Research
On-device research index

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.

169,341 papers · 148 categories

Trend · papers per month

24487296 · May 202619922001200920182026
48 results for negative jumps

The paper extends optimal investment and consumption strategies to include jumps in asset prices.

problem Optimal investment and consumption with downside risk constraint in jump-diffusion models.
method Extends results to jump-diffusion setting, finds explicit optimal strategy under certain constraints.
result Explicit optimal strategy can be found in subset of admissible strategies under positive jumps.

The study reveals unspanned risks in equity option risk premiums, explaining negative premiums for certain options.

problem Explaining negative risk premiums for certain equity option types.
method Developed a decomposition of equity option risk premiums, operationalized the pricing kernel process, and incorporated unspanned risks.
result Empirical evidence supports the presence of unspanned risks, explaining negative risk premiums for certain options.

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.

Study on MMV in jump-diffusion models resolves MV's non-monotonicity issues.

problem Non-monotonicity and free cash flow stream problems in MV preferences.
method Explicit solution for MMV preferences in jump-diffusion models, proving non-negative potential measures.
result MMV resolves MV's non-monotonicity and free cash flow stream issues.

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 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).

Develops a fast and precise method to evaluate likelihood of jump-diffusion models.

problem Evaluating likelihood functions of models with stochastic volatility and jumps.
method Deterministic nonlinear filtering algorithm based on Kitagawa's method.
result Deterministic filtering is faster and more precise than particle filter.

This paper examines how the U.S.--China trade war affects stock markets, finding evidence of financial contagion and changes in risk channels.

problem The impact of the U.S.--China trade war on stock markets and financial contagion.
method Developed a novel jump-diffusion process to account for risk contagion, using high-frequency financial data and quasi-maximum likelihood estimator.
result Evidence of financial contagion from the U.S. to China, with changes in risk contagion channels.

Study negative discount rate effects on perpetual options in Lévy models.

problem Negative discount rate impacts perpetual American and Swing options in Lévy models.
method Analyze perpetual American and put options in exponential Lévy models with negative discount rate, identify critical continuation prices, and generalize to Swing type problems.
result Double continuation region arises in negative discount rate cases, identified by critical prices.

This paper proposes learning to jump for generative modeling of sparse, skewed, heavy-tailed data.

problem Limited ability of diffusion models in modeling sparse, skewed, heavy-tailed data.
method Forward count thinning process and reverse count thickening process to train a deep neural network.
result Learning to jump performs better than learning to denoise for non-negative, sparse data.

The paper introduces walks with jumps for modeling neuron activity in hyperbolic space.

problem Encoding neuron activity sequences in hyperbolic space.
method Introducing walks with jumps in hyperbolic geometry to model neuron activity.
result Endpoints of walks with jumps do not fully encode the sequence of jump times.

Study shows delayed and persistent implied volatility changes after return jumps.

problem Delayed and gradual movements in implied volatility after return jumps indicate market inefficiency.
method Minute-by-minute data on S&P 500 index options, analyzing implied volatility from at-the-money options and out-of-the-money puts.
result Implied volatility is adjusted asymmetrically after return jumps, especially for negative jumps.

Study optimizes dividend strategies for risk processes with Lévy jumps.

problem Optimizing dividend payments in risk processes with Lévy jumps.
method Analyzes spectrally positive and negative Lévy processes, using scale functions.
result Periodic barrier strategy is optimal for spectrally negative Lévy processes with completely monotone Lévy density.

In most sampling algorithms, including Hamiltonian Monte Carlo, transition rates between states correspond to the probability of making a transition in a single time step, and are constrained to be less than or equal to 1. We derive a Hamiltonian Monte Carlo algorithm using a continuous time Markov jump process, and ar…

2015-09-13abs ↗pdf ↗

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.

Estimates Heston model with jumps in asset prices using Bayesian regression and particle filtering.

problem Estimating the Heston model with jumps in asset prices.
method Bayesian regression combined with particle filtering method to handle jumps.
result Improves the estimation of key parameters in the Heston model with jumps.

Investment and insurance decisions are studied in a model with nonlinear portfolio frictions and background risk.

problem Investment and insurance decisions under a model with nonlinear portfolio frictions and background risk.
method Dynamic programming approach to find optimality conditions.
result Agent can choose to assume, partially assume, or purchase total insurance against adverse jumps in wealth.

New CTRW model with memory explains long-term return autocorrelation.

problem Explaining long-term autocorrelation in financial returns.
method Proposed a Directed Continuous-Time Random Walk (CTRW) model with memory, considering only positive jumps and dependence on previous jumps.
result Bid-ask bounce explains only a small fraction of the long-term autocorrelation in financial returns.

Sustaining efficiency and stability by properly controlling the equity to asset ratio is one of the most important and difficult challenges in bank management. Due to unexpected and abrupt decline of asset values, a bank must closely monitor its net worth as well as market conditions, and one of its important concerns …

2010-04-05abs ↗pdf ↗

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.

Estimates change point in high-dimensional dynamic graphical models.

problem Detecting change points in high-dimensional graphical models.
method Developed an estimator with Op(ψ2)O_p(ψ^{-2}) rate of convergence, established asymptotic distribution under high-dimensional scaling.
result Asymptotic distribution characterized under vanishing and non-vanishing jump size regimes.

A discrete diffusion model learns denoising, scoring, and bridging in different coordinates.

problem Understanding what a discrete diffusion model learns in different coordinate systems.
method Rigorous derivation of continuous-time Markov chain ELBO, Oracle Distance theorem, and exact coordinates for optimizer.
result The negative ELBO is exactly equal to the data entropy plus the path KL from the oracle reverse process to the learned one.

Study examines asymmetry impacts on Japanese stock market volatility modeling and forecasting.

problem Understanding asymmetry's impact on modeling and forecasting realized volatility in Japanese stock markets.
method Employed heterogeneous autoregressive (HAR) models with three types of asymmetry: positive and negative realized semivariance, asymmetric jumps, and leverage effects.
result Leverage effects significantly influence realized volatility modeling and forecast performance in Japanese stock markets.

This paper considers magnitude, asymptotics and duration of drawdowns for some Lévy processes. First, we revisit some existing results on the magnitude of drawdowns for spectrally negative Lévy processes using an approximation approach. For any spectrally negative Lévy process whose scale functions are well-behaved at …

2015-06-28abs ↗pdf ↗

This paper demonstrates the usefulness and importance of the concept of honest times to financial modeling. It studies a financial market with asset prices that follow jump-diffusions with negative jumps. The central building block of the market model is its growth optimal portfolio (GOP), which maximizes the growth ra…

2008-08-21abs ↗pdf ↗

Theoretical models applied to option pricing should take into account the empirical characteristics of the underlying financial time series. In this paper, we show how to price basket options when assets follow a shifted log-normal process with jumps capable of accommodating negative skewness. Our technique is based on…

2013-12-16abs ↗pdf ↗

The paper examines the short-time implied volatility of additive processes and finds key parameters.

problem Characterizing the short-time implied volatility of equity markets.
method Examined pure jump exponential additive processes with power-law scaling parameters.
result The implied volatility is consistent with equity market characteristics if and only if β=1 and δ=-1/2.

News might trigger jump arrivals in financial time series. The "bad" and "good" news seems to have distinct impact. In the research, a double exponential jump distribution is applied to model downward and upward jumps. Bayesian double exponential jump-diffusion model is proposed. Theorems stated in the paper enable est…

2014-04-08abs ↗pdf ↗

The problem of existence of solution for the Heath-Jarrow-Morton equation with linear volatility and purely jump random factor is studied. Sufficient conditions for existence and non-existence of the solution in the class of bounded fields are formulated. It is shown that if the first derivative of the Levy-Khinchin ex…

2009-11-05abs ↗pdf ↗

Study reveals strong co-jumping behavior in U.S. yield curves compared to Europe.

problem Understanding co-jumps in interest rate futures markets.
method Localized co-jumps through wavelet coefficients, identified statistically significant ones, and analyzed using high frequency data.
result Stronger co-jumping behavior in U.S. yield curves compared to European ones.

Estimates change point in high dimensional time series models.

problem Change point estimation in high dimensional time series.
method Plug-in least squares estimator with sufficient conditions for adaptivity.
result Optimal rate of convergence Op(ξ2)O_p(ξ^{-2}) in integer scale.

We investigate the extension of the multilevel Monte Carlo path simulation method to jump-diffusion SDEs. We consider models with finite rate activity, using a jump-adapted discretisation in which the jump times are computed and added to the standard uniform dis- cretisation times. The key component in multilevel analy…

2011-06-23abs ↗pdf ↗