dst 20200716 pengjin

Dr. Peng JIN
Associate Professor of Financial Mathematics
Division of Science and Technology
office: T3-502-R5


Curriculum Vitae


Aug 2006 - Nov 2009, Ph.D. in Mathematics, Bielefeld University, Germany
Sep 2004 - July 2006, Institute of Applied Mathematics, Chinese Academy of Sciences, China
Sep 2000 - Aug 2004, B.Sc. in Mathematics, Shandong University, China

Research Interests

Probability theory, mathematical finance

Current Teaching

FINM2013 Time Series for Finance and Macroeconomics
FINM3033 Risk Management in Finance

Selected Publications
  1. P. Jin: Brownian motion with singular time-dependent drift, J. Theoret. Probab., 30(2017), no. 4, 1499-1538.
  2. P. Jin, J. Kremer and B. Rüdiger: Exponential ergodicity of an affine two-factor model based on the α-root process, Adv. in Appl. Probab., 49(2017), no. 4, 1144-1169.
  3. P. Jin: On weak solutions of SDEs with singular time-dependent drift and driven by stable processes, Stoch. Dyn., 18(2018), no. 2, 1850013, 23 pp.
  4. P. Jin, J. Kremer and B. Rüdiger: Moments and ergodicity of the jump-diffusion CIR process, Stochastics, 91(2019), no. 7, 974-997.
  5. P. Jin, J. Kremer and B. Rüdiger: Existence of limiting distribution for affine processes, J. Math. Anal. Appl., 486(2020), no. 2, 123912, 31 pp.
  6. P. Jin: Uniqueness in law for stable-like processes of variable order, J. Theoret. Probab., 2020, https://doi.org/10.1007/s10959-020-00988-0
  7. M. Friesen, P. Jin and B. Rüdiger: Existence of densities for multi-type CBI processes, Stoch. Proc. Appl., 130(2020), no. 9, 5426–5452.
  8. M. Friesen, P. Jin and B. Rüdiger: Stochastic equation and exponential ergodicity in Wasserstein distances for affine processes, Ann. Appl. Probab., 30(2020), no. 5, 2165–2195.
  9. M. Friesen, P. Jin and B. Rüdiger: Existence of densities for stochastic differential equations driven by Lévy processes with anisotropic jumps, Ann. Inst. Henri Poincaré  Probab. Stat., to appear (2020+).
  10. M. Friesen and P. Jin: On the anisotropic stable JCIR process, ALEA Lat. Am. J. Probab. Math. Stat., 17(2020), no. 2, 643–674.
Grants and Projects
  • Co-PI, Stochastic functional differential equations with jumps and the boundary problems with measure data, No. 11861029, National Natural Science Foundation of China, 2019-2022.