collaborators

8 papers

q-fin.MF2026

Microstructural Foundation for the Rough Hawkes--Heston Model

Yingli Wang, Yinhao Wu, Lingjiong Zhu

Hawkes-based microstructural foundations for rough volatility, leverage, and rough Heston-type limits were developed by El Euch et al. (2018, Finance Stoch., 22(2), 241--280) and c…

math.PR2026

An Eyring--Kramers Law for the Hypoelliptic Third-Order Langevin Diffusion

Yingli Wang, Lingjiong Zhu

We prove an Eyring--Kramers law for metastable transitions of the hypoelliptic third-order Langevin diffusion in the low-temperature limit. This diffusion is a three-level Markovia…

math.PR2026

Weak Equilibrium Measures and Capacity--Hitting Identities for the Hypoelliptic Third-Order Langevin Diffusion

Ping He, Xiaodan Li, Yingli Wang +1

We construct weak equilibrium measures and weak capacities for the hypoelliptic third-order Langevin diffusion motivated by an accelerated sampling algorithm (Mou et al. (2021) \te…

stat.ML2026

Variance Reduction for Stochastic Gradient Generalized Non-reversible Langevin Monte Carlo Algorithms

Bingye Ni, Xiaoyu Wang, Yingli Wang +1

We study the leading-order fluctuation of stochastic gradient Euler-Maruyama estimators for generalized non-reversible Langevin dynamics. Under structural assumptions tailored to t…

math.PR2026

Rough Heston model as the scaling limit of bivariate cumulative heavy-tailed INAR processes: Weak-error bounds and option pricing

Yingli Wang, Zhenyu Cui, Lingjiong Zhu

We study nearly unstable bivariate cumulative heavy-tailed INAR() processes and show that, under a one-factor parameterization and a suitable scaling, they converge to the…

stat.ML2026

Accelerating Constrained Sampling: A Large Deviations Approach

Yingli Wang, Changwei Tu, Xiaoyu Wang +1

The problem of sampling a target probability distribution on a constrained domain arises in many applications including machine learning. For constrained sampling, various Langevin…