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.
Efficiently reconstructs jump-diffusion processes from data using neural networks.
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…
The paper simplifies complex jump-diffusion markets to complete models.
Optimal wealth strategy derived for jump-diffusion models with liabilities.
We investigate which jump-diffusion models are convexity preserving. The study of convexity preserving models is motivated by monotonicity results for such models in the volatility and in the jump parameters. We give a necessary condition for convexity to be preserved in several-dimensional jump-diffusion models. This …
Study on hedging risky assets with jumps and costs.
Study short maturity Asian options in jump-diffusion models with local volatility.
Formula for European option pricing under jump diffusion model.
This research improves option pricing models using Heston, GARCH, and jump diffusion models.
RL for jump-diffusions applies to financial portfolio selection and option hedging.
Develops efficient methods for approximating densities of financial models with jumps.
Python package ajdmom simplifies moment formula derivation for jump diffusions.
In this article, a compact finite difference method is proposed for pricing European and American options under jump-diffusion models. Partial integro-differential equation and linear complementary problem governing European and American options respectively are discretized using Crank-Nicolson Leap-Frog scheme. In pro…
Paper develops models for better HFT and algorithmic trading.
Generative model handles varying data dimensions using jump diffusion processes.
In this paper, we are presenting a method for estimation of market parameters modeled by jump diffusion process. The method proposed is based on Gibbs sampler, while the market parameters are the drift, the volatility, the jump intensity and its rate of occurrence. Demonstration on how to use these parameters to estima…
In this short paper, in order to price occupation-time options, such as (double-barrier) step options and quantile options, we derive various joint distributions of a mixed-exponential jump-diffusion process and its occupation times of intervals.
Proposes a new jump-diffusion model for option pricing.
Study on short-term behavior of ATM-IV for jump-diffusion model.
In mathematical finance a popular approach for pricing options under some Levy model is to consider underlying that follows a Poisson jump diffusion process. As it is well known this results in a partial integro-differential equation (PIDE) that usually does not allow an analytical solution while numerical solution bri…
New deep learning method for option pricing in jump-diffusion models.
In this paper we outline methodology to efficiently simulate (jump) diffusion bridge sample paths without discretisation error. We achieve this by considering the simulation of conditioned (jump) diffusion bridge sample paths in light of recent work developing a mathematical framework for simulating finite dimensional …
Paper models transition risk using jump-diffusion model to price credit swaps.
Paper solves MV portfolio selection in jump-diffusion models with no-shorting constraint.
This paper uses Malliavin calculus to price and compute delta of financial derivatives in jump-diffusion models.
Paper develops semi-analytic method for American options in time-dependent jump-diffusion models.
In this article we extend earlier work on the jump-diffusion risk-sensitive asset management problem [SIAM J. Fin. Math. (2011) 22-54] by allowing jumps in both the factor process and the asset prices, as well as stochastic volatility and investment constraints. In this case, the HJB equation is a partial integro-diffe…
Develops a new model for pricing without arbitrage opportunities.
Refining previously known estimates, we give large-strike asymptotics for the implied volatility of Merton's and Kou's jump diffusion models. They are deduced from call price approximations by transfer results of Gao and Lee. For the Merton model, we also analyse the density of the underlying and show that it features …
The aim of this paper is to examine the time scaling of the semivariance when returns are modeled by various types of jump-diffusion processes, including stochastic volatility models with jumps in returns and in volatility. In particular, we derive an exact formula for the semivariance when the volatility is kept const…
In this article, a three-time levels compact scheme is proposed to solve the partial integro-differential equation governing the option prices under jump-diffusion models. In the proposed compact scheme, the second derivative approximation of unknowns is approximated by the value of unknowns and their first derivative …
The paper models stock returns using -Gaussians and negative binomials.
Proposes MLEs for MMJDM with EM-algorithm.
We suggest a simple reduction of pricing European options in affine jump-diffusion models to pricing options with modified payoffs in diffusion models. The procedure is based on the conjugation of the infinitesimal generator of the model with an operator of the form $e^{iΦ(-i\dd_x)}$ (gauge transformation in the dual s…
In this paper, we study the asymptotic behaviors of implied volatility of an affine jump-diffusion model. Let log stock price under risk-neutral measure follow an affine jump-diffusion model, we show that an explicit form of moment generating function for log stock price can be obtained by solving a set of ordinary dif…
Affine jump-diffusions constitute a large class of continuous-time stochastic models that are particularly popular in finance and economics due to their analytical tractability. Methods for parameter estimation for such processes require ergodicity in order establish consistency and asymptotic normality of the associat…
In this paper we consider a jump-diffusion dynamic whose parameters are driven by a continuous time and stationary Markov Chain on a finite state space as a model for the underlying of European contingent claims. For this class of processes we firstly outline the Fourier transform method both in log-price and log-strik…
Paper improves American option valuation in complex models.
The paper examines conditions for stochastic invariance of cones in SPDEs with jumps.
Paper explores two methods for optimal portfolio selection in financial markets.
In mathematical Finance calculating the Greeks by Malliavin weights has proved to be a numerically satisfactory procedure for finite-dimensional Itô-diffusions. The existence of Malliavin weights relies on absolute continuity of laws of the projected diffusion process and a sufficiently regular density. In this article…
Unified q-learning for mean-field jump-diffusion models with unobservable population distribution.
Unified framework for growth models with environmental risk and pollution-dependent disasters.
Study on MMV in jump-diffusion models resolves MV's non-monotonicity issues.
Study parameter sensitivities in bond pricing models with jumps.
In this paper we derive an easily computed approximation to European basket call prices for a local volatility jump-diffusion model. We apply the asymptotic expansion method to find the approximate value of the lower bound of European basket call prices. If the local volatility function is time independent then there i…
We consider a Markov process , which is the solution of a stochastic differential equation driven by a Lévy process and an independent Wiener process . Under some regularity conditions, including non-degeneracy of the diffusive and jump components of the process as well as smoothness of the Lévy density of $Z…
Bayesian inference for biochemical reaction networks using jump-diffusion approximations.