Data-driven Financial Econometrics

STATS241P

Stanford School of Humanities and Sciences


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Description

Approximate dynamic programming and time series approaches in options, interest rate, and credit markets. Nonlinear least squares, nonparametric regression and model selection. Behavioral finance and efficient markets. Economic capital, risk measures, and regulatory supervision. Quantile regression, extreme value theory, and applications to market risk analytics. Empirical Bayes approach to pricing insurance contracts. Corporate bonds, bond ratings, and corporate default analytics.

Prerequisites

  • STATS240P or equivalent
  • A conferred Bachelor’s degree with an undergraduate GPA of 3.3 or better.

Topics include

  • Substantive and empirical modeling approaches in options, interest rate, and credit markets
  • Nonlinear least squares, logistic regression and generalized linear models
  • Nonparametric regression and model selection
  • Multivariate time series modeling and forecasting
  • Vector autoregressive models and cointegration
  • Risk measures, models and analytics

Course Availability

The course schedule is displayed for planning purposes – courses can be modified, changed, or cancelled. Course availability will be considered finalized on the first day of open enrollment. For quarterly enrollment dates, please refer to our graduate education section.

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