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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.

168,657 papers · 148 categories

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48 results for jump term

A short-term pattern in LIBOR dynamics was discovered. Namely, 2-month LIBOR experiences a jump after Xmas. The sign and size of the jump depend on the data trend on 21 days before Xmas.

2019-08-27abs ↗pdf ↗

Cryptocurrency, the most controversial and simultaneously the most interesting asset, has attracted many investors and speculators in recent years. The visibly significant market capitalization of cryptos also motivates modern financial instruments such as futures and options. Those will depend on the dynamics, volatil…

2019-12-11abs ↗pdf ↗

A machine learning method for short-maturity options with jumps and stochastic volatility.

problem Short-maturity options with jumps and stochastic volatility.
method Differential machine learning method combining supervision and PIDE-residual penalty.
result Improves jump-term approximation and reduces Greeks errors compared to baselines.

New method for handling multi-dimensional singular controls with jump costs in mean-field problems.

problem Handling jump costs in multi-dimensional singular controls.
method Introducing two-layer parametrisations to interpolate jumps on both distributional and pathwise levels.
result Derivation of a DPP and characterisation of the value function as a minimal super-solution to a quasi-variational inequality.

New model estimates corporate defaults using pure jump processes, capturing extreme events.

problem Estimating corporate defaults using standard diffusion models that underestimate short-term probabilities.
method Introduced pure jump processes with negative jumps only, derived formulas, calibrated parameters, and implemented practical tools.
result Models redistribute credit risk towards shorter maturities, improving short-term default probability estimates.

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.

The paper predicts cryptocurrency prices using a path-dependent Monte Carlo simulation.

problem Forecasting cryptocurrency prices with volatility and jumps.
method Merton's jump diffusion model with machine learning, traditional, and statistical methods.
result Introduced a path-dependent Monte Carlo simulation for cryptocurrency price prediction.

This paper models CSI 300 index volatility using machine learning and addresses jump prediction.

problem Volatility modeling and jump prediction for high-frequency CSI 300 index data.
method Generalized Barndorff-Nielsen and Shephard model with machine learning algorithms for parameter estimation and forecast evaluation.
result Deterministic component of stochastic volatility processes can be captured over short and longer-term windows.

This paper develops a novel numerical method for pricing American options in a two-asset jump-diffusion model.

problem Pricing American options under correlated two-asset jump-diffusion models using finite difference methods often fails to preserve monotonicity and accurately discretize jump integrals.
method Introduces a novel monotone integration scheme to solve 2-D Partial Integro-Differential Equations (PIDEs) efficiently and accurately.
result The proposed method ensures convergence to the viscosity solution of the variational inequality and is both \ell_{\infty}-stable and consistent.

The model outperforms other models in option pricing, especially for short-term implied volatility.

problem Improper calibration and pricing of exotic options in financial models.
method Stochastic volatility model with double-exponential jumps, Fourier pricing techniques.
result The model outperforms other models in fitting the short-term implied volatility smile and pricing exotic options.

The paper introduces a new stochastic volatility model with long-term memory and jumps.

problem Developing a model for variance and volatility swaps with long-term memory and jumps.
method Fractional Barndorff-Nielsen and Shephard model incorporating long-term memory and jumps.
result Arbitrage-free prices for variance and volatility swaps derived for the new model.

Method detects jumps in high-frequency order prices using local minima.

problem Detecting jumps in high-frequency order prices with noisy data.
method Developed methods to estimate, locate and test for jumps using local minima of best ask quotes.
result Consistently estimated jump sizes and times, established asymptotic properties of tests, and demonstrated faster convergence rates.

A new method for pricing derivatives using self-exciting dynamics and finite-difference transforms.

problem Pricing derivatives with accumulated marks using a self-exciting marked point process.
method Derive discounted pricing equation as a PIDE, transform to one-dimensional PIDEs, use Laplace/Fourier transform, approximate jump term, solve using finite difference scheme.
result Efficiently price derivatives with accumulated marks using a novel finite-difference and transform approach.

Extends credit risky bond market models to include jumps and general semimartingales.

problem Modeling credit risky bonds with jumps and general semimartingales under minimal assumptions.
method Extends Heath-Jarrow-Morton approach to include jumps and generalizes recovery scheme.
result Derives generalized drift conditions for local martingale measures, ensuring no asymptotic free lunch.

A new method for pricing options with stochastic volatility and jumps.

problem Pricing options under stochastic volatility and jumps.
method Fourth-order compact finite-difference scheme with implicit-explicit Crank-Nicolson framework.
result The method achieves near-fourth-order spatial accuracy and up to two orders of magnitude lower runtime than quadratic finite elements.

Markov jump processes (MJPs) are used to model a wide range of phenomena from disease progression to RNA path folding. However, maximum likelihood estimation of parametric models leads to degenerate trajectories and inferential performance is poor in nonparametric models. We take a small-variance asymptotics (SVA) appr…

2015-03-01abs ↗pdf ↗

The paper solves complex swing option pricing equations with numerical methods.

problem Valuation of swing options with jumps under a mean-reverting model.
method Proposes second-order numerical methods to solve PIDEs convection-dominated and with nonlocal integral terms.
result Numerical methods confirm second-order convergence behavior.

The signature function of a knot is a locally constant integer valued function with domain the unit circle. The jumps (i.e., the discontinuities) of the signature function can occur only at the roots of the Alexander polynomial on the unit circle. The latter are important in deforming U(1) representations of knot group…

2003-10-14abs ↗pdf ↗

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 ↗

We use the database leak of Mt. Gox exchange to analyze the dynamics of the price of bitcoin from June 2011 to November 2013. This gives us a rare opportunity to study an emerging retail-focused, highly speculative and unregulated market with trader identifiers at a tick transaction level. Jumps are frequent events and…

2017-04-26abs ↗pdf ↗

We propose moment-based variational inference as a flexible framework for approximate smoothing of latent Markov jump processes. The main ingredient of our approach is to partition the set of all transitions of the latent process into classes. This allows to express the Kullback-Leibler divergence between the approxima…

2019-05-14abs ↗pdf ↗

This work models overnight rates with jumps and discontinuities, extending classical short-rate models.

problem Capturing the jump behavior and discontinuities in overnight rates for accurate modeling.
method Developed a term structure modeling framework based on overnight rates, accommodating stochastic discontinuities.
result Simple specifications can capture the jump behavior of overnight rates, and explicit valuation formulas are provided.

The paper presents a method for detecting jump sizes in crude oil prices.

problem Detecting jump sizes in crude oil price data.
method Sequential hypothesis testing using infinitesimal generators and super-solutions.
result The method improves the Barndorff-Nielsen and Shephard model for derivative and commodity market analysis.

We propose a new Directed Continuous-Time Random Walk (CTRW) model with memory. As CTRW trajectory consists of spatial jumps preceded by waiting times, in Directed CTRW, we consider the case with only positive spatial jumps. Moreover, we consider the memory in the model as each spatial jump depends on the previous one.…

2018-07-05abs ↗pdf ↗

In the present paper we present a finite element approach for option pricing in the framework of a well-known stochastic volatility model with jumps, the Bates model. In this model the asset log-returns are assumed to follow a jump-diffusion model where the jump component consists of a Levy process of compound Poisson …

2008-12-16abs ↗pdf ↗

The paper models cryptocurrency price and volatility with jumps and fractional volatility.

problem Empirical evidence shows jumps in cryptocurrency price and volatility.
method Fractional stochastic volatility model with jumps and short-term volatility dependency.
result Fractional stochastic volatility models outperform other models in pricing and hedging cryptocurrency options.

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.

The non-gaussianity of processes observed in financial markets and relatively good performance of gaussian models can be reconciled by replacing the Brownian motion with Levy processes whose Levy densities decay as exp(-lambda|x|) or faster, where lambda>0 is large. This leads to asymptotic pricing models. The leading …

2002-12-11abs ↗pdf ↗

We study the leading term in the small-time asymptotics of at-the-money call option prices when the stock price process SS follows a general martingale. This is equivalent to studying the first centered absolute moment of SS. We show that if SS has a continuous part, the leading term is of order T\sqrt{T} in time $…

2010-06-11abs ↗pdf ↗

Formula for option pricing in a stochastic volatility model with jumps.

problem Developing a formula for European option pricing in a complex stochastic volatility model.
method Fractional integral of a diffusion process, martingale representation, and Itô calculus for processes with jumps.
result A first-order approximation formula for option prices.

Unified model for equity option pricing and interest-rate risk assessment.

problem Pricing short and medium-term equity options and interest-rate risk.
method Developed a stochastic modeling framework using Heston, Bates, and CIR models, calibrated using Fourier inversion and FFT.
result Calibration stability and convergence of parameter sets across models.