Course Description



Course Outline

Session Topics Readings Homeworks
1 Basic statistics, distributions, hypothesis testing, maximum likelihood Lecturer handout hw1
2 Linear regression Lecturer handout hw2
3 Univariate time series analysis, white noise, AR, MA, ARMA, ARIMA, and GARCH Lecturer handout hw3
4 Kalman filter, dynamic system model Lecturer handout hw4
5 Multivariate time series and cointegration Lecturer handout hw5
6 Longitudinal data analysis Lecturer handout hw6
7 Measures (real analysis) and probability Lecturer handout hw7
8 Brownian motion calculus, Ito’s lemma Lecturer handout hw8
9 Calculus for martingales and semi-martingales Lecturer handout hw9
10 Extreme value theory Lecturer handout hw10
11 Markov chain Lecturer handout hw11
12 Bootstrapping Lecturer handout hw12


Recommended Readings

  1. All of Statistics: A Concise Course in Statistical Inference, Larry Wasserman
  2. All of Nonparametric Statistics, Larry Wasserman
  3. Statistical Analysis of Financial Data in S-Plus, René Carmona
  4. Likelihood-Based Inference in Cointegrated Vector Autoregressive Models, Søren Johansen
  5. Introduction To Stochastic Calculus With Applications (3rd Edition), Fima C. Klebaner
  6. Financial Calculus: An Introduction to Derivative Pricing, Martin Baxter, Andrew Rennie