activity
20092022
most citedLocal linear quantile estimation for nonstationary time series

108 citations · 152 across the 8 of their papers we have counts for

collaborators

14 papers

math.OC2022

Stability of Equilibria in Time-inconsistent Stopping Problems

Erhan Bayraktar, Zhenhua Wang, Zhou Zhou

We investigate the stability of equilibrium-induced optimal values with respect to (w.r.t.) reward functions and transition kernels for time-inconsistent stopping problems…

math.OC2020

Singular Perturbation of Zero-Sum Linear-Quadratic Stochastic Differential Games

Beniamin Goldys, James Yang, Zhou Zhou

We investigate a class of zero-sum linear-quadratic stochastic differential games on a finite time horizon governed by multiscale state equations. The multiscale nature of the prob…

math.OC2020

Multiscale Linear-Quadratic Stochastic Optimal Control With Multiplicative Noise

Beniamin Goldys, Gianmario Tessitore, James Yang +1

We investigate the asymptotic properties of a finite-time horizon linear-quadratic optimal control problem driven by a multiscale stochastic process with multiplicative Brownian no…

math.ST2020

Statistical Inference for High Dimensional Panel Functional Time Series

Zhou Zhou, Holger Dette

In this paper we develop statistical inference tools for high dimensional functional time series. We introduce a new concept of physical dependent processes in the space of square…

math.ST2020

Estimation and Inference of Time-Varying Auto-Covariance under Complex Trend: A Difference-based Approach

Yan Cui, Michael Levine, Zhou Zhou

We propose a difference-based nonparametric methodology for the estimation and inference of the time-varying auto-covariance functions of a locally stationary time series when it i…

math.ST20192 cited

Globally Optimal And Adaptive Short-Term Forecast of Locally Stationary Time Series And A Test for Its Stability

Xiucai Ding, Zhou Zhou

Forecasting the evolution of complex systems is one of the grand challenges of modern data science. The fundamental difficulty lies in understanding the structure of the observed s…