11 papers
Variance-Optimal Hedging in the Rough Hawkes--Heston Model
Yingli Wang, Xiaoyu Wang
We study variance-optimal stock hedging and the convergence of approximate strategies in the rough Hawkes--Heston model. Starting from the model's affine conditional transform and…
Improved Analysis for Hessian-free High-resolution Monte Carlo Sampling
Wujun Lv, Xiaoyu Wang, Yingli Wang +1
Hessian-free high-resolution (HFHR) dynamics augments underdamped Langevin dynamics (ULD) with reversible position diffusion for sampling problems that arise in machine learning. W…
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…
VIX and European options with jumps in the short-maturity regime
Desen Guo, Dan Pirjol, Xiaoyu Wang +1
We present a study of the short-maturity asymptotics for VIX and European option prices in local-stochastic volatility models with compound Poisson jumps. Both out-of-the-money (OT…
Sampling non-log-concave densities via Hessian-free high-resolution dynamics
Xiaoyu Wang, Yingli Wang, Lingjiong Zhu
We study the problem of sampling from a target distribution on , where can be non-convex, via the Hessian-free high-resolution (HFHR) dyna…
Regime-Switching Langevin Monte Carlo Algorithms
Xiaoyu Wang, Yingli Wang, Lingjiong Zhu
Langevin Monte Carlo (LMC) algorithms are popular Markov Chain Monte Carlo (MCMC) methods to sample a target probability distribution, which arises in many applications in machine…
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…
Non-Reversible Langevin Algorithms for Constrained Sampling
Hengrong Du, Qi Feng, Changwei Tu +2
We consider the constrained sampling problem where the goal is to sample from a target distribution on a constrained domain. We propose skew-reflected non-reversible Langevin dynam…
Generalized EXTRA stochastic gradient Langevin dynamics
Mert Gurbuzbalaban, Mohammad Rafiqul Islam, Xiaoyu Wang +1
Langevin algorithms are popular Markov Chain Monte Carlo methods for Bayesian learning, particularly when the aim is to sample from the posterior distribution of a parametric model…
Short-maturity options on realized variance in local-stochastic volatility models
Dan Pirjol, Xiaoyu Wang, Lingjiong Zhu
We derive the short-maturity asymptotics for prices of options on realized variance in local-stochastic volatility models. We consider separately the short-maturity asymptotics for…
Short-maturity asymptotics for VIX and European options in local-stochastic volatility models
Dan Pirjol, Xiaoyu Wang, Lingjiong Zhu
We derive the short-maturity asymptotics for European and VIX option prices in local-stochastic volatility models where the volatility follows a continuous-path Markov process. Bot…