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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.

168,742 papers · 148 categories

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275380106 · May 202619922001200920172026
48 results for price jumps

Simplifies pricing options in jump-diffusion models using gauge transformations.

problem Pricing European options in affine jump-diffusion models.
method Gauge transformation in the dual space to reduce to diffusion model pricing.
result A general procedure for calculating ΦΦ and applications in pricing and estimation.

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.

In order to understand the origin of stock price jumps, we cross-correlate high-frequency time series of stock returns with different news feeds. We find that neither idiosyncratic news nor market wide news can explain the frequency and amplitude of price jumps. We find that the volatility patterns around jumps and aro…

2008-03-12abs ↗pdf ↗

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.

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 uses entropy to derive stock price dynamics and option valuation.

problem Deriving stock price dynamics and option valuation from information constraints.
method Develops an entropic inference framework to derive stochastic processes from information constraints, representing price changes through two channels: continuous and jump.
result The derived dynamics is the Merton jump diffusion, with Geometric Brownian Motion as the no jump limit.

Paper develops semi-analytic method for American options in time-dependent jump-diffusion models.

problem Pricing American options in models with time-dependent and exponential jumps.
method Generalizes existing methods for barrier and American options to handle arbitrary time dependencies and solves the problem through algebraic and Fredholm-Volterra equations.
result Presents a semi-analytic solution for American options in time-dependent jump-diffusion models with exponential jumps.

This research improves option pricing models using Heston, GARCH, and jump diffusion models.

problem Inaccurate option pricing due to Black-Scholes assumptions.
method Monte Carlo simulation, GARCH model, Heston model, Merton jump-diffusion model.
result Heston model produces estimates closer to market prices, Merton model performs well for volatile assets, GARCH model improves volatility forecasts.

The paper prices and replicates various financial contracts on a risky asset with stochastic volatility and jumps.

problem Pricing and replicating financial contracts on assets with stochastic volatility and jumps.
method Develops pricing and hedging formulas for various financial contracts, independent of the volatility process dynamics.
result Pricing and hedging formulas for financial contracts are derived without dependence on the volatility process dynamics.

Study on pricing rules for income streams with partial insider information.

problem Determining the value of partial information in pricing rules for income streams.
method Analyzes three types of agents with varying levels of jump information and derives explicit state price densities.
result Explicit formulas for pricing rules with different levels of jump information are provided.

Study near-maturity convergence rates of American put prices in Lévy models.

problem Analyzing convergence rates of optimal exercise prices in Lévy models.
method Examined two settings: jumps of unbounded and bounded variation, deriving near-maturity expansions.
result Near-maturity convergence rate of optimal exercise price is of order √(T-t).

The paper extends the market price of risk for electricity swap contracts, incorporating jump risk.

problem Pricing electricity swap contracts with consideration of jump risk.
method Introducing a Merton type model with jumps and transferring to the physical measure, comparing arithmetic and geometric averaging.
result A decomposition of swap's market price of risk into classical and market price of risk components.

Study geometric step options with jumps, deriving pricing equations and characterizations.

problem Pricing geometric step options in markets with jumps.
method Symmetry and parity relations, partial integro-differential equations, ordinary integro-differential equations.
result Derive semi-analytical pricing results for geometric step options.

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.

Non-spanning identification of scheduled event risk in option pricing.

problem Separating continuous surface from scheduled jump in option pricing.
method Modeling FOMC decisions, CPI releases, and NFP reports as deterministic-time jumps in risk-neutral option pricing.
result Improves held-out event-spanning pricing with Gaussian and two-component mixture jumps.

Develops a PIDE framework for option pricing with stochastic volatility and jumps.

problem Option pricing under stochastic volatility and jumps.
method PIDE framework derived from Lévy-type process, implemented via finite-difference discretization with FFT for nonlocal jump operator, calibrated using GMM.
result Stochastic volatility accounts for most pricing improvement, reducing implied-volatility RMSE by 39% compared to Black-Scholes.

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.

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 ↗

Study uses neural networks to value Bitcoin options considering price jumps and sentiment.

problem Valuing Bitcoin options under price jumps and market sentiment.
method Bivariate jump-diffusion model, incorporating Google search sentiment, and artificial neural networks.
result Derives a closed formula for Bitcoin option pricing and validates using high-volatile stocks.

The paper models financial asset prices with jumps and evaluates European option prices using numerical methods.

problem Modeling and pricing European options with jumps in delayed stochastic systems.
method Existence, uniqueness, and positivity of solutions to delayed stochastic differential equations with jumps. Application of Fourier transformation for analytical pricing and Monte-Carlo simulation with a logarithmic Euler-Maruyama scheme for numerical approximation.
result The logarithmic Euler-Maruyama scheme provides a positive and convergent method for approximating the solution to the delayed stochastic differential equations with jumps.

Study parameter sensitivities in bond pricing models with jumps.

problem Analyzing the impact of parameters on bond pricing models with jumps.
method Theoretical analysis and MATLAB simulations of a Brownian motion and compound Poisson process.
result Explicit call price formula and verification of sensitivities.

The paper provides approximations for pricing Asian options using a mixed fractional Brownian motion with jumps.

problem Pricing Asian options under a mixed fractional Brownian motion with jumps.
method Approximate closed-form solutions for arithmetic Asian options and power options.
result Analytical formulas for pricing arithmetic Asian options and power options are derived.

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.

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.

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.

New framework analyzes pre-stock jump trading behaviors using multivariate time series analysis.

problem Understanding micro-trading behaviors before stock price jumps.
method Multivariate time series analysis considering temporal information.
result Identifies highly informative attributes for predicting price jumps.

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 ↗

We propose a model for hedging in a market with jumps for a large investor. The dynamics of the stock prices and the value process is governed by forward-backward SDEs driven by Teugels martingales. Unlike known FBSDE market models, ours accounts for jumps in stock prices. Moreover, it allows to find an optimal hedging…

2013-09-09abs ↗pdf ↗

The classical linear Black--Scholes model for pricing derivative securities is a popular model in financial industry. It relies on several restrictive assumptions such as completeness, and frictionless of the market as well as the assumption on the underlying asset price dynamics following a geometric Brownian motion. …

2019-01-19abs ↗pdf ↗

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.