Jiajing Sun

Jiajing Sun

PhD, CFA, FIMA, Member of the London Mathematical Society. Associate Professor and the Deputy Director of the Department of Statistics and Data Science, School of Economics and Management, University of the Chinese Academy of Sciences.

Financial Econometrics

Postgraduate course, University of Chinese Academy of Sciences, School of Economics and Management, 2014

This course focuses on financial econometrics, covering the core theories and methodologies used to model and analyze financial data. As the lead instructor, I provided lectures on the key econometric techniques and their applications in finance, including asset pricing models, market efficiency, volatility forecasting, and derivative pricing.

Course Content:

  1. Introduction to Financial Data:
    • Characteristics of financial data and sources of data.
    • Overview of time series models relevant to financial data analysis.
  2. Predicting Financial Returns:
    • Market Efficiency and its implications for asset pricing.
    • ARMA Models: Autoregressive moving average models.
  3. Predicting Market Volatility:
    • Introduction to ARCH and GARCH models for volatility forecasting.
    • EGARCH models for asymmetric volatility.
  4. Event Study Methodology:
    • Analysis of abnormal returns and testing abnormal returns using a cross-sectional approach.
  5. Asset Pricing Models:
    • Review of CAPM theory, empirical testing of CAPM, and multifactor pricing models (e.g., Arbitrage Pricing Theory).
  6. Present-Value Relations:
    • The relationship between prices, dividends, and returns.
  7. Derivative Pricing:
    • Introduction to Brownian motion, Black-Scholes, Merton models, and the martingale approach.
  8. Nonlinear Financial Data Models:
    • Bilinear models, piecewise linear models, TAR, STAR, and SETAR models.

Additional Topics:

If time permits, we will explore more advanced topics such as spectrum analysis, Kalman filters, Markov regime-switching models, and high-frequency data models.

Teaching Methodology:

This course combines theoretical instruction with practical applications using real-world financial data. The course uses R programming and MATLAB for data analysis and model implementation.

Hours: 40 hours

  • “The Econometrics of Financial Markets” by John Y. Campbell, Andrew Lo, and A. Craig MacKinlay, Princeton University Press.
  • “Time Series Analysis” by James Hamilton, Princeton University Press, 1994.
  • “Analysis of Financial Time Series” by R. S. Tsay, 3rd edition, People’s Posts and Telecommunications Press, 2012.