
A master at fostering understanding.
Encourages deep understanding and curiosity.
Always goes the extra mile for students.
Helps students see the joy in learning.
Creates a safe space for learning and growth.
Dr. Gerald Cheang is a Senior Lecturer in the School of Mathematical Sciences within the College of Sciences at Adelaide University. He holds a BSc (Hons) from the University of Auckland, New Zealand, and MA and PhD degrees from Yale University, United States. Additionally, Cheang possesses a Postgraduate Diploma in Teaching of Higher Education from Nanyang Technological University, Singapore, and Zetifikat Deutsch als Fremdsprache certification from the Goethe Institut. Prior to his current role, he served as Senior Lecturer in the School of Information Technology and Mathematical Sciences at the University of South Australia. Cheang's research specializations encompass mathematical finance, stochastic processes, asset pricing theory, non-parametric estimation, model selection theory, and approximation theory. He is eligible to supervise Masters and PhD students and currently co-supervises doctoral candidates, including Ms. Xiaoni Wu on 'From Policy to Plate: Optimizing Agrifood Supply Chains for Sustainability and Inclusive Development' and Mrs. Hansi Kaushalya Perera Thanippuli Kankanamalage on 'Collision probability modelling for short-term satellite encounters'. Cheang teaches undergraduate courses such as Advanced Statistical Theory (STAT 3005), Advanced Stochastic Processes (MATHX 200), Time Series Analysis (MATHX 313), and Statistical Theory (STAT 2003).
Cheang has made notable contributions to quantitative finance and applied mathematics through his publications. Key works include 'A numerical approach to pricing exchange options under stochastic volatility and jump-diffusion dynamics' with L.P.D.M. Garces (Quantitative Finance, 2021), 'Representation of exchange option prices under stochastic volatility jump-diffusion dynamics' with L.P.D.M. Garces (Quantitative Finance, 2020), 'Perpetual exchange options under jump-diffusion dynamics' with G. Lian (Applied Mathematical Finance, 2015), 'Approximate hedging of options under jump-diffusion processes' with K.F. Mina and C. Chiarella (International Journal of Theoretical and Applied Finance, 2015), 'Change of numéraire and a jump-diffusion option pricing formula' with G.A. Teh (2014 book chapter), 'Approximation with neural networks activated by ramp sigmoids' (Journal of Approximation Theory, 2010), and 'A Better Approximation for Balls' with A.R. Barron (Journal of Approximation Theory, 2000). These papers address critical challenges in option pricing under jump-diffusion and stochastic volatility models, neural network approximations, and hedging strategies, with several receiving citations in Scopus and Web of Science, such as 37 for the 2010 approximation theory paper.
