduces to offline density estimation.

problem Offline learning for CMDPs with horizon H.
method Reduction to offline density estimation, layerwise exploration-exploitation tradeoff.
result First efficient and near-optimal reduction from CMDPs to offline density estimation.