Yu-Sin Chang, Ph.D., FRM
Assistant Professor
- Milwaukee WI UNITED STATES
- Mathematics
Dr. Yu-Sin Chang's research interests include probability, stochastics, and financial mathematics.
Education, Licensure and Certification
Ph.D.
Applied Mathematics
Illinois Institute of Technology
M.S.
Financial Engineering
University of Michigan-Ann Arbor
M.S.
Money and Banking
National Chengchi University
B.S.
Money and Banking
National Chengchi University
Biography
Areas of Expertise
Accomplishments
Society for Industrial and Applied Mathematics
2018-12-12
Early Career Travel Award
Affiliations
- Association for Women in Mathematics (AWM) : Member
- Society for Industrial and Applied Mathematics (SIAM) : Member
Social
Event and Speaking Appearances
Markovian Consistency of Multivariate Markov Processes
Joint Mathematics Meetings Denver, CO
2020-01-16
Systemic Risk and the Dependence Structures
SIAM Conference on Financial Mathematics and Engineering Toronto, Ontario Canada
2019-06-16
Third Eastern Conference on Mathematical Finance
Illinois Institute of Technology, Chicago, IL, October, 2018
Research Grants
Summer Faculty Development Grant
Milwaukee School of Engineering $3000
2020-05-01
One long-term objective of this project is to study the stochastic dependence between the coordinates of a multivariate Markov process. The interconnection or dependence structure between objects within a stochastic dynamical system plays a critical role in modeling various phenomena from a wide range of applied fields. Various applications are related to, among others, the linked financial institutions within a financial system, sociology, criminology and terrorism, social networks, ruin problems in insurance, and credit risk. For finite dimensional multivariate random variables the dependence structure between their components is fully characterized in terms of the so-called copulae and the Sklar's Theorem. On the other hand, the analysis or the characterization of the dependence structure between the components of a multivariate stochastic process is a relatively new area. In part, this project contributes to this area.
Selected Publications
Systemic Risk and the Dependence Structures
arXiv PreprintChang, Y.S.
2018
We propose a dynamic model of dependence structure between financial institutions within a financial system and we construct measures for dependence and financial instability. Employing Markov structures of joint credit migrations, our model allows for contagious simultaneous jumps in credit ratings and provides flexibility in modeling dependence structures. Another
key aspect is that the proposed measures consider the interdependence and reflect the changing economic landscape as financial institutions evolve over time. In the final part, we give several examples, where we study various dependence structures and investigate their systemic instability measures. In particular, we show that subject to the same pool of Markov chains, the simulated Markov structures with distinct dependence structures generate different sequences of systemic instability