Course Detail

Multivariate Time Series Analysis (41914)

Course Description by Faculty

  • Tsay, Ruey
  • Content

    This course investigates the dynamic relationships between variables, including analysis of large scale dependent data. It starts with linear relationships between two variables, including distributed-lag models and detection of unidirectional dependence (Granger causality). The dynamic models discussed include vector autoregressive models, vector autoregressive moving-average models, multivariate regression models with time series errors, co-integration and error-correction models, dynamic factor models, and multivariate volatility models. The course also addresses classification (or clustering) of large scale time series, principal component analysis, asymptotic principal component analysis, online recursive estimation, deep neural networks, and machine learning for dependent data.  Empirical data analysis is an integral part of the course. Students are expected to analyze many real data sets. Finally, the course discusses forecasting under the current data-rich environment. The main software used in the course includes the MTS and SLBDD  packagesin R, but students may use their own software if preferred.

  • Prerequisites
    Business 41910 or equivalent course on univariate time series analysis. PhD Only: strict. MBA/Masters students must have prereq or instructor permission: strict. BUSN 41914=STAT 33700
    • PhD - students only

  • Materials
    Textbook: (1) Ruey S. Tsay, Multivariate Time Series Analysis with R and Financial Applications , First Edition (Wiley, 2014). Optional. (2) Daniel Pena and Ruey S. Tsay, Statistical Learning of Big Dependent Data, First Edition (Wiley 2021). Optional.
  • Grades
    Homework assignments (20%), Mid-term exam (40%), and final project (40%).
    • Allow Provisional Grades (For joint degree and non-Booth students only)

    • No auditors

  • Syllabus
  • Winter 2023Section: 41914-50T 1:30PM-4:30PMHarper Center3A - Seminar RoomIn-Person Only
Description and/or course criteria last updated: October 31 2022