Cindy L. Yu
- Ph.D., Statistics, Cornell University, 2005
STAT 690A: Continuous Time Asset Pricing Models
Spring 2023 by Professor Cindy Yu
- This is a 3 credit course.
- This course provides an introduction to continuous-time finance for graduate students who are interested in learning classical math finance, and major in Statistics, Economics, Mathematics, or Business.
- My goals are (i) to help students develop necessary mathematical tools to understand continuous-time finance models; (ii) to review some major results of continuous-time finance; (iii) to introduce students to some active research areas in financial statistics, including machine learning and Bayesian analyses.
- Topics that I plan to cover include: Black-Scholes option pricing model, Option Pricing with Stochastic Volatility and Jumps, Dynamic Term Structure Interest Rate Models, Credit Risk Modeling, Some Examples of Statistical Applications in Asset Pricing (Markov Chain Monte Carlo Method, and Machine Learning Methods)
Stat 641, or Stat 642, or a Stochastic Process course. Students with equivalent background should request permission of the instructor.
I will draw materials from different books and articles in my lectures. Therefore, there is no single textbook that is required for this course. Studying original academic articles is an integral part of Ph.D. education. I will recommend some important articles for each major topic covered in the course to read in the reference list. The following books are classical math finance books, and are recommended for this course.
• Duffie, Darrell, 2001, Dynamic Asset Pricing Theory, Princeton University Press.
• Shreve, Steven, 2004, Stochastic Calculus for Finance II, Springer.
• Ingersoll, Jonathan, 1987, Theory of Financial Decision Making, Rowman and Littlefield.
Your grade of the course will be based on 4-5 homework assignments (80%) and a final course presentation (20%) of important articles in the area.