Yanghui Liu

Education

Ph.D., Mathematics, University of Kansas Lawrence KS

M.S., Mathematics, Chinese Academy of Science Wuhan China

B.S., Mathematics, Nanchang University Nanchang China

Journal Articles

Zhou, H., Hu, Y., & Liu, Y. (2023). Backward Euler method for stochastic differential equations with non-Lipschitz coefficients driven by fractional Brownian motion. BIT Numerical Mathematics , (2023) 63:40. In Progress.

Chong, C., Hoffmann, M., Liu, Y., Rosenbaum, M., & Szymanski, G. (2023). Statistical inference for the rough volatility: Central limit theorem. Annals of Applied Probability, In Progress.

Leon, J., Liu, Y., & Tindel, S. (2023). Euler scheme for SDEs driven by fractional brownian motions: Malliavin differentiability. Stochastic Processes and their applications,

CHONG, C., HOFFMANN, M., Liu, Y., ROSENBAUM, M., & SZYMANSKI, G. (2023). Statistical inference for rough volatility: minimax theory. . Annals of Statistics,

Leon, J., Liu, Y., & Tindel, S. (2023). Euler scheme for SDEs driven by fractional brownian motions: integrability and convergence in law. Annals of Applied Probability,

Liu, Y., Hu, Y., & Nualart, D. (2021). Crank-Nicolson scheme for stochastic differential equations driven by fractional Brownian motions. Annals of Applied Probability, 2021, Vol. 31, No. 1, 39–83.

Liu, Y., Selk, Z., & Tindel, S. (2020). Convergence of trapezoid rule to rough integrals. Annales de l'Institut Henri Poincar\'e (B) Probabilit\'es et Statistiques., 2023, Vol. 59, No. 3, 1434–1462.

Liu, Y., & Tindel, S. (2020). Discrete rough paths and limit theorems. Annales de l'Institut Henri Poincar\'e, Probabilit\'es et Statistiques, 56(3). 1730--1774.

Hu, Y., Liu, Y., & Tindel, S. (2019). On the necessary and sufficient conditions to solve a heat equation with general Additive Gaussian noise. Acta Mathematica Scientia, 39(3). 669--690.

Liu, Y., Nualart, E., & Tindel, S. (2019). LAN property for stochastic differential equations with additive fractional noise and continuous time observation. Stochastic Processes and their Applications, 129(8). 2880--2902.

Liu, Y., & Tindel, S. (2019). First-order Euler scheme for SDEs driven by fractional Brownian motions: the rough case. Annals of Applied Probability, 29(2). 758--826.

Tindel, S., Liu, Y., & Lin, G. (2019). On the anticipative nonlinear filtering problem and its stability. Applied Mathematics and Optimization,

Hu, Y., Liu, Y., & Nualart, D. (2016). Rate of convergence and asymptotic error distribution of Euler approximation schemes for fractional diffusions. Annals of Applied Probability, 26(2). 1147--1207.

Hu, Y., Liu, Y., & Nualart, D. (2015). Taylor schemes for rough differential equations and fractional diffusions. Discrete and Continuous Dynamical Systems, Series B,

Liu, Y. Limit theorems for compensated weighted sums and  application to numerical approximations. Annals of Applied Probability,

Liu, Y., & Wang, X. Power variations and limit theorems for stochastic processes controlled  by fractional Brownian motions. Electronic Journal of Probability,

Presentations

Liu, Y. (2024, March 9). How volatile is the asset volatility?. Hunter Probability and Statistics Seminar, 3-27-2024..

Liu, Y. Compensated weighted sums and numerical approximations. Seminar on Stochastic Processes. Rice University. March 13-16.

Liu, Y. Compensated weighted sums and numerical approximations. AMS Sectional Meeting, Florida. March 23-24th.

Liu, Y. (2024, March 9). How Volatile is Asset Volatility?. 2nd Annual Faculty Research Symposium, Baruch College CUNY, March, 24, 2023..

Liu, Y. (2024, December 9). Statistical Inference for Rough Volatility. Applied Math Conference, University of Geosciences, Wuhan, Dec. 17-18, 2022..

Liu, Y. (2024, March 9). Numerical approximations for stochastic rough integrations. AMS Spring Central Virtual Sectional Meeting, Purdue University, March 26-27, 2022..

Liu, Y. (2024, October 9). Optimal rate and limit theorem for rough volatility. CUNY Probability Seminar. October 18, 2022..

Liu, Y. (2024, March 9). Numerical approximations for stochastic rough integrations. Seminar on Stochastic Processes, Lehigh University Mar 16-19, 2022.. Lehigh University

Liu, Y. How rough is volatility?. Eugene M. Lang Faculty Fellows Luncheon October 28, 2022..

Liu, Y. (2024, December 9). Numerical approximations for stochastic differential equations driven by fractional Brownian motion. Frontier Probability Day, December 3-5, 2021..

Liu, Y. (2021, January 21). Numerical Approximations for Rough Differential Equations. TU Berlin SPDE Seminar. Berlin, Germany: TU Berlin.

Liu, Y. (2021, February 19). Numerical Approximations for Rough Differential Equations. Columbia SPDE Seminar. New York City: Columbia University.

Liu, Y. (2021, November 20). Numerical solutions for stochastic differential equations. AMS Sectional Meeting. Mobile, Alabama: AMS.

Liu, Y. (2021, August 3). Numerical stochastic integrations and limit theorems. CBMS conference. Huntsville, Alabama: University of Alabama - Huntsville.

Liu, Y. (2020, September 15). Discrete Rough Paths and Applications to Numerical Approximations. CUNY Probability Seminar. CUNY Graduate Center: CUNY Graduate Center.

Liu, Y. Compensated weighted sums and numerical approximations. Conference on Applied Math, Wuhan, China, 12-17-2022..

Other Scholarly Works

Research Currently in Progess

Liu, Y., & Tasissa, A.(n.d.). Deep learning rough differential equations and its applications in finance.. In Progress.

Liu, Y., & Gatheral, J.(n.d.). On the volatility of rough SABR model . In Progress.

Liu, Y., & Wang, T.(n.d.). Parameter estimation of multiplicative SDEs via discrete observation . In Progress.

College

University

Professional