Zhiliang Ying

I took his class in the Spring 2004 semester. He wasn't available during his scheduled office hours. He was always too busy. So what was the point in designating office hours on the syllabus and during the start of the semester when he can't see any of his students at anytime? That was just for show. Each attempted visit to his office was a wasted trip. He's a low talker and a "small writer", often barely audible to hear and his handwriting is so miniscule the students needed binoculars to see the board even from the first row. He has a good sense of humor though.

General knowledge of statistical methods in finance. Detailed methods and their realizations.

Most basic stuff in probabilities (expectation, variance, CLT, etc.), Various distributions, law of large numbers

A general introduction to mathematical statistics and statistical decision theory. Elementary decision theory, Bayes inference, Neyman-Pearson theory, hypothesis testing, most powerful unbiased tests, confidence sets. Estimation: methods, theory, and asymptotic properties. Likelihood ratio tests, multivariate distribution.

The homeworks are incredibly long, mundane and useless since we spent more time trying to learn SAS than about the Analysis of Categorical Data. The Midterm was reasonable, but the Final Exam was impossible, as well as unreasonably and ridiculously full of theory and concepts barely touched upon in the lectures and textbook. The final exam came out of left field and it felt like being in the twilight zone going nowhere but He//.

I learned many knowledge on financial models

Markowitz mean-variance portfolio theory, capital asset pricing model, multivariate linear regression, factor analysis, financial time series models, fixed income securities and credit risk, survival analysis models, value at risk, multivariate distributions, copula, interest rate models, principal component analysis, modeling high frequency trading.

Standard introductory materials to probability.

Basic stuff, estimation (UMVUE, decision theory), testing (UMP, LRT, composite null, contiguity)

I wish this course would move more quickly and provide more materials, in more depth, with much more